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Research

MIDSAI is poised to significantly advance various research activities across diverse clusters. These clusters harness cutting-edge AI and data science technologies to address real-world challenges like healthcare, urban informatics, robotics, social sciences, and sustainable development. Students and faculty engage in transformational research and practical applications through collaborations within these clusters, which are aligned with institutional and UAE strategic priorities.

Research-intensive

Students engage in research from the start:

  • A full-year thesis on either academic or industry problems.
  • Annual two-week research workshops, culminating in a hackathon.
  • A regular data science seminar bringing speakers from academia and industry.
  • Opportunities to work closely with faculty on real, interdisciplinary research questions.

Engineering Research Clusters

  • Robotics and AI: Students explore human-robot interaction and control systems in collaboration with the NYUAD Center for Artificial Intelligence and Robotics (CAIR), contributing to innovations in robotics through AI.

  • Urban Informatics: Research in this cluster develops data science and AI tools to address problems in transportation, urban fairness, and decision-making. Students will collaborate with NYUAD Center for Interacting Urban Networks (CITIES) researchers.

  • Wireless Communications: The focus is on data-driven models for optimizing next-generation networks.

Science Research Clusters

Scalp electrodes used in electroencephalograms
  • Neuroscience and Brain Behavior: Data science techniques analyze datasets to gain insights into human behavior, enhancing courses related to AI applications in social science.

  • Complex Biological Systems: Students apply computational modeling to understand complex biological behaviors, enriching life sciences research.

  • Quantum Computing and Technology: The research involves quantum machine learning applied to various real-world problems and provides opportunities for quantum technology exploration. Students will benefit from collaborations with the NYUAD Center for Quantum and Topological Systems (CQTS).

  • Interdisciplinary Data Science and AI: blurb tk. Students will have collaborations with the NYUAD Center of Interdisciplinary Data Science and AI (CIDSAI).

  • Artificial Intelligence and Natural Language Processing: Research areas include Arabic natural language processing, machine translation, text analytics, and dialogue systems. Students can collaborate with NYUAD's Computational Approaches to Modeling Language (CAMeL) Lab.

Social Science Research Clusters

  • Computational Social Science: Students analyze large-scale social data, addressing societal inequalities and informing policy-making with data-driven insights.

  • Government and Public Policy: AI and data science tools are used to model and analyze government policies for a positive societal impact.

Innovative Applications and Faculty-led Research

  • Healthcare: AI-driven research in personalized diagnostics, treatment, and post-COVID conditions enhances medical outcomes and patient care.

  • Human-Machine Interaction (HMI): AI systems are developed to improve engagement recognition and understanding of emotions in collaborative environments.

  • Assistive Technologies: AI supports navigation for visually impaired individuals and learning tools for ADHD students.

  • Social Equity and Ethics: Studies focus on editorial diversity, digital inequality, and AI fairness in medical applications.

  • 3D Computer Vision and Robotics: Research in vision-language models and medical imaging supports advancements in robotics and healthcare.

  • Natural Language Processing and Knowledge Graphs: Multilingual NLP systems enhance social behavior studies and knowledge alignment.
  • Environmental Support: AI models aid urban systems management and assess crowd behavior to mitigate pandemic risks.

  • Explainable AI: Research on AI-assisted decision-making enhances transparency and collaboration in fields like healthcare.

The program fosters interdisciplinary collaboration, preparing students to tackle global challenges with AI and data science insights and emphasizing the importance of ethical considerations and societal impact.