Visiting Student Summer Undergraduate Research Program

NYU Abu Dhabi welcomes the unique experiences and insights visiting students bring to the university and region.

The Visiting Student Summer Undergraduate Research Program provides an opportunity for undergraduate students at NYU New York, NYU Shanghai, and UAE-based universities to take part in research projects at NYUAD over the summer.

Students in this program have the chance to engage in hands-on research experiences, collaborating with faculty members, researchers, and fellow students in a dynamic and intellectually stimulating environment. By bringing together students from different NYU campuses and local universities in the UAE, the program promotes a cross-cultural exchange of ideas and perspectives.

Professor David Holland speaks with undergraduate students at NYU Abu Dhabi.

Summer positions, eligibility criteria, and the application process can be found below. Students are welcome to apply for up to three positions but must submit a separate application for each position.

Students must hold a valid UAE residence visa or UAE citizenship in order to be eligible to take part in the program. NYUAD is unable to sponsor a residence visa solely for the purpose of this program. For NYU New York and NYU Shanghai students, this means the program is open only to students sponsored by NYUAD and students who are otherwise resident in the UAE.

Summer 2025

Summer 2025 positions will be posted in January/February 2025.

2024 Application Details

	Details
Application Deadline	February 29, 2024, 5pm GST
Program Dates	Eight Weeks NYU Students: May 20-July 12, 2024 External Students: June 3-July 25, 2024
Program Location	All summer 2024 positions are expected to take place in person, on the NYUAD campus.
Program Funding	Students will be awarded USD 150 per week* and will be provided with on-campus accommodation free of charge. * The funds transfer process amongst program participants will be dependent on the student's association with the institution.

Eligibility Criteria

The conditions of eligibility are as follows:
- Students must be currently enrolled in full-time, undergraduate study at a UAE-based university. While the program is designed for sophomore and junior undergraduate students, first-year and senior students (who would have just graduated) may be considered.
- Students must hold a valid UAE residence visa or a UAE citizenship in order to be eligible to take part in the program. NYUAD is unable to sponsor a residence visa solely for the purpose of this program.
- Students must have a cumulative GPA above 3.3. Students who not meet this requirement may still apply — it is up to the discretion of the supervising faculty whether you can be considered.
- The position should usually be in line with the student’s declared major and academic interests.
- Students must have valid health insurance during the period of the research placement.
- Students will be required to enroll in a zero-credit, pass/fail class and attend an orientation session.
- Students must be available for the full duration of the advertised position.
The conditions of eligibility are as follows:
- Students must hold a valid UAE residence visa or a UAE citizenship in order to be eligible to take part in the program. NYUAD is unable to sponsor a residence visa solely for the purpose of this program. For NYU New York and NYU Shanghai students, this means the program is open only to students sponsored by currently at NYUAD and students who are otherwise resident in the UAE.
- Students must be currently enrolled in full-time, undergraduate study at NYU New York or NYU Shanghai.
- Only students who have successfully completed at least 44 credits and have a GPA above 3.3 are eligible to take part. Students who do not meet this requirement may still apply — it is up to the discretion of the supervising faculty whether you can be considered.
- Students must be in good academic and disciplinary standing.
- The position should usually be in line with the student’s declared major and academic interests.
- Students will be required to enroll in a zero-credit, pass/fail class and attend an orientation session.
- Students must be available for the full duration of the advertised position.

Arts and Humanities
Engineering
Science
Social Science

Arts and Humanities Summer Positions

Research Project Description:
Research Center/ Lab:	al Mawrid Arab Center for the Study of Art
Faculty Supervisor's Name:	Salwa Mikdadi
The students will conduct library and archival research to produce a thematic poster exhibition or write a short essay using the Center’s archive of primary documents on Arab art, most of the documents are in Arabic language.
Timeline:
June 10-31: Select research topic and submit an abstract and a bibliography. July 1-26: Create Poster Exhibit. The undergraduate students will be working under the supervision of al Mawrid's Center's researchers to create a text-based exhibition in the Center’s vitrines and/or poster exhibitions. OR write a 1,500-2,000 word essay.
Responsibilities:
The student will study and complete assignments and practicum in museum studies and art history, through applied practices of curatorship and museum research standard.
Skills Needed:
Excellent communication skills in both written and spoken Arabic and English.
Class Level:	Sophomore, junior, or senior
Major:	Arts, arts history
Other Requirements:	Familiar with research methodology and the use of library databases

Research Project Description:
Research Center/ Lab:	Open Gulf
Faculty Supervisor's Name:	David Wrisley
OpenGulf (opengulf.github.io), a transdisciplinary digital humanities research group working on historical materials about the Arabian Gulf region, is looking for a visiting student researcher. The data for this project include a searchable text version of Lorimer's Gazetteer of the Persian Gulf, Oman and Central Arabia and a large dataset of annotated places found in it. The student researcher will work (1) to refine the data from one portion of the Arabian Gulf region, visualize and write about that data and (2) to extract entities and quantities from this historical corpus (animals, plants, temperature ranges, objects, water terminology, construction materials, rainfall amounts) to build a geocoded dataset for a web-based environment atlas. A sample visualization of such data (for camels) created by a visiting researcher last summer can be found here: opengulf.github.io/camels/.
Timeline:
Week 1: Initial review of the data. Identification of region of interest and entities for extraction. Week 2: Orientation in research tasks according to the researcher's skill set. Week 3: Data verification and historical research. Geocoding. Week 4: Data verification and historical research. Geocoding. Week 5: Data verification and historical research. Geocoding. Week 6: Publishing the environmental data. Exploratory visualization. Weeks 7-8: Writing up results. Documenting work. (samples here: opengulf.github.io/TeamBlogs/)
Responsibilities:
Creating dataset Verification of data Documenting work Communicating with project team Designing and implementing the web maps Publishing the finalized data
Skills Needed:
The ability to document one's work, to work both independently and in a team are a must. Experience with data cleaning, preparation and verification are desirable, as well as GIS/web mapping. Some knowledge of Arabic or Wikidata and interest in the Arabian Gulf region and climate/environmental history are a plus, but not required.
Class Level:	Any
Major:	Humanities, social science, history, interactive media arts, Middle Eastern studies, global liberal studies, anthropology, geography
Other Requirements:	OpenGulf is a global, multi-institutional research group. Even though the project is on site and will involve a local team, there will also be work with researchers abroad. Experience working with team messaging systems and good file management skills are desirable. The student will receive training and guidance on necessary platforms. Along with your application, please include links to data-centered projects that you have worked on, specifying which tasks in the project you did yourself.

Research Project Description:
Research Center/ Lab:	Open Gulf
Faculty Supervisor's Name:	David Wrisley
OpenGulf (opengulf.github.io), a research group working on digital Gulf history is looking for a visiting student researcher. The data for this project includes many handwritten historical archival documents from the Gulf region. The student researcher will work on transcribing some documents from scratch and correcting machine generated transcriptions. The student researcher will be doing research concerning handwritten digitized documents in Arabic, particularly from the Arabian Gulf. The student will learn about new advances in artificial intelligence which allow us to train models to recognize handwriting with precision using the Transkribus platform.
Timeline:
Week 1: Initial review of the data. Identification of documents to work on. Review progress of the project thus far. Research. Week 2: Orientation in research tasks according to the researcher's skill set. Research. Week 3: Transcription, correction. Week 4: Transcription, correction, retraining AI models. Week 5: Initial write-up of results in blog post. correction, retraining AI models. Week 6: Writing. correction, retraining AI models. Weeks 7-8: Writing up results. Documenting work
Responsibilities:
Research to identify documentation Verification of data Documenting work Communicating with project team Transcribing and correcting automated transcription of documents Writing a few blog posts on the process such as these by a previous assistant.
Skills Needed:
Strong Arabic language skills are a must. Ability to type in Arabic (not fast, but with high accuracy). The ability to document one's work, to work both independently and in a team are a must. Experience in web platforms. Interest in artificial intelligence, but no experience required.
Class Level:	Any
Major:	Humanities, social science, history, Middle Eastern studies, global liberal studies, anthropology, geography
Other Requirements:	OpenGulf is a global, multi-institutional research group. Even though the project is on-site and will involve a local team, there will also be work with researchers abroad. Experience working with team messaging systems and good file management skills are desirable. The student will receive training and guidance on necessary platforms. Along with your application, please include links to research projects that you have worked on, specifying which tasks in the project you did yourself.

Research Project Description:
Research Center/ Lab:	French Studies at NYUAD
Faculty Supervisor's Name:	Madeleine Wolf
Artists, writers, photographers, and historians have helped us understand what Paris looked like during the nineteenth-century, as the city was demolished and rebuilt by ambitious city planners, besieged by foreign forces, and destroyed during civil conflicts. But what did this tumultuous period sound like? And what can this tell us about how Parisians perceived major historical and cultural upheavals on both sensory and symbolic levels? In order to respond to these questions, this project aims to transform nineteenth-century French sources into a digital archive and then eventually into an interactive "sound map." From this archive, we will compile and tag references to specific sources of sound as well as references to the locations associated with these sounds. After analyzing trends and identifying particularly noisy spaces of the French capital, we will ultimately transfer the most interesting and pertinent information to a map of Paris, which allows users to click and explore the sounds of nineteenth-century Paris. We will be working on the first phase of this project, focused on compiling data from already digitized sources using databases such as HathiTrust, Gallica, and RetroNews.
Timeline:
June 6 – 17: Introduction to the project; compiling and cleaning data from specific French-language sources (books, novels, poetry, news articles). This will likely be the most difficult and time-consuming part. June 20-24: Tagging references to sound (if there is time, we’ll also tag them based on other common identifiers/descriptions of the sound and the emotions/reactions they elicit) June 27 - July 1: Tagging references to location July 4-8: Identifying trends and most important geo-sonic references, choosing more prominent examples July 11-15: Finalizing key examples and pins; in the first phase, we will pin geo-sonic references to a map of Paris using Google maps or Google Earth July 18-29: Development of a more sophisticated map on Google Earth, ARCGis, or using Advanced Map Block on Squarespace. If time, we will overlay a nineteenth-century map of Paris and include images whenever possible.
Responsibilities:
- Compiling and managing sound-related data from literary, historical, and other works - Cleaning data from digitized French sources - Tagging sonic / location references - Adding pins to maps, using software/sites such as Google Earth, Google Maps, ArcGis, or Squarespace. - Potentially developing a website to host an interactive map
Skills Needed:
Strong proficiencies in French, data analysis, web development. Previous digital humanities experience is ideal. Basic knowledge of history or desire to learn more.
Class Level:	Any
Major:	Any
Other Requirements:

Engineering Summer Positions

Research Project Description:
Research Center/ Lab:	CITIES / Collaborative Intelligence Lab
Faculty Supervisor's Name:	Djellel Difallah Please contact nyuad.cities@nyu.edu with any questions.
This position is connected to CITIES's CityGraph project. The student will work on developing software for knowledge extraction and annotation. Given the time limitation, the scope will be discussed with the student to focus on specific websites or information type: 1) Fact extraction from textual and tabular content, for example, the data extraction can extract facts about public buildings from their websites: ⟨Louvres_Abu_Dhabi, Open_days, Tuesday_to_Sunday⟩, and/or 2) Interactive interfaces for citizens to enter complementary information in the system, for example, by interacting with an AI chatbot, or simply filling out missing properties in the portal.
Timeline:
2 weeks: Onboarding and learning about APIs (particularly ChatGPT) 3 weeks: Writing scripts to extract and transforming data in RDF form 4 weeks: Develop an interface in a Webapp format to collect data injected into our database.
Responsibilities:
- Write python scripts for data scrapping from HTML public APIs. - Code prompts for ChatGPT or similar models for relation extraction. - Develop human input interfaces for data correction or augmentation.
Skills Needed:
Python, web app development
Class Level:	Junior or senior
Major:	Computer science, data science, social science
Other Requirements:

Research Project Description:
Research Center/ Lab:	Laboratory for Computer-Human Intelligence
Faculty Supervisor's Name:	Tuka Waddah Alhanai
Candidate will conduct (one or more of) data processing, train machine learning models, and full-stack web app development applied to real-world data. Focus of their work is a function of their skill set and career ambitions.
Timeline:
Week 1-4: Data collection, aggregation, de-noising Week 4-8: Training ML models, interpreting results, or development of full-stack web app to render data and visuals
Responsibilities:
Candidate is responsible for applying methods and techniques in Computer Science, Computer Engineering, Electrical Engineering to process data and transform it into meaningful insights. Candidate will also be responsible for rendering results and generating reports on their work, as well as targeting a research venues for publication of their work.
Skills Needed:
Python, HTML/CSS, MySQL, Bash
Class Level:	Junior or senior
Major:	Computer Engineering, Computer Science, Electrical Engineering, Interactive Media
Other Requirements:

Research Project Description:
Research Center/ Lab:	Applied Interactive Multimedia
Faculty Supervisor's Name:	Mohamad Eid
We will develop cognitive brain-computer interaction using EEG brain imaging and machine learning. The candidate will work on developing VR simulations, collecting and processing EEG data, and developing machine learning models for classification/regression.
Timeline:
Develop a VR simulation, connect the EEG device to the VR simulation using Unity game engine, develop a machine learning model to process the EEG data in real-time and provide immediate feedback to the VR simulation.
Responsibilities:
Develop VR simulation using Unity game engine. Develop machine learning models to process the EEG data. Participate in a literature review about the topic. Write a technical report about the project.
Skills Needed:
Machine learning, VR development
Class Level:	Any
Major:	Electrical or computer engineering or computer science
Other Requirements:

Research Project Description:
Research Center/ Lab:	Applied Interactive Multimedia Lab
Faculty Supervisor's Name:	Mohamad Eid
This project involves developing origami-inspired haptic interfaces for wearable hand augmentation. We will go through the complete design and evaluation for the interface, including design, simulation, 3D printing and prototyping, characterization, and evaluation with human subjects.
Timeline:
2 weeks: Orientation and familiarization with origami-inspired technologies. 2 weeks: Designing the haptic interface 3 weeks: Prototyping and evaluation 1 week: Wrap up and write up
Responsibilities:
Learn about 3D modeling and printing technologies. Develop code for controlling the haptic interface. Build an experimental setup for characterizing the haptic interface. Conduct a human-subject evaluation for the haptic interface. Documenting code and writing up a report about the task.
Skills Needed:
Basic 3D modeling and printing skills Programming skills (Python or C++)
Class Level:	Junior, Senior
Major:	Electrical or computer engineering or computer science
Other Requirements:

Research Project Description:
Research Center/ Lab:	CITIES
Faculty Supervisor's Name:	Adela Kovarova
The Center for Interacting Urban Networks (CITIES) at NYUAD promotes excellence in urban science research that leads to real improvements in terms of economic opportunity and growth, safety and security, health and wellness, and the overall quality and sustainability of everyday life in urban areas. It is fundamental research that can ultimately be translated into pragmatic ideas for increasing the livability of our cities, with a special emphasis on Abu Dhabi and the UAE. The selected candidate will work in a unique interdisciplinary environment, where faculty from across the four NYUAD divisions (Engineering, Science, Social Sciences, and Arts and Humanities) synergistically work on cutting-edge urban science-related studies. The fine details of the research project will depend on the candidate-specific interests and should focus on the main research areas to which CITIES efforts are targeted, namely the interactions among three of the main layers that compose each city: (i) the physical layer, which includes physical infrastructure, instrumentation, and networks of devices; (ii) the digital layer, which includes data produced by human, devices, and sensors; and (iii) the social layer, which includes humans, their interactions, and the social networks that transpire. We offer multiple research opportunities in the area of cybersecurity where we aim at developing different types of security attacks and defenses in autonomous vehicles in smart cities settings. However, applicants can apply for a broad range of other urban science opportunities including, but not limited to, multimodal mobility systems, traffic flow dynamics, supply chain management, AI (development of AI-based decision support tools), Urban Dynamics (use of social media data to develop methods for monitoring urban activity), Smart Urban Infrastructure (design of innovative building materials). If you have an interest in any of these fields, please explain in your cover letter. The candidate may apply to work with any of the faculty currently affiliated with CITIES, namely Monica Menendez, Azza Abouzied, Saif Jabari, Kinga Makovi, Ali Diabat, Kemal Celik, Christina Poepper, John Burt, Farah Shamout, Muhammad Shafique. Please contact nyuad.cities@nyu.edu with any questions. Tutoring by any faculty at NYUAD is possible, provided that the research project aligns with CITIES main research objectives.
Timeline:
The project could consist of two main phases: data acquisition and data modeling and analysis, possibly followed by writing the results in a scientific paper to be published or in a report.
Responsibilities:
Possible responsibilities may vary according to the specific interests of the candidate, the research project, the faculty supervisor within CITIES, and the research project that is ultimately selected. Responsibilities may include: analyzing data sets and running computer models, data acquisition, contributing to writing a scientific paper, produce a report at the end of the project.
Skills Needed:
Required skills may vary depending on the selected project and may include: computational skills; ability to work with others; excellent writing skills; mathematics, etc.
Class Level:	Sophomore, junior, or senior
Major:	Engineering, science, or social sciences
Other Requirements:

Research Project Description:
Research Center/ Lab:	The Advanced Microfluidics and Microdevices Laboratory
Faculty Supervisor's Name:	Mohammad Qasaimeh
Developing microfluidic assays for innovative biology experimentation and point-of-care diagnostics.
Timeline:
Week 1 - Literature review Week 2 - Lab training Week 3 - Prototyping Week 4 - Modeling Week 5 - Experiments Week 6 - Experiments Weeks 7 and 8 - Report writing
Responsibilities:
Literature review Experiments Report writing
Skills Needed:
Dedication, hard work, teamwork, writing skills, Wet bench lab skills
Class Level:	Sophomore or above
Major:	Engineering, biology, chemistry
Other Requirements:

Research Project Description:
Research Center/ Lab:	Ramadi Lab for Advanced Neuroengineering and Translational Medicine
Faculty Supervisor's Name:	Khalil Ramadi
Conduct research related to Neuroengineering. Our lab uses mechanical, electrical, and chemical techniques to attempt to interface with the brain and peripheral nervous system in a minimally invasive way. These technologies could potentially lead to therapies of neurological, metabolic, and gastrointestinal disorders. Responsibilities will include literature review, preparation, and characterization of nanomaterials, device design and fabrication, presenting data/results in the weekly group meetings.
Timeline:
Week 1-2: Literature Review and training; Week 2-6: Data collection; Week 6-8: Data analysis and final presentation
Responsibilities:
Literature review, experimental set up, data collection, analysis
Skills Needed:
No experience is required. Training will be provided in all areas. Familiarity with CAD, electrical circuits, manufacturing, or chemical synthesis would be beneficial, although not essential.
Class Level:	Sophomore or junior
Major:	Mechanical, electrical, chemical, biomedical engineering
Other Requirements:

Research Project Description:
Research Center/ Lab:	The Vijay Lab
Faculty Supervisor's Name:	Vijayavenkataraman Sanjairaj
3D Printing and Bioprinting is increasingly being considered as an ideal tool for engineered tissues and organs. Students can choose to work on one of the focus areas (i) New bioink isolation and formulation from plant / animal sources (ii) Bioink optimization and bioprinting (iii) Bioprinting of specific tissue structures such as bone, nerve, or skin (iv) Computational studies on various tissue engineering scaffold designs and computational bioprinting.
Timeline:
Timeline and detailed work schedule will be based on the chosen project and the progress. Roughly, the timelines are given below: Week 1 to 2 — Literature Review and basic preparation for the project Week 3 to 7 — Computational or Experimental work Week 8 — Wrapping up and report
Responsibilities:
3D Printing and Bioprinting is increasingly being considered as an ideal tool for engineered tissues and organs. Students can choose to work on one of the focus areas (i) New bioink isolation and formulation from plant / animal sources (ii) Bioink optimization and bioprinting (iii) Bioprinting of specific tissue structures such as bone, nerve, or skin and (iv) Computational studies on various tissue engineering scaffold designs and computational bioprinting.
Skills Needed:
For Bioprinting projects, no prior experience is required. For Computational projects, prefer candidates with a knowledge of 3D modeling software such as AutoCAD and SolidWorks, CFD software such as COMSOL, Abaqus or ANSYS.
Class Level:	Any
Major:	Mechanical, biomedical, chemical, and biomolecular Engineering
Other Requirements:

Research Project Description:
Research Center/ Lab:	eBrain Lab
Faculty Supervisor's Name:	Muhammad Shafique
This project will focus on implementing different machine learning algorithms for advanced driver assistance and their mapping on smart mobile phones.
Timeline:
2 weeks: Getting hands-on with mobile application development, available algorithms at the lab, profiling, benchmarking, etc. 4 weeks: Implementation of different machine learning algorithms for mobile ADAS. 2 weeks: Testing, validation, extensive experimentation
Responsibilities:
Development, implementation, testing, comparison between different approaches.
Skills Needed:
Good programming knowledge preferably in Python, knowledge of basic machine learning algorithms, (preferably) mobile application development.
Class Level:	Sophomore and junior undergraduate students, senior students (who would have just graduated) may be considered.
Major:	Computer engineering, computer science, electrical engineering
Other Requirements:

Research Project Description:
Research Center/ Lab:	eBrain Lab
Faculty Supervisor's Name:	Muhammad Shafique
This project has multiple sub-projects that can be given to different students based on their interests, i.e., whether they would like to do hardware- or software-related work. These sub-projects aim at developing and optimizing bio-signal processing for low-power computing systems: (a) Implementing architecture-aware pruning and quantization on biomedical DNNs to develop precision/recall-aware model compression techniques for embedded GPUs (like Nvidia, Jetson Nano, and Xavier). (b) Implementation of advanced algorithms for time-series analysis for ECG/EEG for short-term and long-term predictions, and their deployment on embedded GPUs. (c) Implementing and evaluating deep learning / autoencoder models for reconstructing bio-signals; in this work, we investigate the compressed sensing tolerance of bio-signals and investigate novel DL architectures and autoencoders, which can be used to reconstruct the original signal with maximum possible accuracy. (d) Implementation of state-of-the-art deep learning models for classification of COVID-19 from real-world biomedical image datasets like X-rays.
Timeline:
2 weeks: Getting hands-on the programming, development framework, hardware platform. 4 weeks: Implementation of the targeted research problem, as detailed in the topic description. 2 weeks: Testing, validation, extensive experimentation
Responsibilities:
Development, implementation, testing, comparison between different approaches
Skills Needed:
Good programming knowledge in Python, knowledge of basic machine learning algorithms, (preferably) ML development frameworks like Pytorch and GPU programming, otherwise will be learned quickly in the first two weeks.
Class Level:	Sophomore and junior undergraduate students, first-year and senior students (who would have just graduated) may be considered.
Major:	Computer engineering, computer science, electrical engineering
Other Requirements:

Research Project Description:
Research Center/ Lab:	eBrain Lab
Faculty Supervisor's Name:	Muhammad Shafique
This project has multiple sub-projects that can be given to different students based on their interests, i.e., whether they would like to do hardware- or software-related work. These sub-projects aim at optimizing ML algorithms for embedded platforms deployed in autonomous systems like UAVs and autonomous vehicles under energy-constrained scenarios: (a) Implementing tinyML benchmark applications (like tinyMlPerf) on Embedded GPUs like Jetson Nano, implementing different optimization techniques for performance/energy optimization, profiling, and benchmarking. (b) Developing a hardware-aware neural architecture search framework (based on existing open-source implementations) under constraints for autonomous mobile robots (like Rovers and UAVs), and their deployment on embedded GPUs. (c) Developing embedded Lifelong Learning algorithms for autonomous mobile robots (like Rovers and UAVs) considering limited energy budgets.
Timeline:
2 weeks: Getting hands-on the programming, development framework, hardware platform. 4 weeks: Implementation of the targeted research problem, as detailed in the topic description. 2 weeks: Testing, validation, extensive experimentation
Responsibilities:
Development, implementation, testing, comparison between different approaches
Skills Needed:
Good programming knowledge in Python, knowledge of basic machine learning algorithms, (preferably) ML development frameworks like Pytorch and GPU programming, otherwise will be learned quickly in the first two weeks.
Class Level:	Sophomore and junior undergraduate students, first year and senior students (who would have just graduated) may be considered.
Major:	Computer engineering, computer science, electrical engineering
Other Requirements:

Research Project Description:
Research Center/ Lab:	CITIES
Faculty Supervisor's Name:	Muhammad Shafique Please contact nyuad.cities@nyu.edu with any questions.
This project has multiple sub-projects that can be given to different students, if multiple candidates apply, and based on their interests, i.e., whether they would like to do do hardware- or software-related work. These sub-projects aim at developing different types of security attacks and defenses in autonomous vehicles in the smart cities settings. Topic (a) Implementing backdoor attacks for autonomous vehicles and evaluate them in the CARLA full-system simulator demonstrating a smart mobility use case, where a complete environmental model is available. Topic (b) Implementing defenses for backdoors for autonomous vehicles and evaluating them in the CARLA full-system simulator demonstrating a smart mobility use case, where a complete environmental model is available. The work would analyze the pros and cons of existing defense mechanisms, their robustness in full-system setting, and potentially devise a more powerful defense considering the ADAS stack. Topic (c) Robustness of Traffic Sign Recognition Framework against Adversarial Attacks: Most of the state-of-the-art adversarial attacks do not consider the complete pipeline of ML-based systems. For example, in the traffic sign recognition system, the impact of traffic sign detection is ignored in most of the research works. Therefore, in this project, we plan to evaluate the robustness of the traffic sign recognition system while considering the complete pipeline, including traffic sign detection and all preprocessing stages. To evaluate the robustness against different environmental conditions, we plan to implement and analyze this whole pipeline in CARLA simulator.
Timeline:
2 weeks: Getting hands-on the programming, CARLA framework. 4 weeks: Implementation of the targeted research problem, as detailed in the topic description. 2 weeks: Testing, validation, extensive experimentation.
Responsibilities:
Development, implementation, testing, comparison between different approaches
Skills Needed:
Good programming knowledge in Python, knowledge of basic machine learning algorithms, (preferably) ML development frameworks like Pytorch otherwise will be learnt quickly in the first two weeks.
Class Level:	Sophomore and junior undergraduate students, first-year and for UAE-based students, senior class.
Major:	Computer engineering, computer science, electrical engineering
Other Requirements:

Research Project Description:
Research Center/ Lab:	Micro- and Nanoscale Bioengineering Lab
Faculty Supervisor's Name:	Rafael Song
Marine iguanas living on Galapagos Islands are known for their very efficient salt glands, where they “sneeze” out salt. Because they feed underwater, they take in a large amount of saltwater. In order to prevent dehydration, they must expel salt without expelling water, so they have specialized glands that remove salt from their blood. Bioinspired by this ability, the project aims to build an "artificial salt gland" in a microfluidic chip that can expel salt ions from sea water and demonstrate the capability of marine iguanas' salt sneezing on chip.
Timeline:
June 1-14: Design and fabrication of the salt extraction chip June 15-30: Testing of the prototype for salt removal July 1-15: Building a millimeter-scale artificial salt gland July 16-29: Testing on sea water with quantification of salt removal rate
Responsibilities:
Design and build microfluidic chips and testing with various salt water samples in the lab. Characterization of the extracted salt ions in terms of flow rate and power consumption.
Skills Needed:
Mechanical Design with 3D software tools such as Solidworks or Autocad
Class Level:	Any
Major:	Mechanical, chemical, electrical engineering
Other Requirements:

Science Summer Positions

Research Project Description:
Research Center/ Lab:	Center for Astrophysics and Space Science
Faculty Supervisor's Name:	Dimitra Atri
We invite students to work in our research group on Mars, Moon, and Asteroids. The group is interested in the atmosphere of Mars, its surface and subsurface chemistry, and exploring its present and past habitability. We are also preparing to do science with the UAE’s Asteroid and Lunar missions. The main research areas are: 1. Mars atmosphere: Investigating how space weather impacts the Martian atmosphere. Using a combination of numerical modeling and data from space missions, the goal is to understand space weather-induced changes in atmospheric chemistry and escape rates. Data from the UAE’s Hope mission will be used to complement ongoing research with NASA’s MAVEN and Curiosity missions. AI-based techniques for data analysis are being developed from multiple missions to take advantage of large datasets and obtain a comprehensive picture of the planet. 2. Martian surface and subsurface: an experimental facility to simulate Martian conditions and study the chemistry of the planet based on data from Mars rovers is being established. The Martian subsurface environment will be simulated, the target of ESA/Roscosmos’s ExoMars 2022 mission. The goal is to investigate the present and past habitability of the planet. 3. Crewed missions to Moon and Mars: All major spacefaring nations, including the UAE (Mars 2117) are seriously thinking about crewed missions to the Moon and Mars in future. The group is investigating the impact of radiation on astronaut health using a combination of numerical modeling and medical data. The group will also work toward developing sustainable exploration strategies for such missions. 4. Mars and Moon-analog environments: The goal is to gain insights into potential life on Mars by studying Mars-like environments on Earth by (1) exploring Mars-analog sites, and (2) studying the microbial response in Mars simulation chambers in the laboratory. The group will investigate the effect of multiple extreme conditions of salinity, temperature, desiccation, and irradiation on microbial communities in the Arabian Gulf. Similar studies are also being planned for Lunar exploration.
Timeline:
Depending on the skill level and interest, students will be given a computational assignment, literature review, or asked to work on a research problem.
Responsibilities:
Assist the scientists of the research group in performing research by either of the following (1) data analysis, (2) simulations, (3) literature review, (4) write a research paper.
Skills Needed:
Our projects are interdisciplinary and students from various backgrounds can apply, which include physics, computer science, engineering, biology, chemistry, and political science (other disciplines are welcome too).
Class Level:	Any
Major:	Any

Research Project Description:
Research Center/ Lab:	Sadler Edepli Lab
Faculty Supervisor's Name:	Kirsten Edepli
The genes underlying zebrafish development can be manipulated using genetic approaches that include generating mutations and transgenics. This project will systematically characterize genetic tools used for studying zebrafish liver development and then apply these tools to understand the response of the liver to the overexpression of cancer genes.
Timeline:
Week 1-2: Project overview, literature research, animal use training, environmental health and safety Week 3-5: Training in zebrafish embryo manipulation, microscopy, and data gathering Week 6-8: Project development and data analysis; project presentation
Responsibilities:
The student will be responsible for carrying out experiments with zebrafish using microscopy and molecular biology techniques. Student is responsible for maintaining a regular schedule, regular communication about progress and data, adhering to all lab and institutional guidelines, and maintaining detailed notes about all experiments. In addition, participating in general lab maintenance, attending lab meetings, carrying out data analysis, and presenting data at lab meetings is expected. All environmental health and safety, animal husbandry and care and laboratory safety training will be carried out prior to starting with experiments.
Skills Needed:
Courses in molecular biology, cell biology, genetics or the equivalents, strong work ethic.
Class Level:	Any
Major:	Any
Additional Requirements:	Must be able to work at least 20 hours a week for at least five weeks.

Research Project Description:
Research Center/ Lab:	Equbal Research Lab
Faculty Supervisor's Name:	Asif Equbal
We are excited to offer a unique summer internship opportunity at the cutting edge of quantum computing and machine learning. This project is centered around the exploration of quantum machine learning, with a special focus on density matrix evolution under spin Hamiltonians.
Timeline:
Week 1: Revisit quantum mechanics and computing. Week 2: Generate data for Quantum Machine Learning. Week 3-6: Machine learning techniques application. Week 7-8: Manuscript writing
Responsibilities:
1. Scripting Numerical Calculations: The intern will be instrumental in scripting sophisticated numerical calculations, a vital component for data collection on high-performance quantum computing platforms. 2. Exploring Machine Learning Techniques: Delving into the state-of-the-art in machine learning, the intern will have the opportunity to explore and apply advanced machine learning techniques. These skills will be directly applied to the development of models for quantum state tomography and quantum process tomography, crucial for understanding quantum systems.
Skills Needed:
Basics of quantum mechanics and computer programming skills
Class Level:	Any
Major:	Physics, mathematics, or computer science

Research Project Description:
Research Center/ Lab:	Equbal Research Lab
Faculty Supervisor's Name:	Asif Equbal
Quantum information science and technology is expected to revolutionize the world. It exploits the unique quantum mechanical properties of a system, such as superposition and entanglement, to develop highly efficient methods of computation, secure communications or encryption, and sensing. There is a growing interest in quantum technology to overcome the classical limitations of current technology. The main theme of this project is to perform an in-silico design and understand the physical and spin properties of a molecular system in order to explore properties favorable to quantum technology, especially the coherence time. Molecular systems offer structural modularity with the possibility of fine-tuning at the atomic level. Since a molecular quantum system involves a large number of parameters (multidimensional landscape), the project will use data science and machine learning for this complex optimization problem. NYUAD has very advanced resources to perform these calculations. In addition, the Center for Quantum and Topological Systems at NYU Abu Dhabi is equipped with a 2-qubit NMR-based quantum computer (Gemini). The Gemini system is an excellent tool for understanding the fundamentals of quantum computing and basic quantum mechanical-based research.
Timeline:
Week 1: Review of the concepts of quantum mechanics. Week 2: Numerically solve the Schrodinger equations for spins in an external magnetic field. Week 3: Understand Coherence and Decoherence. Week 4-7: Numerically simulate an open quantum system and optimize the molecular systems with long coherence time. Week 7-8: Prepare a manuscript.
Responsibilities:
1. Perform quantum mechanical computation of open systems, primarily using MatLab/Python. 2. Learn and explore the Gemini 2-qubit Quantum Computer. 3. Experimentally measure the coherence time of multiple systems. 4. Prepare manuscript
Skills Needed:
Basics of quantum mechanics and computer programming skills
Class Level:	Any
Major:	Physics, physical chemistry, computer science, mathematics

Research Project Description:
Research Center/ Lab:	Equbal Research Lab
Faculty Supervisor's Name:	Asif Equbal
Electrons are ubiquitous, present in every atom. Electrons have two important properties: charge and spin. The charge and spin of electrons are indicators of the local chemical environment of a physical system, and the spin provides more precise information. The spin of electrons, when placed in an external magnetic field, begins to precess (dance) around the magnetic field. The frequency of this dance is unique and is a signature of the local chemical environment. This technique is called electron spin resonance (ESR). It has been used to It has been used to obtain information on complex functional materials and biological processes. The objective of this project is to advance the capabilities of electron spin resonance and to study the local chemical environment of an aggregated or clustered system. These clustered electron spins are common in nature but their study is difficult using conventional ESR. In this project, we will choreograph the dance of clustered electron spins using a “sequence of microwave irradiation,” which will serve as a unique signature. The ultimate aim to transfer quantum information of electrons to nucleus using coherent microwave irradiation.
Timeline:
Week 1: Understand the basics of electron spins using quantum mechanics. Week 2: Learn experiments to detect electrons. Week 3-6: Perform choreography experiments to understand dynamics of multi-coupled electron spins under microwave irradiation. Week 7-8: Prepare a manuscript.
Responsibilities:
1. Perform computation of electron spin dynamics 2. Perform experiments 3. Write a manuscript in a publishable format.
Skills Needed:
Physics, physical chemistry
Class Level:	Any
Major:	Physics, chemistry

Research Project Description:
Research Center/ Lab:	Physics
Faculty Supervisor's Name:	Azam Gholami
C. reinhardtii is a single-celled green algae of about 10 μm in diameter that swim by the beat of its two flagella at frequency of 60 Hz. It has a photo-sensitive eye-spot that breaks cell bilateral symmetry, distinguishing the cis flagellum (closer to the eye-spot) from the trans flagellum. C. reinhardtii is widely distributed worldwide in soil and fresh water and is used as an exceptionally useful organism in physics and biology for studying signaling, cell motility, and the cytoskeleton. The swimming motion of C. reinhardtii is similar to a human breast-stroke but at a frequency of 60 Hz and consists of two steps: first, the two flagella in a nearly straight configuration move back, and consecutively, they bend and push forward to pull the cell body through the surrounding fluid at speeds of 100 μm/sec. The beating pattern of flagella shows curvature waves that propagate from the basal end towards the distal tip and has a small out-of-plane component that causes the cell to rotate around the swimming axis with a frequency of 2 Hz. Two flagella can beat in synchrony or out of synchrony. A cell with two synchronously beating flagella swims in a straight path whereas any desynchronization causes the cell to show a run-and-tumble-like behavior. Our aim is to build a ciliary carpet experimentally and to investigate its collective beating patterns which give rise to a directional fluid transport. To achieve this goal, we will use isolated and demembranated axonemes from Chlamydomonas to build an active ciliary carpet. It was shown theoretically that MCWs are stable if their wavelength exceeds a critical threshold given by four times the inter-ciliary distance. It is believed that hydrodynamic interactions between cilia are the main mechanism of MCWs formation. Neighboring axonemes interact via their induced velocity fields. Depending on the local flow field in the vicinity of axonemes, they react to the hydrodynamic forces by modifying the duration of power and recovery strokes. We will focus on studying the collective dynamics of ciliary carpets and will systematically explore different synchronization mechanisms.
Timeline:
[1] Cilia isolation and demembrantion (0-1 months) [2] Establishing efficient protocols for surface patterning; Optimizing cilia-substrate attachment protocols (0-2 months).
Responsibilities:
The student needs to take care of the cell culture, flagella isolation, surface patterning, and optimizing the cilia-substrate attachment protocols.
Skills Needed:
Microfluidics, cell culture, data analysis, microscopy
Class Level:	Junior or senior
Major:	Physics, biology, bioengineering
Other Requirements:

Research Project Description:
Research Center/ Lab:	Kirmizialtin Lab
Faculty Supervisor's Name:	Serdal Kirmizialtin
RNA is one of the essential molecules of life. The structure and interactions of RNA molecules have implications in medicine and understanding of biological processes. The project aims to model structure and dynamics of RNA molecules using molecular dynamics simulations.
Timeline:
Weeks 1-2: Learn the basics of Molecular dynamics simulation. Weeks 2-6: Write codes to distribute MD simulation data to HPC clusters. Weeks 4-6: Analyze the big data. Weeks 4-6: Write technical reports.
Responsibilities:
Execute and analyze MD simulation data. Write reports. Attend group meetings.
Skills Needed:
Basic level of background in biomedical or chemical engineering or chemistry.
Class Level:	Junior or senior
Major:	Chemistry, biology, physics, chemical engineering
Other Requirements:

Research Project Description:
Research Center/ Lab:	Smart Materials Lab
Faculty Supervisor's Name:	Panče Naumov
This internship provides training in the basic analytical techniques for characterization of oil and gas, specifically related to components that cause fouling in the oil extraction and processing plants. The student will work closely with the members of the Smart Materials Lab (SML) and the Center for Smart Engineering Materials (CSEM) to develop materials for sensors that could be used for detection and prevention of scaling in the UAE’s oil extraction facilities. The student will learn and operate specific experimental setups that provide analysis of oil under simulated environments close to those encountered in real conditions.
Timeline:

Responsibilities:
Application of standard chemical techniques for the preparation of oil fraction analysis using different analytical methods, acquiring and processing of analytical data, and presenting the results orally and in writing.
Skills Needed:
Knowledge of basic organic and analytical chemistry, experience with working in an undergraduate chemical laboratory or engineering laboratory, ability for teamwork, and motivation to acquire practical skills in oil-related research.
Class Level:	Any
Major:	Science or engineering majors
Other Requirements:

Research Project Description:
Research Center/ Lab:	Smart Materials Lab
Faculty Supervisor's Name:	Pance Naumov
Smart dynamic materials constitute an emerging class of materials that are capable of controllable responses to external stimuli such as force, light or heat. By tactful modification of the assembling components and molecular manipulation techniques, in the Smart Materials Lab (SML) we are exploring a broad range of materials such as crystals or polymers that exhibit multiple responses so as to realize multidirectional control over their shape, position and motility. Such soft actuators are useful for controlling energy conversion from light or heat to mechanical work that could be further conveniently transferred to electricity or motion. In this project, the student will work closely with the members of the SML and the Center for Smart Engineering Materials (CSEM) to prepare, analyze and assess the performance of new and exciting smart materials for applications in optics, flexible electronics, and soft robotics.
Timeline:
Timeline to be determined.
Responsibilities:
The student will work with a member of the SML to synthesize organic materials, make a device, and characterize the performance of the device. The student will be trained on a range of synthetic, analytical and engineering techniques.
Skills Needed:
Basic chemistry-theoretical knowledge, Sample experimental operation, and excellent writing ability in English.
Class Level:	Sophomore or above
Major:	Chemistry, physics, mechanical engineering

Research Project Description:
Research Center/ Lab:	Center for Quantum and Topological Systems
Faculty Supervisor's Name:	Hisham Sati
There has been a lot exciting research on quantum computing, both at the hardware and the software levels, with the latter leading to various quantum computing languages. One drawback to these is the fact that the hardware part of the development is still lagging behind, leading to the need and prominence for quantum simulators. It would hence be interesting and desirable to come up with an approach to quantum computing languages that simulate quantum processes not on a pertinent quantum computer but on a classical one. At the same time, it would be important for such an approach to be fundamental and aware of the quantum material underlying the expected hardware, leading to languages that are implementable and realistic. A promising such approach is through topological quantum computing, which is robust against nose, errors, and perturbations, leading to reliable and scalable hardware, and hence practically useful and implementable software. The development of this approach is at the heart of the research at the Center for Quantum and Topological Systems (CQTS).
Timeline:
Approaches to the foundations of quantum computing languages.
Responsibilities:
Project approach to quantum computing languages in collaboration and coordination with mentors and other students. Implementing and simulating topological quantum gates, verification and certification of the simulations, building a reliable software library, and then combining ingredients from such a library to construct simulations of the desirable quantum programs. Participation in the activities of the center, including workshops, training sessions, seminars, conferences, hackathons, meetings, and interaction with visitors.
Skills Needed:
This opportunity is open to students from computer science, computer and electrical engineering, mathematics, and physics
Class Level:	Any
Major:	Varies, including computer science, computer and electrical engineering, mathematics, and physics

Research Project Description:
Research Center/ Lab:	Teaching, Learning, and Development Lab
Faculty Supervisor's Name:	Antje von Suchodoletz
In this project, we want to give a voice to first-time Emirati fathers to learn more about their attitudes and beliefs regarding parental and family roles as they transition into parenthood. Using a mixed-method approach, that is combining open-ended interview questions with survey questions, physiological measures, and observations, we hope to contribute to a better understanding of how Arab-Muslim fathers construct their identity as fathers, how they balance traditional and modern values around child rearing and family roles, and how they develop parenting competencies. Participants will be recruited during the last trimester of the wife’s pregnancy when the first interview and survey data will be collected. The second data collection is planned around three months after childbirth to explore potential changes in fathers’ attitudes and beliefs regarding parental and family roles. At that time, the families will be invited to the Play Lab at NYU Abu Dhabi where fathers will complete another interview and also be observed interacting with the baby when we collect physiological data. Fathers and mothers will also be asked to complete a second survey. Together, we hope this rich data will help inform policies related to paternal, familial, and child well-being, such as paternity and parental leaves and the inclusion of fathers in health services and educational settings. It might also inform the development of resources and initiatives specifically targeting Emirati fathers of young children, such as programs that support new fathers’ mental health, with the ultimate goal to optimize children’s development.
Timeline:
Week 1: Introduction to the research project and the available data (interview data from pre-birth and 3- months data collection; video recording of father- infant interaction from 3-months data collection; physiological data from 3-months data collection); Intensive training in the coding procedures (behavioral coding, interview coding, physiological data cleaning) and the software required for each set of data; Intensive training in the data collection procedure (subject to ongoing data collections). Week 2: Accomplish reliability in the coding and data collection procedures to ensure the quality of the data Remaining weeks: Support the ongoing project activities with regard to coding and data collection (with supervision of the project’s research assistants). Week 3-8: Transcription and coding of interview data using MAXQDA; the coding prepare data (survey data) for analyses. Week 6-8: Get practice in basic (descriptive) analysis of the data; become involved in dissemination of findings (research brief for website).
Responsibilities:
Responsibilities include active involvement in all stages of the data processing, in particular: coding of interview, video, and physiological data following standardized procedures and manuals; prepare data for analyses; participate in data collection.
Skills Needed:
Strong interpersonal and communication skills. The ability to handle tasks requiring high levels of attention to detail, to carry complex research tasks to completion, and to efficiently manage work in the time required.
Class Level:	Any
Major:	Psychology; social science; education; human development; or related field
Other Requirements:	Fluent in English and Arabic (ideally Emirati dialect) Basic knowledge in research methods in psychological/social science research would be beneficial but not required.

Research Project Description:
Research Center/ Lab:	Teaching, Learning, and Development Lab
Faculty Supervisor's Name:	Antje von Suchodoletz
There is no doubt that technology plays a crucial role in children’s and adults’ lives, one that is likely to increase even more in the next generation(s) with today’s children being younger when they enter the digital space than previous generations. The 2018 Norton’s My First Device Report, an online survey with parents across ten countries, including the UAE, showed that about 68 percent of 5-10-year-old children and 69 percent of 11-15-year-old children owned a tablet in the UAE. The average age of children to own their first tablet was 7 years in the UAE, compared to the average age of 9 years across all 10 countries. Despite these numbers, and despite concerns about the negative impact of excessive screen time on children’s development and well-being, especially in the early years (e.g., Canadian Pediatric Society, 2017; Stoilova et al., 2021), little research has been done on technology use and habits among young children and their parents and caregivers. This is the case in many countries, and also in the UAE. The scientific and public discourse often focuses on questions related to screen time – how much time should children be allowed to spend on digital devices, such as tablets or smartphones (e.g., Carson et al., 2016)? However, when determining the effects of digital technology on children, it is important to consider more than just the amount of screen time and also take into account what children are actually doing with these devices. What apps are available to support children’s cognitive development and learning, and what is their quality? And, finally, how can policymakers, school officials, and parents be guided in the selection of high-quality apps, and how can developers be guided in designing appropriate new digital interventions? To address these questions, the research aims to (1) describe the current state of young children’s digital technology use, with a specific focus on the UAE, (2) develop a framework for evaluating the quality and developmental appropriateness of different digital media for young children, prioritizing quality over quantity of app use, and (3) create a rating system for digital interventions for early childhood that is theory-based and evidence-driven.
Timeline:
Week 1-2: Introduction to the research project; training in systematic academic literature (in scientific databases and the grey literature); training in descriptive statistic analyses; accomplish reliability in the procedures to ensure the quality of the data. Week 3-8: Support the ongoing project activities with regard to the systematic academic literature review and the development of survey/interview items to measure caregivers' beliefs regarding the use of technology; prepare the data for analyses (caregiver survey; pilot data); get practice in basic (descriptive) analysis of the data; prepare tables and graphs for dissemination of caregiver survey results
Responsibilities:
Responsibilities include active involvement in all stages of the systematic literature review; participate in item development for caregiver survey and interview; prepare data for analyses; participate in basic descriptive analyses and visualization of findings.
Skills Needed:
Strong interpersonal and communication skills; The ability to handle tasks requiring high levels of attention to detail, to carry complex research tasks to completion, and to efficiently manage work in the time required.
Class Level:	Any
Major:	Psychology; social science; education; human development; or related field
Other Requirements:	Fluent in English and Arabic (ideally Emirati dialect) Basic knowledge in research methods in psychological/social science research would be beneficial but not required.

Social Science Summer Positions

Research Project Description:
Research Center/ Lab:	Public Health Research Center
Faculty Supervisor's Name:	Amar Ahmad
The UAE Healthy Future Study (UAEHFS) is one of the first large prospective cohort studies in the region examining causes and risk factors for chronic diseases in adult UAE nationals. Missing values are often unavoidable in empirical research and can lead to distortions in many cases. In addition, "I don't know" and "I'd rather not answer" responses are common in public health research. However, statistical approaches to dealing with “don't know” and “I'd rather not” responses can affect the validity of the survey and the researchers' ability to interpret the results. Five common statistical machine-learning methods of handling missing values will be included in this analysis. These are mode imputation, k-nearest neighbor (KNN) imputation, classification, and regression trees (CART), random forest (RF) imputations, and random samples from observed values (Sample). The outcome of this study aims to shed light on the development of missing data procedural knowledge and provide methodological support for public health decision-making when data with missing values are collected. Furthermore, the aim of this study is to prevent the exclusion of missing data rather than to generate data.
Timeline:
Timeline of tasks to be determined.
Responsibilities:
Several statistical machine-learning approaches will be used to address the impact of missing data on clinical decision-making. -You will use empirical data from a previous study on depression symptoms in patients with coronary heart disease. -You will study the effect of the complete case analysis (i.e. when missing data are omitted) and multiple imputation on parameter estimates and confidence intervals using machine learning approach, e.g., k-nearest neighbors (KNN) random forest, and support vector machine (SVM) as well as logistic regression. -You will use several statistical packages such as randomForest and Kernlab. -As we are using multiple approaches in this study, the method of false discovery rate (FDR) will be used to adjust for multiple testing. -You will be used the R software on both Windows and Linux as appropriate. -You will use the Area Under the Receiver operating characteristic (ROC) curve (AUC) and the Kappa score to assess the imputation effects of missing values data proceeding approach.
Skills Needed:
This research assistantship is aimed at students who are familiar with a statistical programming language (ideally R) and have background in linear algebra (vectors and matrices: transpose, inverse and determinants quadratic forms) as well as probability theory (discrete and continuous univariate random variables, expectation, variance, and normal distribution).
Class Level:	Junior or senior
Major:	Mathematics
Other Requirements:	Missing Values, Data Mining, Statistical Programming, Statistical Machine Learning Methods, Statistical Modeling. You would like to constantly develop yourself, learn, and apply new statistical methods.

Research Project Description:
Research Center/ Lab:	Public Health Research Center
Faculty Supervisor's Name:	Amar Ahmad
This summer assistantship project aims to provide students with a hands-on, immersive experience in statistical machine learning. The project will delve into the development and application of advanced statistical models that are foundational to machine learning. Students will have the opportunity to work alongside experienced researchers and data scientists to explore innovative solutions to data-driven problems.
Timeline:
Week 1-2: Orientation to categorical data and dimensionality reduction. Literature review on PCA, MCA, UMAP, and related techniques. Week 3: Practical sessions on PCA, MCA, and UMAP implementation and data preprocessing. Week 4-5: Hands-on project execution, applying methods to selected datasets, and beginning comparative analyses. Week 6: Data visualization and interpretation. Development of the dashboard (if applicable). Week 7-8: Final analysis, report writing, and preparation for presentation.
Responsibilities:
Objectives: 1) To cultivate a deep understanding of statistical learning theory. 2) To develop practical skills in implementing statistical machine learning models. 3) To enhance proficiency in programming and data analysis with tools like R, and relevant ML libraries. 4) To engage in collaborative research and contribute to ongoing projects. 5) To create a comprehensive report or portfolio that demonstrates the student's project work. Potential Project Ideas Unsupervised Learning and Clustering Techniques: 1) Utilize unsupervised algorithms to discover patterns in unlabeled data. 2) Perform customer segmentation, gene expression grouping, or market basket analysis. Dimensionality Reduction for Data Visualization: 1) Apply techniques like principal component analysis (PCA), Multiple Correspondence Analysis (MCA), or Uniform Manifold Approximation and Projection (UMAP) on high-dimensional data. 2) Visualize and interpret the reduced feature space for insights. Expected Outcomes: 1) A set of Jupyter Notebooks or R Markdown files documenting the code, experimentation, and analysis. 2) A final report or presentation summarizing the project approach, challenges encountered, and insights gained. 3) Contributions to a public code repository (e.g., GitHub) for portfolio display and open-source collaboration.
Skills Needed:
This research assistantship should have a background in statistics, mathematics, or computer science. Prior experience with programming (R preferred) and an interest in machine learning. Ability to work both independently and collaboratively in a research environment.
Class Level:	Junior, senior
Major:	Statistics, data science, computer science, economics, engineering, quantitative social sciences, psychology, and humanities
Other Requirements:	To explain technical concepts to a non-technical audience is a plus. Strong written and oral communication skills, as the project will involve report writing and presentations. Ability to explain technical concepts to a non-technical audience is a plus. Ability to work effectively in a team, as the project may involve collaborative work with peers, mentors, and possibly external partner

Research Project Description:
Research Center/ Lab:	Economics Program
Faculty Supervisor's Name:	Jordan J. Norris
Assist with economics academic research. The topic of research is broadly in spatial economics, where we try to understand the role of space in economic outcomes. Topics include: - Spatial inequality: how and why does economic prosperity vary across cities, regions, and countries? - Spatial interdependence: how locations are interconnected by networks (e.g., supply chains, social networks) and what are the economic consequences of these (e.g., on economic growth, macroeconomic policies) - Spatial policy: what is the best policy to influence economic outcomes, taking the above into account (e.g., promoting economic mobility; ensuring self-sustaining rather than transitory impacts)
Timeline:
The assistant will be required to create reports of the tasks completed, with deliverables being every one-two weeks. These include constructed/cleaned datasets, tables/graphs, code, and descriptions/summaries of what has been done.
Responsibilities:
1. Data collection and cleaning. Collecting the data from the relevant sources (these will all be available online, either in public or academic databases), and cleaning the data. 2. Regression analysis. The specification (e.g., OLS, panel) will be given. Expect the assistant to take initiative in exploring the results and in investigating robustness. 3. Quantitative analysis. Potentially apply economic models, for example using Monte Carlo simulations. 4. Documentation. Provide well-commented and well-organized code, write up results in reports, and create tables and figures communicating the findings. These must be sufficiently clear such that research can continue from where the assistant left off, if necessary. 5. Literature review. Review prior work to help inform directions we will take in the project. Throughout, the assistant will be in direct contact with the faculty supervisor. They will be provided with instructions for the tasks, guidance on how to complete, and regular feedback. Outside of this, they will be expected to work mostly independently, and be able to apply their own problem-solving ability to make progress on the tasks.
Skills Needed:
Stata, Econometrics
Class Level:	Junior
Major:	Economics
Other Requirements:	Good communication skills; writing/presentational skills

Research Project Description:
Research Center/ Lab:	Social Sciences Research Fellowship
Faculty Supervisor's Name:	Milena Tekeste
The workplace flexibility discourse emerged in the 1970s, and since the 1990s, in particular, it has received increasing attention in the fields of organizational psychology, sociology, and careers. The evolvement of the flexible work discourse amongst a spectrum of research specialisms has caused scholars to apply numerous terms to refer to workplace flexibility, for example, organizational flexibility, flexible work arrangements, and flexibility HRM. Irrespective of the terminology used, the phenomenon scholars seek to further understand, study and reveal how employer-driven flexibility or employee-driven flexibility enhances the working life of individuals, organizations, or society as a whole. In January 2022, the UAE government introduced a new workweek for the public sector from Sunday to Thursday to Monday to midday on Friday for nearly all Emirates. This change is believed to encourage flexible hours and remote working. Within this study, we want to explore the extent to which the change in the UAE work week has impacted the working lives/ work-life interface of women. In addition, we seek to understand the extent to which this change has promoted or hindered labor market participation and women’s careers.
Timeline:
The project could consist of two main phases: data acquisition and data analysis, followed by writing the results in a scientific paper to be published or in a report.
Responsibilities:
Assist the research lead in performing research by either of the following 1) literature review 2) data collection 3) data analysis 4) writing a research paper The fellow is also required to participate in weekly team meetings and, depending on the level and skills, complete some training.
Skills Needed:
- Strong interest in Organizational Behavior and Employment Relations - For students interested in writing tasks: Strong research skills, the ability for academic writing and referencing. - For students interested in data management tasks: knowledge of NVivo - Strong time management skills, attention to detail, well organized and interpersonal and communication skills
Class Level:	Any
Major:	Any, but preferably Business, Organizations and Society
Other Requirements:

The Visiting Undergraduate Research Program is a win-win situation for students and faculty. The program has allowed undergraduate students to get immersed in the world of research and bring a fresh viewpoint and approach to ongoing research being conducted. The diversity and different academic backgrounds of the students spark creativity and innovation into the research projects they work on.

Borja Garcia de Soto, Assistant Professor of Civil and Urban Engineering; Director, S.M.A.R.T. Construction Research Group

Featured Research

Muhammad Haider creates a supersaturated solution of ROY, one of the most polymorphic compounds known today.

My research project focused on two compounds known as ROY and HCB. ROY is one of the most polymorphic compounds known today, meaning it can crystallize in several different forms such as prisms and needles. What is especially interesting about ROY is that seven of its known polymorphs are all stable at room temperature and standard pressure.

- Muhammad Haider, NYU New York

NYU Abu Dhabi Undergraduate Research Report 2020-2021 (PDF)

Social and Cultural Events

Visiting undergraduate research students can usually expect an energetic social calendar during their time here. This includes a welcome lunch, campus activities, and visits to key UAE cultural and social hotspots such as the Sheikh Mohammed Centre For Cultural Understanding in Dubai (below).

Visiting undergraduate students visited the Sheikh Mohammed Centre For Cultural Understanding in Dubai.

Contact Us

NYUAD Office of Undergraduate Research
Email: nyuad.undergraduateresearch@nyu.edu

NYUAD is a member of the international Council on Undergraduate Research.

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