Preview - Visiting Student Summer Undergraduate Research Program

Summer 2023 Available Positions

• 3D Printing and Bioprinting: Vijayavenkataraman Sanjairaj, the Vijay Lab

  Research Center/ Lab:	The Vijay Lab
  Faculty Supervisor's Name:	Vijayavenkataraman Sanjairaj
  Research Project Description:
  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.
  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:
• Advanced Sensing and Analysis Systems for Petroleomics (Oil and Gas) Applications: Panče Naumov, Smart Materials Lab

  Research Center/ Lab:	Smart Materials Lab
  Faculty Supervisor's Name:	Panče Naumov
  Research Project Description:
  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:
• Applied Machine Learning + Full-Stack App Dev: Tuka Alhanai, Laboratory for Computer-Human Intelligence

  Research Center/ Lab:	Laboratory for Computer-Human Intelligence
  Faculty Supervisor's Name:	Tuka Waddah Alhanai
  Research Project Description:
  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. Students are expected to be on-campus to take part in this position. In the event that public health guidelines prevent in-person work or international travel, please confirm if this position can take place remotely.
  Timeline:
  Week 1-4: Data collection, aggregation, de-noising Weeks 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:
• Approaches to the Foundations of Quantum Computing Languages: Hisham Sati, Center for Quantum and Topological Systems

  Research Center/ Lab:	Center for Quantum and Topological Systems
  Faculty Supervisor's Name:	Hisham Sati
  Research Project Description:
  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
• A Biomimetic Design of Marine Iguana's Salt Gland: Rafael Song, Micro- and Nanoscale Bioengineering Lab

  Research Center/ Lab:	Micro- and Nanoscale Bioengineering Lab
  Faculty Supervisor's Name:	Rafael Song
  Research Project Description:
  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:
• Cognitive Brain-Computer Interaction: Mohamad Eid, Applied Interactive Multimedia

  Research Center/ Lab:	Applied Interactive Multimedia
  Faculty Supervisor's Name:	Mohamad Eid
  Research Project Description:
  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:
• Computational Modeling of RNA: Serdal Kirmizialtin, Kirmizialtin Lab

  Research Center/ Lab:	Kirmizialtin Lab
  Faculty Supervisor's Name:	Serdal Kirmizialtin
  Research Project Description:
  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:
• Data Extraction from Unstructured Sources: Djellel Difallah, CITIES / Collaborative Intelligence Lab

  Research Center/ Lab:	CITIES / Collaborative Intelligence Lab
  Faculty Supervisor's Name:	Djellel Difallah
  Research Project Description:
  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 (see next activity).
  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:
• Designing an Edge AI-based Advanced Driver Assistance System Using Smart Mobile Phones: Muhammad Shafique, eBrain Lab

  Research Center/ Lab:	eBrain Lab
  Faculty Supervisor's Name:	Muhammad Shafique
  Research Project Description:
  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:
• Developing Tiny Machine Learning Algorithms for Wearable Healthcare: Muhammad Shafique, eBrain Lab

  Research Center/ Lab:	eBrain Lab
  Faculty Supervisor's Name:	Muhammad Shafique
  Research Project Description:
  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:
• Implementing Tiny Machine Learning Algorithms for Autonomous Mobile Robots: Muhammad Shafique, eBrain Lab

  Research Center/ Lab:	eBrain Lab
  Faculty Supervisor's Name:	Muhammad Shafique
  Research Project Description:
  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:
• Machine Learning Security: Developing Attacks and Defenses for Autonomous Vehicles in Smart Cities: Muhammad Shafique, CITIES

  Research Center/ Lab:	CITIES
  Faculty Supervisor's Name:	Muhammad Shafique
  Research Project Description:
  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:
• Development of New Technologies for Neuromodulation: Khalil Ramadi, Ramadi Lab for Advanced Neuroengineering and Translational Medicine

  Research Center/ Lab:	Ramadi Lab for Advanced Neuroengineering and Translational Medicine
  Faculty Supervisor's Name:	Khalil Ramadi
  Research Project Description:
  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:
  Weeks 1-2 Literature Review and training; Weeks 2-6 Data collection; Weeks 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:
• Electron Spin Choreography Using Microwaves: Asif Equbal, Equbal Research Lab

  Research Center/ Lab:	Equbal Research Lab
  Faculty Supervisor's Name:	Asif Equbal
  Research Project Description:
  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 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 not 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.
  Timeline:
  Week 1: Understand basics of Spin Resonance and quantum mechanics. Week 2: Learn basics of numerical simulations. Week 3-6: Perform choreography to understand dynamics of multi-coupled electron spins under a microwave irradiation. Week 7-8: Prepare a manuscript.
  Responsibilities:
  1. Perform computation of electron spin dynamics 2. Write a manuscript in a publishable format.
  Skills Needed:
  1. Quantum Mechanics 2. MatLab and data science understanding (not mandatory but preferred)
  Class Level:	Any
  Major:	Physcial chemistry, computer science, mathematics, physics
• Empirical Spatial Economics: Jordan J. Norris, Economics Program

  Research Center/ Lab:	Economics Program
  Faculty Supervisor's Name:	Jordan J. Norris
  Research Project Description:
  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. Current projects include: - Regional political fragmentation and economic development - The local composition of industry and long-run growth - International demand exposure and technical change in production
  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. Simulation analysis. Explore theoretical results numerically by simulating data. 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
• Engineering Materials for Future Quantum Technology: Asif Equbal, Center for Quantum and Topological Systems

  Research Center/ Lab:	Center for Quantum and Topological Systems
  Faculty Supervisor's Name:	Asif Equbal
  Research Project Description:
  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. 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 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: Learn Qiskit programming, build quantum circuits and test your understanding on the Gemini quantum computer. Week 4-7: Numerical optimize the molecular systems for future quantum technology. Week 7-8: Prepare a report.
  Responsibilities:
  1. Perform quantum mechanical computation, primarily using MatLab. 2. Learn and explore the Gemini 2-qubit Quantum Computer. 3. Prepare report
  Skills Needed:
  Basics of quantum mechanics and computer programming skills
  Class Level:	Any
  Major:	Physics, chemistry, and computer science
• Experiments With the Educational Quantum Computer: Asif Equbal, Center for Quantum and Topological Systems

  Research Center/ Lab:	Center for Quantum and Topological Systems
  Faculty Supervisor's Name:	Asif Equbal
  Research Project Description:
  There has been a lot exciting research on building quantum computers using various platforms using different physics and chemistry of the underlying quantum materials. Many of the existing prototypes rely on extreme laboratory conditions, such as large size which makes them immobile, and extreme temperatures close to absolute zero, which make them physically inaccessible for students. However, one of the earliest approaches, which relies on spin resonance, although operating on a small number of qubits, allows for such prototypes to be of desktop size and operating under standard/normal conditions, rendering them usefully accessible to students, hence of high educational value. The Center for Quantum and Topological Systems (CQTS) has acquired one such educational quantum computer, making NYUAD one of the first and limited number of institutions worldwide with such a system, and is very excited for the opportunities that this holds for our students. In this project the students will explore the underlying fundamental quantum mechanical principles that make quantum computing possible, highlighting the hands-on experimental aspects through the educational quantum computer. Explorations include Rabi oscillation experiments, Bell state preparation, BCS model simulation, various standard quantum gates, execution of of a quantum circuit, Already with such a machine one can explore various prominent quantum algorithms such as Deutsch, Rover, and HHL. This opportunity is open to any student with interest in experimental realization of quantum effects underlying quantum computing. Students from science and engineering are welcome to apply.
  Timeline:
  Week 1: Revisit quantum mechanics and computing Week 2-6: Experimental on the educational quantum computer
  Responsibilities:
  Prepare a report on details of each quantum computing experiment.
  Skills Needed:
  Basic quantum mechanics and computer programing
  Class Level:	Any
  Major:	Any
• First-time Emirati Fathers’ Identity, Attitudes, and Beliefs Regarding their Role in Parenting, Family, and Child Development: Antje von Suchodoletz, Teaching, Learning and Development Lab

  Research Center/ Lab:	Teaching, Learning and Development Lab
  Faculty Supervisor's Name:	Antje von Suchodoletz
  Research Project Description:
  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. We are early childhood development researchers at New York University Abu Dhabi and New York University Shanghai. 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; intensive training in (a) the data collection protocol; (b) the transcription process for qualitative interviews; and (c) the coding manual and coding procedure for the analyses of the interviews. Week 2: Accomplish reliability in the transcription/coding protocols (interview data) to ensure the quality of the data; training in the use of MAXQDA, a commonly used software in Social Sciences to transcribe and code qualitative data. 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: transcription and coding of interview data following standardized procedures and manuals; 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 Arabic and English (spoken and written); Basic knowledge in research methods in psychological / social science research would be beneficial but not required.
• Historical Geographical and Environmental Data About the Arabian Gulf: David Wrisley, Open Gulf

  Research Center/ Lab:	Open Gulf
  Faculty Supervisor's Name:	David Wrisley
  Research Project Description:
  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.
• Humanities Research Fellowship: Saqer Almarri, Humanities Research Fellowships for the Study of the Arab World

  Research Center/ Lab:	Humanities Research Fellowship
  Faculty Supervisor's Name:	Saqer Almarri
  Research Project Description:
  This project will consist of developing a primary sourcebook from a corpus of premodern Arabic text. The research assistant will refer to a digital text corpus, gather data from the corpus, cross-reference the data with other sources, then compile textual materials from the corpus into a document, and engaging in some translation of the work.
  Timeline:
  - Week 1-2: Introduction to the project. Introduction to the use of corpus, and the research workflow. - Week 3-4: Data gathering and verification from the corpus software. - Week 5-6: Compiling the data from the corpus software into a sourcebook document, with proper formatting and citations. - Week 7-8: Selection of materials and translation. - Weekly: There will be a weekly review with the research supervisor to address any possible adjustments in the research workflow.
  Responsibilities:
  The research assistant will review data from the corpus and develop a sourcebook with the guidance of the researcher.
  Skills Needed:
  -The research assistant should be comfortable reading and writing Arabic. -An ability to translate from Arabic, or a desire to learn to translate, is an advantage. -The research assistant should have basic skills in Arabic digital humanities, or a willingness to develop them.
  Class Level:	Any
  Major:	Any
  Other Requirements:
• Mars Research Group: Dimitra Atri, NYUAD Center for Space Science

  Research Center/ Lab:	Center for Space Science
  Faculty Supervisor's Name:	Dimitra Atri
  Research Project Description:
  We invite students to work in our research group. The group is interested in the atmosphere of Mars, its surface and subsurface chemistry, and exploring its present and past habitability. 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 Mars: All major spacefaring nations, including the UAE (Mars 2117) are seriously thinking about crewed missions to the planet 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-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.
  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
• Microfluidics for Biology and Life Sciences: Mohammad Qasaimeh, The Advanced Microfluidics and Microdevices Laboratory

  Research Center/ Lab:	The Advanced Microfluidics and Microdevices Laboratory
  Faculty Supervisor's Name:	Mohammad Qasaimeh
  Research Project Description:
  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, team work, writing skills, Wel lab skills
  Class Level:	Sophomore or above
  Major:	Engineering, biology, chemistry
  Other Requirements:
• The New UAE Work Week and its Impact on Women’s Careers: Milena Tekeste, Social Sciences Research Fellowship

  Research Center/ Lab:	Social Sciences Research Fellowship
  Faculty Supervisor's Name:	Milena Tekeste
  Research Project Description:
  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:
• Smart Materials for Electronics and Robotics Applications: Panče Naumov, Smart Materials Lab

  Research Center/ Lab:	Smart Materials Lab
  Faculty Supervisor's Name:	Pance Naumov
  Research Project Description:
  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
• Sound-Mapping Nineteenth-Century Paris: Madeleine Wolf, French Studies at NYUAD

  Research Center/ Lab:	French Studies at NYUAD
  Faculty Supervisor's Name:	Madeleine Wolf
  Research Project Description:
  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:
• Statistical Machine Learning, UAE Healthy Future Study: Raghib Ali, Public Health Research Center

  Research Center/ Lab:	Public Health Research Center
  Faculty Supervisor's Name:	Raghib Ali
  Research Project Description:
  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.
• UAE Healthy Future Study: Raghib Ali, Public Health Research Center

  Research Center/ Lab:	Public Health Research Center
  Faculty Supervisor's Name:	Raghib Ali
  Research Project Description:
  The UAE Healthy Future Study — a collaborative prospective observational cohort study among UAE nationals. It has long been known that the UAE has some of the highest rates of obesity, diabetes and heart disease in the world but the reasons for this are unclear. Until now there have been no studies done in the UAE or the region which can give us reliable answers as to why these diseases are so common. Now, for the first time, investigators from the leading universities and hospitals in the UAE have come together to find out why by setting up the UAE Healthy Future Study. The UAE Healthy Future Study seeks to determine how the health of 20,000 UAE national men and women, currently aged 18 to 40 is affected by their lifestyle, environment and genes, specifically looking at risk factors for obesity, diabetes and heart disease. This study will help us to find out: Why are obesity, diabetes and heart disease so common in the UAE? What is the relative importance of our genes, lifestyle (including diet, physical activity and tobacco use) and the environment in causing these diseases? What can be done to prevent these diseases in the future? To answer these questions reliably, long-term studies are needed which follow thousands of people over many years to see how their lifestyle and environment affects the risk of developing these diseases — these are called cohort studies. Previous cohort studies showed that smoking causes lung cancer; high blood pressure and cholesterol cause heart attacks and strokes, etc. The study is being led by investigators from NYUAD working in collaboration with the leading universities and hospitals in the UAE including UAE University, Zayed Military Hospital SEHA (Abu Dhabi Blood Bank), Zayed University, Khalifa University, Healthpoint Hospital, Cleveland Clinic Abu Dhabi, and Higher Colleges of Technology. This level of collaboration is unprecedented in the UAE and is helping to build capacity for population health research throughout the UAE and is one of the major accomplishments of the PHRC. The results of this study will provide a key evidence base for implementing the most effective health interventions and policies. It will be a national resource for the UAE, enabling researchers and policy makers to help build a healthier society for generations to come.
  Timeline:
  Timeline of tasks to be determined.
  Responsibilities:
  To assist in the epidemiological analysis and interpretation of data from the UAEHFS, including literature reviews and statistical analysis.
  Skills Needed:
  Nothing specific other than enthusiasm and willingness to work hard.
  Class Level:	Any
  Major:	Any
  Other Requirements:
• Urban Science: Monica Menendez, CITIES

  Research Center/ Lab:	CITIES
  Faculty Supervisor's Name:	Monica Menendez
  Research Project Description:
  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. 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: