Find Academic Supervisors

Adrian WellerView profile

Research Professor

• Artificial Intelligence
• Machine Learning
• Explainability
• +9 more

Adrian Weller is a prominent researcher and academic at the University of Cambridge, serving as a Director of Research in Machine Learning within the Department of Engineering. He holds multiple significant leadership roles including Programme Director for Trust and Society at the Leverhulme Centre for the Future of Intelligence (CFI), and previously served as Programme Director for AI at The Alan Turing Institute, the UK national institute for data science and AI. His work bridges theoretical machine learning research with practical applications and societal implications of artificial intelligence. Weller's research interests span a broad spectrum of AI and machine learning topics with a particular focus on ensuring beneficial societal outcomes. His work encompasses explainability, fairness, robustness, scalability, privacy, safety, and ethics in AI systems. He has made significant contributions to trustworthy machine learning, including developing frameworks for AI governance, certification, and human-AI collaboration. His research group actively investigates neuro-symbolic approaches, privacy-preserving techniques, and methods for improving the reliability and interpretability of AI systems. His recent publications demonstrate a strong trend toward addressing the practical challenges of deploying AI systems in real-world contexts, particularly focusing on certification frameworks, governance mechanisms, and human-centered approaches. His work spans theoretical advances in machine learning architectures while maintaining a strong connection to societal impact, with publications appearing in top venues across AI, machine learning, and interdisciplinary applications. Scientific Awards: MBE for services to digital innovation (2022 Queen's Birthday Honours) Turing AI Fellowship for Trustworthy Machine Learning Weller actively supervises a large group of PhD students and postdocs, with current students including Juyeon Heo, Yanzhi Chen, Katie Collins, Isaac Reid, Yichao Liang, Herbie Bradley, and Shoaib Siddiqui. His former students have gone on to positions at leading institutions including Google DeepMind, ETH Zurich, NYU, and MPI-IS Tübingen. He has served on numerous advisory boards including the Centre for Data Ethics and Innovation, UNESCO's expert group on AI ethics, and the World Economic Forum's Global Future Council on AI. His research has been supported through his Turing AI Fellowship and various collaborative projects focused on safe and ethical AI development. Weller leads a vibrant research group focused on trustworthy machine learning, which actively organizes workshops and conferences including ICML 2024 (where he served as Program Chair), multiple workshops on responsible AI, and events through the ELLIS network. His group collaborates extensively across disciplines, working with researchers in computer science, social sciences, law, and policy to address the multifaceted challenges of developing beneficial AI systems.

Hassan Qudrat-UllahView profile

Professor

• Sustainability
• Global/Climate Change
• System Dynamics
• +3 more

Dr. Hassan Qudrat-Ullah is a Professor at the School of Administrative Studies, York University, and Coordinator of the Certificate in Logistics Management. He holds a PhD in Decision Sciences from NUS Business School and completed a post-doctoral fellowship at Carnegie Mellon University. His research focuses on dynamic decision making, system dynamics modeling, energy planning, and interactive learning environments. He teaches courses on quantitative methods, logistics, and decision analysis, informed by global industry experience across 20+ countries. Research interests include sustainability, climate change, systems thinking, and educational applications of decision sciences. He serves as Editor-in-Chief of the International Journal of Complexity in Applied Science and Technology and is a member of IEEE, DSI, and the International System Dynamics Society. His work has been published in Energy , Decision Support Systems , and others. Key projects include studies on 'structured-debriefing in dynamic decision making' and renewable energy policies in Africa. His recent articles (2023–2025) address AI integration in energy governance, system dynamics for supply chain resilience, and education for sustainability. Hassan advocates for systems thinking in K-12 education and enjoys traveling (visited 129 countries) and bird-watching.

Tim AlthoffView profile

Associate Professor

• Artificial Intelligence
• Human-Centered Computing
• Data Science
• +5 more

Tim Althoff is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering, University of Washington, specializing in Artificial Intelligence and Human-Centered Computing. His research focuses on behavioral data science, combining Data Science Natural Language Processing Social Computing Human-Centered AI Ethics & Fairness to extract insights about health and well-being. Recent publications highlight advancements in: Mental health support through AI Wearable sensor health monitoring Online community analysis Reproducibility in data science Public health interventions with notable papers in ACL, Nature Machine Intelligence, and NeurIPS. Scientific recognition includes: ACL 2023 Outstanding Paper Award WWW 2021 Best Paper Award Double ICWSM 2021 Best Paper Awards SIGKDD Dissertation Award 2019 Fulbright Scholarship German National Merit Foundation Actively mentoring postdoctoral researchers and seeking PhD students in areas like neural representation learning, NLP applications to psychology, and mobile health technologies through his Behavioral Data Science Group .

Sarita V AdveView profile

Professor

• Computer Architecture
• Extended Reality Systems
• Heterogeneous Computing
• +4 more

Sarita V Adve is the Richard T. Cheng Professor of Computer Science at the University of Illinois at Urbana-Champaign, where she conducts research spanning hardware, programming languages, operating systems, and applications with a focus on domain-specific systems. Her work bridges theoretical foundations and practical implementations, particularly in extended reality and heterogeneous computing. Her educational background includes a Ph.D. and M.S. in Computer Science from the University of Wisconsin-Madison (1993, 1989) and a B.Tech in Electrical Engineering from the Indian Institute of Technology Bombay (1987). Prior to joining Illinois, she served on the faculty at Rice University from 1993 to 1999. Adve's research centers on generalizable and scalable specialization for domain-specific systems, with current emphasis on extended reality (XR) systems including virtual, augmented, and mixed reality. She chairs the ILLIXR consortium to democratize XR research and developed the first fully open-source XR system (ILLIXR). Her foundational contributions include memory consistency models for C++ and Java programming languages, the Spandex coherence framework for heterogeneous systems, and software-driven approaches for hardware reliability. Her work spans hardware reliability (SWAT and RAMP projects), power management (GRACE system), and instruction-level parallelism. Recent publications reveal a strong focus on energy-efficient XR systems, hardware-software co-design for AI workloads, and resilience analysis. Her team explores rendering offload, visual-inertial odometry optimization, and compositional error injection frameworks, often targeting tradeoffs between energy, latency, and accuracy in mobile and edge environments. Fellow of the American Academy of Arts and Sciences Fellow of the ACM and IEEE ACM/IEEE-CS Ken Kennedy Award Anita Borg Institute Woman of Vision in Innovation Award ACM SIGARCH Maurice Wilkes Award Alfred P. Sloan Research Fellowship UIUC University Scholar University of Illinois Campus Award for Excellence in Graduate Student Mentoring Adve actively mentors students and has received multiple teaching awards. She co-founded the CARES movement to address discrimination in CS research events and chairs CS@Illinois CARES. Her service includes leadership roles in ACM SIGARCH (2015-2019), DARPA/ISAT study group, ACM Council, and Computing Research Association. She has secured significant funding including DARPA initiatives and Google Faculty Research Awards. She leads the ILLIXR consortium and has established collaborative research programs such as the $8.3M DARPA Joint University Microelectronics Program. Her lab focuses on open-source XR development, heterogeneous system architectures, and reliability-aware designs, with strong industry and government partnerships.

• Learning Sciences
• Technology-Enhanced Learning
• Collaborative Learning
• +4 more

Professor Nancy W. Y. Law is a leading scholar in Learning Sciences and Technology at the University of Hong Kong's Faculty of Education . She has served as Founding Director of the Centre for Information Technology in Education (CITE) (1998-2013) and currently holds the Chair of Learning Sciences and Technology . Her career spans over 25 years of international comparative studies, policy analysis, and large-scale educational innovation. Current roles: Associate Dean (Strategic Development), HKU Key affiliations: Sciences of Learning Strategic Research Theme (co-convener) Research Expertise Her work focuses on technology-enhanced learning , digital literacy , knowledge building communities , and multilevel educational change . She pioneered network models of teacher innovation and socio-technical frameworks for sustainable pedagogical transformation, particularly in STEM education and Cyberbullying prevention . Scientific Leadership With over 25 major research grants (2000-2023) exceeding HK$50 million, she leads projects like: Learning and Assessment for Digital Citizenship Jockey Club Self-directed Learning in STEM Design-Aware Learning Analytics A Fellow of the International Society of Learning Sciences and recipient of the HKSAR Humanities and Social Sciences Prestigious Fellowship , she has supervised numerous international comparative studies including SITES 2006, ICILS 2013, and longitudinal digital citizenship research (2019-2021).

Steven I-Jy ChienView profile

Professor

• Transportation Engineering
• Urban Rail Transit
• Sustainable Transportation Systems
• +4 more

Steven I-Jy Chien serves as Professor and Director of the Transportation Program within the Department of Civil and Environmental Engineering at the New Jersey Institute of Technology (NJIT). His career spans academia, government, and industry with significant contributions to transportation engineering research and practice. His educational credentials include: Ph.D. in Civil and Environmental Engineering from University of Maryland-College Park (1995) M.S. in Civil and Environmental Engineering from University of Maryland-College Park (1991) B.S. in Civil Engineering from Tamkang University (1983) Professor Chien's research focuses on transportation system resilience, sustainable transit operations, and advanced traffic modeling. His work addresses critical challenges in urban rail networks, demand-responsive transit services, and energy-efficient transportation systems. He employs sophisticated computational methods including genetic algorithms, machine learning, and Bayesian approaches to solve complex transportation problems involving network vulnerability, passenger behavior, and infrastructure optimization under uncertainty. Analysis of his recent publications reveals strong emphasis on transportation resilience against cascading failures, sustainable operations for electric transit systems, and pandemic-responsive aviation scheduling. His research spans diverse geographic contexts including major Chinese metropolitan areas and U.S. transportation networks, demonstrating global applicability of his methodologies. His professional recognition includes: 2024 Keynote Speaker at Union-Tech Lecture, National Taiwan Ocean University 2022 Keynote Speaker at International Conference of Chinese Institute of Transportation 2022 Best Poster Award from New Jersey Department of Transportation Professor Chien has secured research funding from federal agencies including the Federal Highway Administration (FHWA) where he contributed to CORSIM traffic simulation software development. His industry experience with China Engineering Consultants Inc. and Information Dynamic Inc. informs his practical approach to transportation challenges. As Transportation Program Director, he oversees curriculum development and industry partnerships that prepare students for transportation sector careers. He maintains active collaboration with transportation agencies globally, particularly through his leadership in the Transportation Program at NJIT which serves as a hub for innovation in urban mobility solutions.

• Ethical Implications of Artificial Intelligence
• Societal Implications of Artificial Intelligence
• Policy Implications of Artificial Intelligence
• +4 more

Hoda Heidari is the K&L Gates Career Development Assistant Professor in Ethics and Computational Technologies at Carnegie Mellon University (CMU), with joint appointments in the Machine Learning Department and the Institute for Software, Systems, and Society. She is affiliated with the Human-Computer Interaction Institute and the Heinz College of Information Systems and Public Policy, and co-leads the university-wide Responsible AI Initiative and K&L Gates Initiative for Ethics and Computational Technologies. Education: PhD in Computer and Information Science (University of Pennsylvania), MSc in Statistics (Wharton School) Her research focuses on the Ethical, Societal, and Policy Implications of AI , particularly fairness and accountability in high-stakes domains. Her work includes evaluating risks/benefits of general-purpose AI, human-AI decision-making systems, and AI governance frameworks. She has received multiple awards, including best paper honors at AIES, FAccT, and SAT-ML. Her research is supported by the NSF Program on Fairness in AI, PwC, CyLab, Meta, and J. P. Morgan. Recent Publications examine generative AI safety, fairness measurement, AI incident documentation, and ethical governance. Her teaching includes courses on Responsible AI, ML Ethics, and Societal Decision-Making, with a focus on preparing students to critically analyze AI's societal impact. Scientific Awards: Best Paper (AIES 2024, FAccT 2021, SAT-ML 2023), Exemplary Track Award (EC 2021) Grants: NSF, PwC, CyLab, Meta, J. P. Morgan She advises doctoral students and postdocs across CMU departments and collaborates with interdisciplinary teams. Her service includes organizing AI safety workshops and advising on NIST guidelines for AI red-teaming.

• International Entrepreneurship
• Technological Innovation
• Corporate Entrepreneurship
• +7 more

Shaker A. Zahra is a Professor of Strategy and Entrepreneurship at the Carlson School of Management, University of Minnesota , where he holds the Robert E. Buuck Chair of Entrepreneurship. He has served as Department Chair, Director of the Holmes Center for Entrepreneurship, and Academic Co-Director of Carlson Ventures Enterprises, and was Founding Co-Director of the Center for Integrative Leadership. Previously, he held the Paul T. Babson Distinguished Professorship at Babson College and faculty roles at Georgia State University and the University of Twente (Netherlands). Education : PhD in Business Administration (University of Mississippi), MBA (National University), B. Commerce (Al-Azhar University) His research focuses on corporate and international entrepreneurship , dynamic capabilities , and social entrepreneurship , particularly in technology-based industries. He explores industry emergence, strategic novelty, and firm heterogeneity, applying theories across global markets. His recent articles emphasize corporate entrepreneurship, international new ventures, and the role of dynamic capabilities in innovation. His work spans industries like robotics, software, pharmaceuticals, and nanotechnology, with studies in China, Brazil, India, and Europe. Scientific Awards : 2014 Global Award for Entrepreneurship Research, 5 Honorary PhDs, Fellowships from AOM, IFERA, and others, and over 20 Best Paper Awards. He has advised 75+ PhD students, taught across undergraduate to executive programs, and consulted for global technology firms. His leadership includes roles on 25+ journal editorial boards, organizing conferences, and delivering 40+ keynote speeches worldwide.

M. Granger MorganView profile

Professor

• Energy Systems
• Climate Change Policy
• Risk Analysis
• +5 more

M. Granger Morgan is the Hamerschlag University Professor of Engineering at Carnegie Mellon University , with appointments in the Department of Engineering and Public Policy , Department of Electrical and Computer Engineering , and H. John Heinz III College . He co-directs the NSF Center for Climate and Energy Decision Making and the Electricity Industry Center at CMU. Education: Ph.D., Applied Physics and Information Science, University of California, San Diego (1969) M.S., Astronomy and Space Science, Cornell University (1965) B.A., Physics, Harvard College (1963) His research spans science, technology, and public policy with focus areas in energy systems , climate change mitigation , electric grid resilience , and uncertainty characterization in policy analysis . Recent publications analyze hydrogen market barriers , carbon sequestration timelines , and interdependent energy infrastructure risks . Scientific leadership includes: Member, National Academy of Sciences Member, American Academy of Arts and Sciences Co-chair, NAS Report Review Committee Board member, International Risk Governance Council Foundation Advisory Board, E.ON Energy Research Center, RWTH Aachen DOE Electricity Advisory Committee member Former EPA Science Advisory Board Chair Fellow of AAAS, IEEE, and Society for Risk Analysis Contact: Office 5220 Wean Hall, Phone 412-268-2672, Email granger.morgan@andrew.cmu.edu

• Financial Analysis
• Equity Valuation
• Life Insurance
• +3 more

Demetris Christodoulou is an Associate Professor in Accounting, Governance and Regulation at the University of Sydney. He holds a BEcon from Piraeus University, an MSc(Fin) from the University of York (UK), and a PhD from Athens University of Economics and Business (AUEB). His research focuses on applying data analytics, econometrics, and visualization techniques to financial analysis, equity valuation, life insurance, and financial advice. He co-directs the PEMA research group, specializing in productivity and performance measurement analytics, and previously led the MEAFA research group (2007–2022). He has collaborated extensively with industry partners including Deloitte and Australian insurers, and developed training programs for over 1,000 executives. His work includes open-source contributions to Stata software and the Graph Workflow platform, alongside $662k in workshop-generated funds supporting academic programs. He has advised multiple PhD students and taught at leading universities globally. Education: BEcon in Economics (Econometrics), Piraeus University MSc in Finance, University of York (UK) PhD in Accounting and Financial Analysis, Athens University of Economics and Business His research interests span financial reporting models, life insurance underwriting strategies, and behavioral finance. Recent projects address dishonesty mitigation in insurance disclosures and the adviser effect on customer disclosures. He has published widely in top journals like the Review of Accounting Studies and Stata Journal , and his work was featured in The Australian for insights on insurance fraud reduction. He maintains international collaborations, including visiting roles at Columbia Business School and the University of Cyprus, and serves on advisory boards for organizations like Behaviour.ai. Publications highlight methodological innovations in econometrics and visualization, with 2025's upcoming Stata Journal paper advancing time-series analysis techniques. His grants include partnerships with industry on longitudinal studies of insured lives, aiming to improve risk modeling and public policy insights.

Ana MijicView profile

Professor

• Water Systems Integration
• Sustainable Water Management
• Urban Water Resilience
• +5 more

Professor Ana Mijic is a leading academic in water systems integration at Imperial College London's Department of Civil and Environmental Engineering (Faculty of Engineering). Her work focuses on developing systems tools to balance economic growth with sustainable water use, flood management, and water quality under future uncertainties. She leads high-profile projects like the EPSRC VENTURA initiative and the NERC CAMELLIA impact programme, emphasizing adaptive planning and grey/green infrastructure integration in urban systems. Education: BEng (First Class) in Civil Engineering from the University of Belgrade (Serbia), MSc (Distinction) in Hydrology for Environmental Management, and PhD in Earth Science & Engineering from Imperial College London (2013). Previously served as a teaching assistant in Fluid Mechanics and Hydrometry at Belgrade University. Research interests include whole-water system modelling, socio-hydrological interactions, and nature-based solutions for resilient urban water systems. Her work bridges academia and practice through partnerships with regulators like the UK Environment Agency and global initiatives like the IAHS HELPING programme. Awards include the Satish Dhawan Visiting Chair Professorship (2022) and the 2019 Imperial President’s Award for Excellence in Research (as part of her Hydrology team). She co-leads Imperial’s Transition to Zero Pollution (TZP) Urban Ecosystems theme and serves on editorial boards for journals like Water Security . Her contributions span over 50 peer-reviewed articles (2020–2025), focusing on integrated water management frameworks, AI-driven monitoring, and systemic approaches to urban resilience. She advocates for participatory decision-making and policy coherence in water governance.

• Artificial Intelligence
• Privacy and Data Protection
• Trustworthy AI
• +4 more

Prof. Dr. Pinar Yolum Birbil is a leading researcher in Responsible AI at the Faculty of Science , Utrecht University . Her work bridges Artificial Intelligence , Privacy and Data Protection , and Software Agents , focusing on Human-Centered AI and Trustworthy Systems . She is part of the AI & Data Science and Responsible AI research groups. PhD in Computer Science, North Carolina State University (2003) MS in Computer Science, North Carolina State University (2000) BSc in Computer Engineering, Marmara University (1998) Her research explores Privacy Preservation in collaborative systems, Computational Theory of Mind for human-agent coordination, and Norm-Based AI Systems . Recent projects include the Hybrid Intelligence Center and tools like PANOLA for privacy support. She investigates how AI can balance user autonomy , ethical norms , and societal values in applications ranging from urban planning to healthcare. Her scientific publications (2023-2025) span topics like Explainable Privacy , Trust in Hybrid Teams , and AI for Diabetes Management , appearing in venues such as JAIR , AAMAS , and ACM TOIT . She emphasizes collaborative AI , with contributions to multiagent simulations and privacy-preserving mechanisms . Scientific Awards : NC State University Alumni Hall of Fame (2017) Woman Entrepreneur of the Year (Microsoft Turkey & KAGIDER, 2017) Bogazici University Academic Encouragement Award (multiple years) Best Paper Award at ESAW 2009 She supervises a dynamic research group with PhD students working on Hybrid Intelligence , Computational Ethics , and Privacy Modeling . Her projects often involve interdisciplinary collaboration with institutions like TNO and the Transforming Cities Hub .

• Recommender Systems
• Machine Learning
• Natural Language Processing
• +4 more

Julian McAuley is a Professor in the Department of Computer Science and Engineering at the University of California, San Diego's Jacobs School of Engineering. His research spans recommender systems, machine learning, natural language processing, music information retrieval, and multimodal learning. He maintains an active research group with numerous PhD students and postdocs working on cutting-edge AI problems. His research interests focus on developing advanced algorithms for personalized recommendation systems, with particular emphasis on sequential recommendation, multimodal learning, and integrating large language models with traditional recommendation approaches. His work bridges the gap between theoretical machine learning and practical applications across multiple domains including e-commerce, music, and healthcare. McAuley has published extensively in top-tier conferences including NeurIPS, ICML, KDD, SIGIR, and ACL, with his most recent work exploring the intersection of large language models and recommendation systems. His publications reveal a strong trend toward multimodal approaches that combine text, vision, and audio for more comprehensive understanding and recommendation. He has received significant research funding from major technology companies including Google, Amazon, Facebook, Adobe, and Samsung, as well as government agencies like the National Science Foundation and Department of Defense. His work has practical applications across multiple industries, with a focus on improving user experience through better personalization. McAuley advises numerous PhD students who have gone on to successful careers at leading technology companies and academic institutions. His former students include Wang-Cheng Kang and Jianmo Ni at Google DeepMind, Chris Donahue and Zachary Lipton as assistant professors at CMU, and Ruining He at Google Deepmind.

Song KimView profile

Associate Professor

• International Political Economy
• Formal and Quantitative Methodology
• Big Data Analysis
• +5 more

Song Kim is an Associate Professor of Political Science at the Massachusetts Institute of Technology (MIT) and a Faculty Affiliate at the Institute for Data, Systems, and Society (IDSS). He holds a Ph.D. in Politics from Princeton University, where he was awarded the Harold W. Dodds Fellowship (2012-2013). His research focuses on International Political Economy, Formal and Quantitative Methodology, and Big Data analysis of international trade. He is particularly known for his work on firm-level political incentives in trade liberalization, which earned him the 2015 Mancur Olson Award and the 2018 Michael Wallerstein Award for best published article in political economy. Kim develops computational methods for analyzing trade data, including dimension reduction and visualization techniques. He maintains two key databases: LobbyView (tracking firm lobbying efforts) and TradeLab (for trade policy analysis). His research has been published in top journals such as the American Political Science Review, American Journal of Political Science, and International Organization. Educations : Ph.D. in Politics (Princeton University), B.A. not explicitly stated. His research interests include the dynamical evolution of lobbying networks, strategic links between political donations and lobbying, and the political origins of trade regulations. He also contributes methodological innovations, such as two-way fixed effects models and matching methods for causal inference with panel data. Awards : Mancur Olson Award (2015) Michael Wallerstein Award (2018) Harold W. Dodds Fellowship (2012-2013) Advising & Grants : No listed advisees. His work is supported by MIT’s IDSS and institutional funding. He collaborates on software tools like the 'wfe' and 'concordance' R packages, advancing computational social science. Labs/Teams : Associated with MIT’s Political Science Department and IDSS, focusing on interdisciplinary projects in trade, lobbying, and quantitative methods.

Antti HonkelaView profile

Professor

• Privacy-preserving machine learning
• Differential Privacy
• Bayesian Machine Learning
• +3 more

Antti Honkela is a Professor of Data Science at the University of Helsinki's Department of Computer Science, within the Faculty of Science. He also serves as the Coordinating Professor for the Privacy-preserving and Secure AI Research Programme at the Finnish Center for Artificial Intelligence (FCAI), and as Deputy Director of the Master's Programme in Data Science. His roles include membership in the Health and Social Data Permit Authority (Findata) and as an Action Editor for Transactions on Machine Learning Research. Honkela's research focuses on privacy-preserving machine learning, differential privacy, Bayesian methods, and their applications in computational biology and healthcare. He leads projects such as the European Lighthouse in Secure and Safe AI (ELSA) and the Data Literacy for Responsible Decision-making initiative. His work emphasizes developing robust frameworks for privacy-aware AI, including differentially private synthetic data and federated learning. Honkela has advised numerous PhD and Master's students, and his contributions span theoretical advancements and practical implementations, such as the D3p Python package for differentially private probabilistic programming. Key contributions include advancements in Bayesian inference from synthetic data, privacy accounting mechanisms, and computational methods for genomic epidemiology. His interdisciplinary approach bridges machine learning, statistics, and healthcare, addressing challenges in data privacy and secure AI deployment.