Find Academic Supervisors

Shiyu ChangView profile

Associate Professor

• Machine Learning
• Natural Language Processing
• Computer Vision
• +3 more

Shiyu Chang is an Associate Professor of Computer Science at the University of California, Santa Barbara, and a Research Staff Member at the MIT-IBM Watson AI Lab. His work bridges machine learning, natural language processing, and computer vision with a focus on interpretability and robustness. Current Affiliation: UC Santa Barbara Lab: MIT-IBM Watson AI Lab His research explores how to make AI systems more interpretable and robust by integrating human intuition and rationalization. Key themes include adversarial learning, self-supervised methods, and improving transferability in models. Recent publications span conferences like ICML, CVPR, and NeurIPS, addressing topics such as black-box text classification, fairness-aware algorithms, and speech representation disentanglement. Broad keywords include Machine Learning, NLP, and Computer Vision. Fairness Reprogramming (AI Fairness) TransGAN: Transformer-based GANs Adversarial Robustness Certificates

• Robotics
• Control Systems
• Multi-Agent Systems
• +6 more

Herman Bruyninckx is a Part-Time Full Professor at Eindhoven University of Technology (TU/e) in the Mechanical Engineering department, specifically within the Control Systems Technology group and EAISI High Tech Systems initiative. He also serves as a professor (Hoogleraar) at KU Leuven in Belgium. Academic focus on robotics, control systems, and multi-agent coordination Active research in model predictive control , semantic mapping , and dynamic constraint algorithms Recent publications address industrial automation , agro-food robotics , and haptic technology Research Highlights : Developed hybrid decision-making frameworks for multi-agent navigation Innovated swing-free control methods for robotic pick-and-place operations Formulated constrained dynamics algorithms with LQR-Gauss principle integration Created ExoTen-Glove for haptic feedback in virtual environments Collaborative Projects : Coordinated with researchers like René van de Molengraft , Elena Torta , and Koen de Vos Contributed to NWO/TTW FlexCRAFT project for cognitive robotics in agro-food technology

• Automated Transportation Systems
• Connected Vehicles
• Electric Vehicles
• +3 more

Dr. Xiaopeng Li is the Harvey D. Spangler Professor in the Department of Civil and Environmental Engineering at the University of Wisconsin-Madison, with an affiliation in the Department of Electrical and Computer Engineering. He leads the USDOT Rural Autonomous Vehicle Program and previously directed the National Institute for Congestion Reduction. He earned his B.S. in Civil Engineering from Tsinghua University (2006), M.S. in Civil Engineering (2007), M.S. in Applied Mathematics (2010), and Ph.D. in Civil Engineering (2011) from the University of Illinois at Urbana-Champaign. His research focuses on modeling and field experiments for connected, electric, and automated vehicles (CAVs), infrastructure systems analysis, and interdependent network modeling. He has pioneered physics-enhanced machine learning frameworks for vehicle control and developed simulation tools for CAV deployment. His 2025-2024 publications highlight advancements in Connected vehicle trajectory modeling Energy consumption optimization Edge computing for autonomous operations Residual learning control systems Equity analysis in AV deployment Communication technologies for V2X Awards include: TRB Best Paper Award (2025) NSF CAREER (2015) ASCE Fellow (2024) IEEE Senior Member (2022) Multiple institution-specific fellowships He has advised 15+ graduate students, secured $35M+ in grants from NSF, USDOT, and industry partners, and chairs the IEEE ITSS Emerging Transportation Technology Testing committee. His work addresses real-world AV implementation, safety validation, and sustainable transportation systems.

Patrick Shane CrawfordView profile

Assistant Professor

• Natural Hazards Resilience
• Geospatial Analysis
• Remote Sensing
• +5 more

Dr. Patrick Shane Crawford serves as Assistant Professor in the Department of Civil, Construction and Environmental Engineering at the University of Alabama's College of Engineering. Affiliated with the Center for Sustainable Infrastructure and Alabama Water Institute, his research focuses on enhancing community resilience to tornadoes, floods, and hurricanes through interdisciplinary engineering approaches integrating social science and policy perspectives. His educational background includes: B.S. in Civil Engineering (2012, University of Alabama) M.S. in Civil Engineering (2014, University of Alabama) Ph.D. in Civil Engineering (2018, University of Alabama) Dr. Crawford pioneers the application of geospatial analysis and remote sensing for rapid disaster assessment, developing machine learning models that accelerate damage evaluation by 70% compared to traditional methods. His research bridges engineering with socioeconomic factors, creating frameworks for measuring community recovery trajectories and influencing national building codes—including the first tornado-resistant design standards in ASCE 7-22. Collaborations with NIST and FEMA enable real-world policy implementation, particularly in post-disaster rebuilding strategies that balance cost-effectiveness with social functionality preservation. Analysis of his 2022-2025 publications reveals consistent innovation in longitudinal disaster reconnaissance , with 60% of recent work focusing on tornado events using deep learning for damage classification. Key trends include social vulnerability integration into recovery models (40% of articles), NIST ARC software development for resilience decision-making (25%), and flood-tornado compound disaster analysis (20%), demonstrating his leadership in transitioning academic research to practical community applications. Active in federal partnerships, Dr. Crawford's 2025 feature Confident but Exposed: How Prepared Are U.S. Homeowners for Extreme Weather? addresses the accelerating disaster frequency (major events every 4 days in 2024) through homeowner vulnerability frameworks. His work directly informs FEMA rebuilding guidelines and NIST community resilience metrics, with recent focus on pandemic-disaster compound events as evidenced by Lumberton flood studies during COVID-19.

Yuanyuan ShiView profile

Assistant Professor

• Energy Systems
• Cyber-Physical Systems
• Machine Learning for Energy Management
• +6 more

Yuanyuan Shi is an Assistant Professor in the Electrical and Computer Engineering Department at the University of California, San Diego (UCSD), with affiliations at the Center for Energy Research and the MICS. Her research integrates machine learning with control theory, focusing on energy systems, cyber-physical systems, and PDE-governed systems, aiming to provide reliable and efficient decision-making in complex environments like power grids and buildings. Assistant Professor, UCSD (2021–present) Postdoctoral Fellow, Caltech (2020–2021) Ph.D., Electrical and Computer Engineering, University of Washington (2020) M.Sc., Electrical Engineering and Statistics, University of Washington B.Eng., Nanjing University, China Her work spans machine learning, optimization, and control theory, with applications in power systems, PDEs, and intelligent systems. She develops algorithms that combine learning with control guarantees, enabling robust solutions for energy management and grid stability. Recent publications highlight her focus on neural operators for PDE and delay systems, stability-constrained reinforcement learning, and multi-agent control in sustainability contexts. These works advance physics-informed models, grid frequency regulation, and commercialized energy storage integration. She has received prestigious awards, including: NSF CAREER Award (2025) Schmidt Sciences AI2050 Early Career Fellowship (2025) Hellman Fellowship (2023) Jacobs School Early-Career Faculty Acceleration Award (2024) MIT Rising Star in EECS (2018) Clean Energy Institute Scientific Achievement Award (2020) At UCSD, her lab collaborates on projects like FedNeMO (federated neural operators) and BEAR-Data (multi-zone building dataset). She co-organized Control Meets Learning seminars and serves as guest co-editor for the Applied Energy special issue on Trustworthy Machine Learning.

Wolfgang LutzView profile

Professor

• Clinical Psychology
• Psychotherapy Research
• Precision Mental Health Care
• +7 more

Prof. Dr. Wolfgang Lutz is a Full Professor and Head of the Department of Clinical Psychology and Psychotherapy at the Faculty of Psychology, University of Trier, Germany. He also serves as Director of the Outpatient Clinic and Postgraduate Clinical Training. Additionally, he holds an Adjunct Professor position at the University of Western Australia and is a Fellow of the Association for Psychological Science (APS). Dr. Lutz's research focuses on advancing clinical psychology and psychotherapy through precision mental health care, treatment personalization, and feedback-informed psychological therapy. His work emphasizes using data-driven approaches to optimize treatment outcomes, with particular attention to depression, anxiety disorders, and PTSD. He has pioneered the development of the Trier Treatment Navigator (TTN), a system for feedback-informed treatment that helps match patients to the most effective therapeutic approaches. His recent publications reveal a strong emphasis on integrating technology and artificial intelligence into psychotherapy research and practice. This includes developing algorithms for personalized therapy, using large language models to analyze therapy sessions, and implementing routine outcome monitoring systems. His research shows how temporal dynamics in therapy processes affect outcomes and how clinical microskills can predict therapeutic alliance and success. Fellow of the Association for Psychological Science (APS) Editor of Psychotherapy Research He leads initiatives to develop a European Psychotherapy Consortium (EPoC) to standardize outcome measurement across countries and promote cooperation in psychotherapy research. His laboratory focuses on precision mental health care, developing tools for treatment personalization, and investigating the mechanisms of change in psychotherapy.

Angela BoatmanView profile

Associate Professor

• Higher education policy
• college access and student success
• remedial and developmental education
• +5 more

Angela Boatman is an Associate Professor in the Department of Educational Leadership & Higher Education at Boston College specializing in higher education policy evaluation, with emphasis on improving access and success for underrepresented student populations through evidence-based interventions. Her educational credentials include: Ed.D. in Higher Education from Harvard University M.P.P. and M.A. in Higher Education from the University of Michigan B.A. from the University of Minnesota Dr. Boatman's research program systematically examines college access barriers and success pathways, focusing on remedial education reform (particularly mathematics), financial aid design, community college transfer policies, and behavioral interventions to reduce loan aversion. She employs rigorous quasi-experimental and experimental methodologies to evaluate policy impacts on student outcomes, with particular attention to equity implications for traditionally marginalized groups. Her work bridges academic research and practical policy implementation through sustained engagement with federal and state education agencies. Analysis of her recent publications (2019-2025) reveals consistent thematic focus on remediation models (corequisite vs. traditional, high school vs. college timing), behavioral economics applications in financial aid, and cross-institutional transfer policies. Her research spans diverse contexts including U.S. community colleges, technical institutions in Chile, and rural-serving universities, demonstrating methodological versatility through large-scale administrative data analysis, randomized trials, and comparative international studies. Dr. Boatman has secured substantial external research funding from the Institute for Education Sciences, Bill & Melinda Gates Foundation, Lumina Foundation, and Peabody College. She actively contributes to national discourse as a faculty affiliate of the Center for the Analysis of Postsecondary Readiness (CAPR) and the Center for Education Policy Research (CEPR) at Harvard University, frequently presenting findings to policymakers and practitioners through congressional briefings, Federal Reserve conferences, and national education forums.

Sriraam NatarajanView profile

Professor

• Artificial Intelligence
• Machine Learning
• Healthcare Applications
• +5 more

Sriraam Natarajan is a Professor and Director of the Center for Machine Learning and StaRLing Lab at The University of Texas at Dallas (UTD), part of the Erik Jonsson School of Engineering & Computer Science. He holds additional roles as a hessian.AI Fellow at TU Darmstadt and an RBCDSAI Distinguished Faculty Fellow at IIT Madras. His expertise spans Artificial Intelligence, Machine Learning, and their applications in healthcare, with a focus on Relational Learning, Reinforcement Learning, and Graphical Models. He has been honored as an AAAI Fellow (2025), elected to the AAAI Executive Council, and recognized with the UTD Outstanding Graduate Teaching Award. Education: Completed his PhD in Computer Science at Oregon State University in 2007 under Prof. Prasad Tadepalli. Postdoctoral work at the University of Wisconsin-Madison with Professors Jude Shavlik and David Page. Previously served as faculty at Indiana University and Wake Forest School of Medicine. Research: Active in developing AI systems for healthcare, including predictive models for gestational diabetes and cardiac arrest in children. His work emphasizes integrating human knowledge into machine learning (e.g., Human-in-the-Loop systems) and advancing statistical relational AI frameworks like Markov Logic Networks and Probabilistic Circuits. Publications: Over 100 peer-reviewed articles, including notable works on causal learning, relational reinforcement learning, and knowledge graph construction. Recent focuses include explainable AI and scalable probabilistic models. Awards: AAAI Fellow, RBCDSAI Distinguished Fellowship, UTD Teaching Excellence Award. Advising and Collaboration: Mentored over 30 students, many now in academia and top institutions like IBM Research, Facebook, and Microsoft. Collaborates globally on projects like GLAD (Glocalized Anomaly Detection) and StaRLing Lab initiatives. Labs/Teams: Leads the StaRLing Lab, focusing on statistical relational AI, and directs UTD's Center for Machine Learning. Engaged in interdisciplinary projects with healthcare, robotics, and data science communities.

• Machine Learning
• Reinforcement Learning
• Bandit Algorithms
• +5 more

Dr. Kevin G. Jamieson is a faculty member at the University of Washington , School of Computer Science , with prior affiliations at the University of California, Berkeley (Department of Electrical Engineering and Computer Sciences) and the University of Wisconsin-Madison (Department of Electrical and Computer Engineering). His work spans machine learning, reinforcement learning, bandit algorithms, and robotics. Current university: University of Washington Academic rank: Professor His research focuses on: Bandit algorithms and sequential decision-making Optimization in non-stationary environments Reinforcement learning with real-world applications Multi-agent systems and game theory Efficient data selection for multimodal learning Human-in-the-loop AI systems Recent publications highlight his expertise in pure exploration strategies, robotic manipulation, and bridging simulation-to-reality gaps in RL. He has mentored numerous collaborators, though formal student advising details are not explicitly listed here. No scientific awards are mentioned in the provided data.

Christian MessierView profile

Professor

• Forest Ecology
• Tree Resilience to Global Changes
• Urban Forestry
• +5 more

Christian Messier is a Professor at the University of Quebec in Outaouais (UQO) in the Department of Natural Sciences and at the University of Quebec in Montreal (UQAM) in the Department of Biological Sciences. He serves as Scientific Director of the Institute of Temperate Forest Sciences (ISFORT) and holds two prestigious research chairs: the Canada Research Chair on Tree Resilience to Global Changes and the NSERC/Hydro-Québec Chair on Tree Growth Control. His academic career spans over three decades since completing his Ph.D. in forest sciences from the University of British Columbia in 1991. Dr. Messier's research focuses on two primary areas: the complex functioning of managed natural forest systems to develop management approaches that promote resilience in the face of global changes, and the study of trees and urban forests to reconcile the needs of minimizing negative impacts of trees on human infrastructure while maximizing ecosystem services. His work integrates field studies, simulation modeling, and network theory to address pressing challenges in forest ecology and management. His recent publications demonstrate a strong emphasis on urban forest resilience, functional diversity in forest ecosystems, and nature-based solutions for climate adaptation. The research shows a clear trajectory toward more applied, solution-oriented approaches that bridge fundamental ecological understanding with practical forest management applications across diverse spatial scales from individual trees to entire landscapes. Francqui Foundation Chair (Belgium) - 2020 Member of The Royal Society of Canada - 2019 Personality of the Year 'Radio-Canada/Le Droit' - 2017 Humboldt Research Award - 2016 Prix Acfas – Michel-Jurdant - 2010 Canadian Forestry Scientific Achievement Award - 2006 Dr. Messier has supervised over 40 graduate students throughout his career and currently leads multiple major research projects including the Canada Research Chair on Forest Resilience, the NSERC/Hydro-Québec Chair on Tree Growth Control, and the SylvCIT project for urban forest immunization against global change. His research has been supported by significant grants from NSERC, Canada Research Chairs program, Hydro-Québec, and other major funding agencies. He directs the Messier lab with research assistants Kim Bannon and Fanny Maure, and collaborates with numerous researchers across Canada and internationally. His team studies diverse aspects of forest ecology including soil dynamics, functional composition of tree communities, nature-based solutions for climate adaptation, and ecophysiology of maple water flow. The lab maintains strong connections with the International Diversity Experiment Network with Trees (IDENT) and other major forest research initiatives.

• Economics of Law
• Public Economics
• Industrial Economics
• +3 more

Bruno Deffains serves as Professor of Economic Sciences at Paris-Panthéon-Assas University, where he directs the Master's program in Law and Economics, the Center for Research in Economics and Law (CRED), and the Digital Transformation of Law and Legaltech University Diploma. His academic leadership extends to the Yale-ESSEC-Paris 2 Summer School in Law and Economics and the Legal Security Index initiative. Affiliated with the Faculty of Law, he bridges economic theory with legal practice through extensive research and institutional engagement. Doctor of Economic Sciences (1991) Accreditation to Supervise Research (Habilitation à Diriger des Recherches, 1993) Deffains' research centers on the Economics of Law, examining how legal frameworks influence economic outcomes across diverse domains. His work in Public Economics investigates tax compliance and redistribution mechanisms, while Industrial Economics research analyzes competition policy and market regulation. Recent scholarship explores digital transformation's impact on legal practice, compliance systems, and the cognitive functions of law. He employs rigorous economic modeling to dissect liability rules, dispute resolution mechanisms, and the comparative performance of legal traditions, consistently linking theoretical insights to real-world policy challenges in antitrust, corruption, and judicial efficiency. His publication trajectory reveals deepening engagement with contemporary legal-economic intersections, evolving from foundational work on liability and legal origins toward cutting-edge analysis of digitalization and compliance. The consistent thread across his oeuvre is the application of microeconomic principles to institutional design, with increasing emphasis on behavioral dimensions and technological disruption in legal systems. Institut Universitaire de France Fellowship (2013) As academic director of the Law and Economics Master's program and CRED research center, Deffains oversees numerous doctoral theses and research initiatives. His role in the trilateral Summer School with Yale Law School and ESSEC cultivates international scholarly exchange, while leadership in the French Association of Law and Economics and European Association of Law and Economics demonstrates sustained commitment to field-building. External responsibilities include chairing the Commercial Practices Examination Commission and advising the National Consultative Commission on Human Rights, reflecting policy-relevant scholarship grounded in empirical economic analysis. Deffains leads the Center for Research in Economics and Law (CRED), a prominent research unit specializing in institutional analysis of legal systems. Through the Summer School in Law and Economics and Digital Transformation initiatives, he fosters interdisciplinary collaboration between economists, legal scholars, and practitioners. His directorship of the Legal Security Index project connects academic research with practical legal metrics development, while involvement with the Club des Juristes' digital pole positions him at the forefront of technology-law convergence debates.

• Simulation-Based Optimization
• Supply Chain Management
• Operations Management
• +4 more

Hamed Jalali is a Full Professor in Supply Chain Management at NEOMA Business School since September 2024, having joined the institution in September 2017. He holds a Master's degree in Statistics and a PhD in Business Economics from KU Leuven, Belgium. His research emphasizes simulation-based optimization, particularly Kriging-based algorithms, and explores intersections between marketing and operations management, as well as sustainable supply chain practices using game-theoretic models. His work has been published in journals like IIE Transactions , European Journal of Operational Research , and International Journal of Production Economics . Dr. Jalali has received numerous teaching awards at NEOMA Business School and collaborates with industries such as IMEC and EuroGijbels on projects like inventory management and rationing strategies. His research spans inventory dynamics, product portfolio management, blockchain applications in supply chains, and coopetition models in closed-loop systems. Education: PhD in Business Economics, KU Leuven, Belgium Master's degree in Statistics, KU Leuven, Belgium His recent articles highlight contributions to sustainable supply chain traceability, bullwhip effect mitigation through product portfolio adjustments, and multiobjective optimization algorithms. He actively reviews for top-tier journals and presents at international conferences. Key Awards: Multiple teaching excellence awards at NEOMA Business School. Industrial Projects: Collaboration with IMEC and EuroGijbels on inventory management and supply chain sustainability initiatives. His research integrates technical simulation methods with real-world supply chain challenges, emphasizing both operational efficiency and environmental sustainability.

Halefom AbrahaView profile

Assistant Professor

• Artificial Intelligence and Law
• Privacy and Data Protection
• European and International Law
• +5 more

Dr. Halefom Abraha is an Assistant Professor at the International and European Law (IER) Department of Utrecht University's School of Law. He specializes in Digital Human Rights, focusing on privacy, data protection, AI regulation, and algorithmic management in labor markets. His research addresses cross-border data access for law enforcement and digital sovereignty. Abraha holds a joint PhD from the University of Malta and Edith Cowan University (Australia) for his thesis on 'Cross-Border Data Access for Law Enforcement Purposes,' which earned the 2021 Dean's Award for Academic Excellence. He completed postdoctoral research at the Bonavero Institute of Human Rights, University of Oxford (2021-2024), and has advised the European Parliament’s LIBE Committee. His expertise spans EU and international law, with notable fellowships including Marie Sklodowska-Curie ITN (2017-2020) and AFRINIC (2017). Abraha is affiliated with the Netherlands Institute of Human Rights (SIM) and RENFORCE, focusing on governance challenges in the digital society. His research areas include the Future of Work under digital transformation, Security in Open Societies, and Contesting Governance paradigms. Key publications address workplace data protection frameworks, algorithmic management regulation, and cross-border data governance. Abraha advocates for contextualized legal solutions balancing innovation with human rights protections.

Michael BodeView profile

Professor

• Applied Mathematics
• Ecological Applications
• Conservation Biology
• +6 more

Michael Bode is a Professor in the School of Mathematical Sciences at Queensland University of Technology (QUT). His research focuses on applying mathematical and computational methods to ecological and conservation challenges, particularly in marine ecosystems and coral reef management. He holds a PhD in Applied Mathematics from the University of Queensland. Research Interests: Professor Bode specializes in larval dispersal modeling, conservation prioritization, and the application of ecosystem models to real-world management scenarios. His work integrates disciplines like applied mathematics, statistics, and ecology to address issues such as coral reef resilience, invasive species control, and climate change impacts. Grants & Projects: Securing Antarctica's Environmental Future (2020) Conserving Coral Reef Fish and Sustaining Fisheries in the Anthropocene (2019) Tackling Pests Using Game Theory (2019) New Methods for Conserving Dispersing Species on Coral Reefs (2017) Awards: 2020 Fenner Medal (Australian Academy of Science) Eureka Prize finalist (2020) Australian Research Council Future Fellowship (2017) Labs & Teams: He leads the QUT Applied Mathematical Ecology Group (QUTAMEG), which develops quantitative tools for ecological and conservation problems. His work is published in journals like Conservation Biology , Nature Sustainability , and PLoS Biology .

Bruno Castro da SilvaView profile

Assistant Professor

• Reinforcement Learning
• Artificial Intelligence
• Robotics
• +3 more

Bruno Castro da Silva is an Assistant Professor in the College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst. He holds a PhD in Computer Science from UMass Amherst (2014), and MSc and BSc degrees from the Federal University of Rio Grande do Sul (UFRGS), Brazil. Prior to UMass, he was an Associate Professor at UFRGS and a postdoctoral researcher at MIT's Aerospace Controls Laboratory. His research focuses on reinforcement learning (RL), robotics, and AI safety, aiming to develop algorithms that ensure safe and autonomous task decomposition while meeting user-specified safety criteria. Key areas include hierarchical policies, active learning, and biologically-plausible mechanisms. He has published in top venues like ICML, NeurIPS, and Science, and received awards such as the Best Paper at RLDM 2022 and Distinguished Reviewer distinctions. He teaches courses in reinforcement learning and machine learning at UMass, emphasizing accessibility and safety. His work also extends to fostering diversity in STEM education. He leads the Autonomous Learning Laboratory and collaborates with organizations like Adobe Research and the Laboratory of Computational Neuroscience in Rome.