Find Academic Supervisors

• Operations Management
• Business Statistics
• Queueing Theory
• +3 more

Taiwo Amoo is an Assistant Professor of Business and Quantitative Methods at Brooklyn College, CUNY , where he has been employed since 1999. His academic career spans institutions including Baruch College (substitute and adjunct roles, 1993-1999) and Kaduna Polytechnic, Nigeria (1987-1988). With a PhD in Operations Research (University of Exeter, 1992) and a BSc in Statistics (University of Ibadan, 1986), Amoo specializes in operations management, statistical analysis, and educational innovation. Current position: Assistant Professor (Brooklyn College, CUNY) Key expertise: Operations Management, Queueing Theory, Rating Scale Methodology Technological proficiency: SAS, SPSS, Oracle Database Systems His research focuses on optimizing rating scale design , integrating technology in education , and interdisciplinary approaches to business programs . Publications from 2000-2002 examine biases in survey construction, humor as an educational tool, and the relevance of traditional disciplinary structures in modern academia. Notable awards include PSC CUNY Grants and recognition as the Best Statistics Student at the University of Ibadan. Current affiliations: Brooklyn College (CUNY) Past affiliations: Baruch College (CUNY), University of Exeter, Kaduna Polytechnic

B. Pablo MontagnesView profile

Associate Professor

• Formal Political Theory
• Political Economy
• Public Policy Analysis
• +3 more

B. Pablo Montagnes is an Associate Professor of Political Science and Quantitative Theory and Methods at Emory University. He holds a Ph.D. in Managerial Economics and Strategy from the Kellogg School of Management, Northwestern University (2010). Before joining Emory in 2015, he was an Assistant Professor at the Harris School of Public Policy, University of Chicago. His research focuses on formal political theory and political economy, with a particular emphasis on strategic behavior in legislative settings, regulatory policy, and public opinion dynamics. Key topics include partisan approval rates, legislative bargaining, and the design of organizational and market mechanisms. Montagnes has published in leading journals such as the Journal of Politics , American Economic Review , and Proceedings of the National Academy of Sciences (PNAS) . Education: Ph.D. in Managerial Economics and Strategy, Kellogg School of Management, Northwestern University (2010) Previous Affiliation: Harris School of Public Policy, University of Chicago (Assistant Professor) Teaching: QTM 110 (Scientific Methods), QTM 315 (Game Theory) Montagnes’ work addresses questions like how regulatory uncertainty affects firm investment, the strategic implications of sequential voting in legislatures, and the reliability of survey-based partisan approval metrics. His recent projects explore polarization incentives, internal labor markets, and the role of lobbyists in policy gatekeeping. He currently holds an office at 311 Tarbutton Hall, Emory University, and can be contacted via email . No awards are explicitly listed in the provided materials.

Chuchu FanView profile

Associate Professor

• Formal Methods
• Control Theory
• Machine Learning
• +3 more

Chuchu Fan is the Leonardo Career Development Professor and Director of the REALM Lab (REliable Autonomous system Lab) at MIT's School of Engineering , with a primary appointment in the Department of Aeronautics and Astronautics and Laboratory for Information and Decision Systems . Her work bridges formal methods , control theory , and machine learning to ensure safety in autonomous systems. Ph.D., University of Illinois at Urbana-Champaign (2019) B.E., Tsinghua University (2013) Her research focuses on rigorous safety verification of autonomous systems through neural Lyapunov-barrier functions , control contraction metrics , and formal logic specifications . Recent work emphasizes LLM integration for symbolic planning, multi-robot collaboration , and robustness against model uncertainties . The 15 most recent articles highlight trends in safety-critical control using graph neural networks , reinforcement learning , and temporal logic . Key themes include collision avoidance , multi-agent coordination , and runtime safety filters applied to drones, self-driving cars, and microgrids. Scientific Awards & Honors : 2025 ONR YIP Award 2023 NSF CAREER & AFOSR YIP Awards 2020 ACM Doctoral Dissertation Award 2016 Rising Stars in EECS As head of the REALM Lab, she leads projects on autonomous air taxis , safety verification , and neural certificates for robotic systems. Her teaching includes courses on feedback control and formal methods for autonomous systems.

Hesham ElSawyView profile

Assistant Professor

• Wireless Networks
• Internet of Things (IoT)
• Federated Learning
• +3 more

Hesham ElSawy is an Assistant Professor in the Department of Systems and Networks at the School of Computing, Faculty of Arts and Science, Queen's University. His work focuses on advancing next-generation wireless systems, with particular emphasis on federated learning, IoT networks, and edge computing. He is affiliated with Ingenuity Labs Research Institute, Queen's University, and contributes to interdisciplinary research at the intersection of communication theory and network optimization. His research interests span stochastic geometry modeling, energy-efficient protocols for massive IoT deployments, and resilient federated learning frameworks. ElSawy explores novel paradigms in aerial wireless networks, UAV-assisted communication, and network security through percolation theory applications. Recent publications highlight his contributions to system-level analysis of parallel computing at extreme edges, UAV-enabled federated learning architectures, and energy-as-a-service models for RF-powered networks. His work emphasizes practical implementations and large-scale network validation. ElSawy holds no listed awards or grants in the provided text but maintains active collaborations through Ingenuity Labs. His research addresses critical challenges in 5G/6G networks, including latency optimization, resource allocation, and heterogeneous network integration.

• Heat Transfer
• Energy Storage
• Thermal Management
• +5 more

Ankur Jain is a Professor in the Mechanical and Aerospace Engineering Department at The University of Texas at Arlington, with a joint appointment in Bioengineering. His research focuses on heat transfer in Li-ion batteries, microscale thermal transport, bioheat transfer, and additive manufacturing. He holds leadership roles, including serving as Associate Editor for IEEE Transactions on Components, Packaging and Manufacturing Technologies and Secretary of the ASME Heat Transfer Division's K16 Committee. Education: Ph.D. (2007) and M.S. (2003) in Mechanical Engineering from Stanford University; B.Tech. (2001) in Mechanical Engineering from IIT Delhi with top honors. Research interests span energy conversion/storage, thermal management of electronics, and biomedical heat transfer applications. Notable achievements include the NSF CAREER Award (2016), ASME Fellow status (2022), and UTA President's Award for Excellence in Teaching (2022). His work has been supported by NSF, DOE, ONR, and Indo-US Science & Technology Forum. Advancing thermal runaway prevention in Li-ion batteries and improving additive manufacturing processes are key current focuses. Collaborations include industry partners like Underwriters Laboratories and Cuberg, Inc.

Ruth UrnerView profile

Associate Professor

• Machine Learning Theory
• Adversarial Robustness
• Algorithmic Fairness
• +4 more

Ruth Urner is an Associate Professor in the Department of Electrical Engineering and Computer Science at York University's Lassonde School of Engineering. She holds a PhD in Computer Science from the University of Waterloo (2013) and completed postdoctoral research at Max Planck Institute for Intelligent Systems (Germany), Carnegie Mellon University, and Georgia Tech. She was a Simons-Berkeley Fellow at the Simons Institute in 2017. Research Focus: Dr. Urner develops mathematical foundations for machine learning paradigms including semi-supervised/active learning, transfer learning, and adversarial robustness. Her current work addresses societal impacts of ML through interpretability and fairness frameworks. She leads projects on strategic classification, robust PAC learning, and calibrated model evaluation. Awards & Leadership: Simons-Berkeley Fellowship (2017) Best Paper Award at NIPS 2015 Workshop on Transfer Learning Organizer: Women in Machine Learning Theory workshops (COLT/ALT) Program Committee: NeurIPS, ICML, COLT, ICLR, AISTATS Teaching & Advising: She teaches Machine Learning Theory, Computational Logic, and Introduction to ML at York University. Current student advisees include Master's candidate Alireza Torabian. She has lectured at international summer schools including Hausdorff School on Algorithmic Data Analysis (Germany) and SMILES Summer School (Russia). Affiliations: Faculty affiliate at Vector Institute (Toronto) and collaborator with Max Planck Institute systems. Her lab investigates theoretical guarantees for learning algorithms under distribution shifts and adversarial conditions.

Zhen Ming JiangView profile

Associate Professor

• Software Engineering
• Artificial Intelligence
• Computer Systems
• +6 more

Zhen Ming (Jack) Jiang is an Associate Professor and York Research Chair (Tier II) in Software Engineering for Foundation Model-Powered Systems at York University's Department of Electrical Engineering and Computer Science. His research bridges software engineering, artificial intelligence, and computer systems with significant industrial impact. Dr. Jiang earned his Ph.D. from Queen's University's School of Computing and MMath/BMath degrees from the University of Waterloo's David R. Cheriton School of Computer Science. During his doctoral studies, he collaborated with BlackBerry's Performance Engineering team, developing tools now used daily to monitor commercial software systems. His research focuses on engineering rigor for AI-powered applications , software engineering evolution in the Generative AI era , and performance optimization of large-scale systems . Key areas include software performance engineering, mining software repositories, debugging distributed systems, source code analysis, and software visualization. His work combines empirical studies with practical tool development. Recent publications reveal strong trends in applying AI to software engineering challenges, particularly in machine learning systems reliability, blockchain efficiency, and AIOps solutions. His research consistently emphasizes empirical validation using real-world systems and industrial case studies. Scientific recognition includes: York Research Chair (Tier II) in Software Engineering for Foundation Model-Powered Systems NSERC Discovery Accelerator Supplements (DAS), 2020 Best Paper Award at ICST 2016 IEEE Software Best SEIP Paper at ICSE 2015 Ph.D. Research Achievement Award at Queen's University Multiple best paper awards at WCRE, MSR, and ICSE Dr. Jiang actively supervises graduate students and has secured competitive research funding including NSERC grants. His service includes program committee roles for top conferences (ICSE, ASE, ICSME) and editorial work for leading journals (TSE, TOSEM, EMSE). He leads research initiatives focused on foundation model-powered systems, collaborating with industry partners on performance monitoring and debugging solutions for large-scale distributed environments.

Michael BurkeView profile

Professor

• Organizational Behavior
• Occupational Safety
• Workplace Safety
• +4 more

Michael Burke is a Professor and Earl P. and Ethel B. Koerner Chair in Strategy and Entrepreneurship at Tulane University’s A. B. Freeman School of Business. He holds affiliations with the Stone Center for Latin American Studies and serves as Chair of Tulane’s Social-Behavioral Institutional Review Board. His academic journey includes roles at New York University (1985–1991) and visiting professorships at the University of Sheffield (2004). Education: Ph.D. in Psychology (Illinois Institute of Technology, 1982), M.S. in Industrial Psychology (Purdue University, 1980), and B.A. in Psychology (University of Notre Dame, 1977). Burke’s research focuses on Organizational Behavior and Occupational Safety , with emphasis on teamwork effectiveness, safety training, and interrater agreement methodologies. His work spans cross-cultural studies (e.g., Peru, Colombia, Mexico) and integrates psychological principles with practical workplace applications. Key contributions include over 60 publications, including seminal articles on safety training efficacy, meta-analytic methods, and climate assessment. His awards include the 2023 Tulane Convergence Award for interdisciplinary collaboration and multiple Dean’s Excellence Awards (2014–2017). He has supervised 2 dissertations/theses in recent years and actively contributes to academic governance, serving as Editor of Personnel Psychology (2007–2010) and on editorial boards for major journals. Burke’s international experience includes collaborations in Latin America, Australia, and Europe, leveraging his fluency in French.

Suresh KhatorView profile

Professor

• Modeling of Energy Systems
• Health Care Systems
• Manufacturing Systems
• +3 more

Suresh Khator is a Professor and Senior Associate Dean for Graduate Programs and Computing Facilities at the University of Houston's Cullen College of Engineering, Department of Industrial and Systems Engineering. He holds a Ph.D. in Industrial Engineering from Purdue University and has extensive experience in academia, industry, and administrative roles. His research focuses on modeling energy, healthcare, and manufacturing systems, facilities design, production planning, and project management. He has supervised 10 PhD dissertations and 37 Master's theses, and his work has been published in top-tier journals and conferences. Khator has received numerous awards, including the Fellow of IISE and multiple teaching excellence awards. His administrative roles include Director of Engineering Computing and Interim Associate Dean at the University of South Florida. He has also contributed to community initiatives, such as science fairs and outreach programs. His articles span power systems resilience, renewable energy integration, and manufacturing automation. He has led over 30 grants and contracts, including projects with the Florida Department of Transportation and utility companies.

• Technology Innovation
• Strategy and Entrepreneurship
• Collaboration, Competition & Cognition
• +7 more

Dr. Anindya Ghosh is an Associate Professor at Tilburg University’s Tilburg School of Economics and Management (TiSEM), specifically in the Department of Strategy and Entrepreneurship. His research focuses on Technology Innovation, Strategy and Entrepreneurship, Collaboration, Competition & Cognition, and Applied Machine Learning, with industry expertise in Imaging, Semiconductors, Wireless, Pharmaceuticals, AI, and Venture Capital. He holds a PhD from the Wharton School (2011) and has held academic roles at the Indian School of Business (2015–2018) and IESE Business School (2011–2015). His work explores themes such as technology sourcing dynamics, ecosystem governance via standards-setting, and alliance management. Recent studies address how firms navigate external technology sourcing preferences, shape ecosystem rules through complementarities, and resolve conflicts during multi-firm coordination. He has also contributed to debates on generalizability of archival-based research findings in strategic management. His research employs mixed methods, including computational analysis of standards-setting interactions and longitudinal alliance data. While no formal grants or labs are listed, his affiliations with TiSEM and collaborations with institutions like the Indian Institute of Technology underscore his interdisciplinary reach.

Sylvia WalbyView profile

Professor

• Violence and Society
• Gender-Based Violence
• Trafficking in Human Beings
• +4 more

Professor Sylvia Walby is a faculty member at Royal Holloway, University of London, within the Department of Law and Criminology, School of Law and Social Sciences. She holds the Alexander von Humboldt Foundation Anneliese Maier Research Award, hosted by the University of Duisburg-Essen (2018–2025), and has held visiting positions at institutions including UCLA and Harvard. Current research focuses on violence and society, including gender dimensions, trafficking, and complex systems theory. Her work contributes to Sustainable Development Goals (SDGs), particularly those addressing gender equality and reduced inequalities. Key publications include Trafficking Chains: Modern Slavery in Society (2024) and methodological contributions to violence measurement. Her research spans criminology, sociology, and gender studies, emphasizing policy engagement and data-driven approaches. Recent articles analyze violent crime trends, trafficking data integration, and violence measurement in crime surveys. These works highlight intersections of gender, policy, and statistical methodologies. Scientific awards include Fellowships from the British Academy and Academy of Social Sciences, an OBE, and an honorary doctorate from Queen’s University Belfast. She has served as Chair of the REF2021 Sociology Sub-Panel and held leadership roles in the International Sociological Association and European Sociological Association.

• Optical Networking
• High-Speed Networks
• Data Center Technologies
• +6 more

Emmanouel (Manos) Varvarigos is a Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), where he leads the High Speed Communication Networks Laboratory. He holds a Diploma from NTUA (1988) and an M.S./Ph.D. from MIT (1990/1992). Prior roles include Professorships at UC Santa Barbara (1992-1998) and Delft University (1998-1999), and leadership at the University of Patras (1999-2015). He has coordinated over 30 EU research projects, including H2020 initiatives like ORCHESTRA and FLEXGRID. His research focuses on optical networking, cloud computing, smart energy grids, and high-speed network protocols. He has published over 450 papers and serves on numerous conference committees. Awards include the NSF Research Initiation Award. His lab employs 5 postdocs and 10+ PhD students, addressing challenges in networking, data centers, and grid computing. Education: Ph.D., Electrical Engineering and Computer Science, MIT, 1992 M.S., Electrical Engineering and Computer Science, MIT, 1990 Diploma in Electrical and Computer Engineering, NTUA, 1988 Research Interests: Optical networking, high-speed network protocols, data center architectures, cloud computing, smart energy grids, wireless networks, and distributed systems. Grants & Projects: Coordinated 7 EU projects (e.g., FLEXGRID, ORCHESTRA) and participated in 35+ others. National projects include roles as Scientific Director of the Greek School Network and CTI’s Network Technologies Division. Labs & Teams: Directs the High Speed Communication Networks Lab (HSCNL), collaborating with global institutions on optical networks, edge cloud, and smart grids. The lab’s work includes EU-funded projects on 5G, data centers, and renewable energy integration.

Simon RowlandView profile

Professor

• Electrical Insulation Materials
• Polymeric Insulation Systems
• Asset Management for Power Systems
• +4 more

Simon Rowland is a Professor of Electrical Materials at the University of Manchester's Department of Electrical and Electronic Engineering, affiliated with the High Voltage Group. He previously served as Head of School (2015-2019) and transitioned from industrial R&D roles at STC, BICC, and Corning Cables to academia in 2003. His expertise centers on electrical insulation materials, polymeric systems, and asset management for power systems. He leads research in the UK’s largest HV laboratory, focusing on solid insulation interfaces and funded by National Grid and EPSRC. He holds 13 patents, primarily in overhead line technology, and is a Fellow of the IEEE and IET. Education: BSc, PhD, FHEA, FIET, FIEEE. Research interests include dielectric reliability, overhead line design, and low-current arcs. Collaborations span materials science and engineering disciplines. Recent awards include the 2025 IEEE Eric O. Forster Distinguished Service Award and 2022 Bhattacharyya Award Finalist. Professional roles include Treasurer of the IEEE Dielectrics and Electrical Insulation Society (2020–present).

Paul QuirkView profile

Professor

• Democratic theory and practice
• Legislative and judicial politics
• Experimental methods
• +4 more

Paul J. Quirk is the Phil Lind Chair in U.S. Politics and Representation at the University of British Columbia's Department of Political Science (Faculty of Arts). He holds a Ph.D. from Harvard University (1978) and has taught at multiple U.S. institutions before joining UBC in 2004. His research focuses on democratic theory, legislative and judicial politics, experimental methods, public opinion dynamics, and U.S. public policy. Quirk's academic career includes roles as a Brookings Institution research associate and editorial board membership in major political science journals. His award-winning works include Industry Influence in Federal Regulatory Agencies (1981) and The Politics of Deregulation (1985). Recent publications address deliberative democracy, presidential competence, and comparative democratic systems between the U.S. and Canada. Education: Ph.D. in Political Science, Harvard University (1978) Affiliations: U.S. Studies Program at UBC, Chair of U.S. Politics Area Committee Research Themes: Congress-executive relations, regulatory policy, polarization effects, deliberative institutional frameworks His awards include the Louis Brownlow Book Award (2005) and the Aaron Wildavsky Enduring Achievement Award (2010). Quirk's work bridges empirical analysis with institutional theory, emphasizing how information and advice shape policymaking processes.

• Medical Imaging
• Artificial Intelligence
• Machine Learning
• +7 more

Dr. Neal Bangerter is a Visiting Professor in the Department of Bioengineering at Imperial College London's Faculty of Engineering. He specializes in medical imaging (MRI), artificial intelligence, machine learning, and signal processing. Dr. Bangerter holds adjunct appointments at INSEAD, the University of Utah, and Brigham Young University. His research focuses on ultra-high field MRI, AI applications in healthcare, and data-driven bioscience technologies. He leads the London Collaborative Ultra-High Field Scanner (LOCUS) project and advises companies on AI and innovation strategies. Education: B.S. in Physics (UC Berkeley), M.S. and Ph.D. in Electrical Engineering (Stanford University). Career highlights include roles at McKinsey & Company, Microsoft, and Reactrix, as well as founding BYU's Medical Imaging Research Center. He has pioneered cross-faculty initiatives like the Crocker Innovation Fellowship Program. Research interests include novel MRI pulse sequences, AI in medical imaging, and large-scale health data analysis. His work spans collaborations with Stanford, Oxford, Cambridge, and Siemens Healthcare. He teaches executive education at INSEAD, focusing on bridging technical concepts with business strategies. Key awards include the David Evans Chair at Brigham Young University. His contributions to the UK Biobank Neuroimaging study and development of MRI techniques like RAFO-4 highlight his impact on advancing imaging technologies and AI applications in healthcare.