Find Academic Supervisors

Ramesh JohariView profile

Professor

• Online Platforms Design
• Economic Analysis
• Machine Learning
• +3 more

Ramesh Johari is a Professor of Management Science and Engineering and Professor (by courtesy) of Electrical Engineering at Stanford University. He holds affiliations with the Institute for Human-Centered Artificial Intelligence (HAI), Precourt Institute for Energy, and the Institute for Computational and Mathematical Engineering (ICME). As Associate Director of Stanford Data Science and Co-Director of the Stanford Causal Science Center, he leads initiatives in data-driven research and causal inference. His research focuses on online platforms, statistical/machine learning, and healthcare technology, with contributions to diabetes care optimization and algorithmic decision-making. Education: PhD in Electrical Engineering and Computer Science from MIT (2004). His work integrates economics, operations research, and computer science to address challenges in platform design and healthcare systems. Notable achievements include developing the Timely Interventions for Diabetes Excellence (TIDE) platform, improving outcomes for type 1 diabetes patients through remote monitoring and algorithmic prioritization. Key research areas include: design of digital health platforms, economic analysis of online markets, and scalable healthcare solutions. His recent studies emphasize equitable access to CGM technology and precision medicine in diabetes care. Scientific Awards: Over 11 honors, including the George E. Nicholson Student Paper Competition (2003), ACM Doctoral Dissertation Award (2004), and NSF CAREER Award (2007). Advising: Mentors doctoral and master’s students in healthcare technology, data science, and operations research. Serves on editorial boards and program committees for top conferences in his field. Current roles include partial leave from January 2025 to June 2025. Labs/Teams: Active in the Society and Algorithms Lab (SOAL) and collaborates with Stanford’s interdisciplinary healthcare initiatives. His work bridges academic research and real-world applications in technology and medicine.

• Geometric Data Processing
• Optimal Transport
• 3D Shape Analysis
• +6 more

Justin Solomon is an Associate Professor in the Department of Electrical Engineering and Computer Science at MIT, leading the Geometric Data Processing Group within CSAIL. His research focuses on applying geometric principles to solve challenges in computer graphics, medical imaging, autonomous systems, and political redistricting. He earned his PhD from Stanford University and completed postdoctoral research at Princeton’s Program in Applied and Computational Mathematics. His work bridges theoretical foundations with practical tools, such as optimal transport and machine learning, to advance shape analysis and data-driven geometry. Education: PhD in Computer Science, Stanford University Postdoctoral Research, Princeton University Research Interests: Applied geometry, optimal transport, 3D shape analysis, machine learning for geometry, computational topology, and interdisciplinary applications like autonomous driving and political redistricting fairness. His group develops methods for robust processing of geometric data across domains, from medical imaging to manufacturing. Projects: Political Geometry: Using geometric algorithms to combat gerrymandering and ensure fair redistricting. Geometric Data Processing Group: Expanding geometric tools for 3D modeling, autonomous systems, and data analysis. Optimal Transport: Bridging theory and practice for statistical and machine learning applications. Labs/Teams: CSAIL’s Geometric Data Processing Group and collaborations with the MIT Center for Computational Science and Engineering (CCSE).

Matissa HollisterView profile

Assistant Professor

• Career Management
• Changing Nature of Work & Retirement
• Comparative Labour & Industrial Policies
• +8 more

Matissa Hollister serves as Assistant Professor (Teaching) in Organizational Behaviour at McGill University's Desautels Faculty of Management, concurrently holding the role of Social Initiative Coordinator. Her scholarly work addresses critical transformations in contemporary work structures and labor markets. PhD in Sociology and Social Policy, Harvard University, USA Master in City Planning, Massachusetts Institute of Technology, USA BA in Urban Studies, Architecture, and Urban Planning, USA institution Hollister's research program centers on employment instability and job tenure dynamics across North American and European labor markets, with growing emphasis on AI's impact on human resources . Her investigations into work-family intersections reveal gendered consequences of economic restructuring, while studies of comparative labor policies highlight institutional responses to rising job insecurity. Recent work develops ethical frameworks for data-driven hiring practices , emphasizing human-centered design in algorithmic management systems. Analysis of her publication trajectory shows consistent methodological rigor in longitudinal labor market analysis since 2004, with notable pivot toward technology-impacted work after 2017. Her cross-national studies (Canada, US, UK, Germany) demonstrate how economic restructuring fragments career pathways while exposing demographic disparities in job security. Key recognitions include: McGill University AI Fellow, World Economic Forum Centre for Fourth Industrial Revolution (2019-2021) Visiting Scholar, Stanford Center for Poverty and Inequality (2010) Center for Advanced Study in Behavioral Sciences Fellowship (2006) National Science Foundation Doctoral Fellowship (1999-2005) Hollister leads significant research initiatives including an SSHRC-funded investigation into job mobility consequences (2018-2022) and Russell Sage Foundation-supported methodology development for measuring job instability (2017-2019). She actively shapes policy through U.S. Equal Employment Opportunity Commission consultations and co-chairs the Responsible AI Certification Standards HR Working Group, while delivering executive education on AI ethics through McGill's Executive Institute. Her institutional engagement spans McGill's Sustainable Growth Initiative and Marcel Desautels Institute for Integrated Management, where she connects academic research to practical workplace solutions through the Dobson Centre for Entrepreneurship.

Florian MadisonView profile

Assistant Professor

• Game Theory
• Macroeconomics
• Money and Finance
• +5 more

Florian Madison is an Assistant Professor of Economics at the Robert Day School of Economics and Finance . He joined the institution in 2019 following postdoctoral studies at the University of California, Irvine and the Federal Reserve Bank of St. Louis. He holds a Ph.D. in Economics from the University of Basel. Education: Ph.D. in Economics, University of Basel Postdoctoral Research: University of California, Irvine and Federal Reserve Bank of St. Louis Research Interests: Dr. Madison focuses on Game Theory , Macroeconomics , and Money and Finance , with expertise in markets with frictions, search and matching, asset pricing, liquidity, and asymmetric information. His work bridges theoretical and applied economics, examining how information asymmetries and market imperfections shape economic outcomes. Recent Publications: His 2024 articles explore currency substitution policies and liquidity dynamics in frictional markets. Earlier work includes analyses of entrepreneurial finance and the European sovereign debt crisis. His 2017 doctoral dissertation advanced theories on monetary liquidity. Grants & Advising: No specific grants or advisees are listed, though his research collaborations are evident in co-authored works like the 2022 paper on entrepreneurial finance.

Jurui ZhangView profile

Associate Professor

• Marketing Modeling
• Social Network Analysis
• Social Media Analytics
• +3 more

Jurui Zhang is an Associate Professor in the Department of Marketing at the University of Massachusetts Boston. His research focuses on marketing modeling, social networks, and social media analytics, with an emphasis on understanding consumer behavior through digital platforms. He explores topics such as music popularity dynamics, linguistic coordination in reviews, and the impact of social media on brand advocacy. His work integrates methodologies like machine learning, text mining, and network analysis to address contemporary challenges in marketing and consumer research. Notable areas of exploration include the role of shape-taste congruence in product evaluation, the effects of reviewer social networks on online reviews, and the analysis of Airbnb review topics influencing listing performance. Zhang’s research demonstrates a strong focus on leveraging data-driven approaches to uncover insights into consumer decision-making processes and digital product success. His findings contribute to both academic discourse and practical strategies for businesses operating in the digital economy.

David HembryView profile

Assistant Professor

• Evolutionary Biology
• Ecology
• Plant-Insect Interactions
• +4 more

David Hembry is an Assistant Professor in the Department of Biology at James Madison University, joining in 2024. He holds a PhD in Environmental Science, Policy, and Management from UC Berkeley (2012) and a BA in Biology from Harvard University (2003). His research focuses on the evolution and ecology of species interactions, particularly mutualistic and parasitic associations between leafflower plants (Phyllanthaceae) and leafflower moths (Lepidoptera: Gracillariidae: Epicephala). His work spans tropical and temperate regions, including active field projects in Texas, Puerto Rico, Asia, and the Pacific Islands. He is supported by NSF and JMU funding, and his lab emphasizes phylogenetic approaches, species interaction networks, and coevolutionary dynamics. Education: PhD, Environmental Science, UC Berkeley, 2012 BA, Biology, Harvard University, 2003 Research Interests: Dr. Hembry investigates how ecological interactions drive evolutionary processes and biodiversity. His lab’s model system explores the coevolutionary history of leafflower plants and their specialist moths, addressing questions about mutualism stability, host shifts, and biogeographic patterns. Key themes include: Coevolutionary mechanisms shaping species diversification Biogeographic dynamics of island ecosystems Phylogenetic methods to disentangle ecological interaction histories Recent Research Trends: His publications highlight coevolutionary dynamics, the macroevolutionary impacts of species interactions, and the role of ecological networks in biodiversity maintenance. Recent work emphasizes cryptic pollinator systems and the evolutionary consequences of mutualism-parasitism transitions. Grants & Funding: NSF grants supporting fieldwork in the Pacific Islands and Neotropics JMU internal funding for lab establishment and student training Labs & Collaborations: The Hembry Lab collaborates with researchers globally on island biogeography, phylogenetics, and coevolution. Key partners include James Ackerman, Ulrich Mueller, and Elvia Meléndez-Ackerman. The lab currently offers MS positions in evolutionary ecology and biogeography.

Kathryn LeonardView profile

Professor

• Computer Science
• Computer Vision
• Data Analysis
• +6 more

Kathryn Leonard is the Interim Vice President for Academic Affairs and Dean of the College at Occidental College, as well as a Professor in the Department of Computer Science. She holds degrees from the University of New Mexico (B.S.), and Brown University (M.S., Ph.D.). Her research focuses on geometric models for computer graphics, vision, and data analysis, emphasizing explainability. She promotes undergraduate research through initiatives like the Center for Undergraduate Research in Mathematics, funded by a $1.4M NSF grant. Leonard also champions diversity in STEM, leading the Association for Women in Mathematics (AWM) and organizing global conferences to support women in computational sciences. Her educational background combines mathematics and English, enabling interdisciplinary approaches to computer science. Notable contributions include developing robust skeletonization algorithms for 3D shapes, shape complexity metrics, and applications in medical diagnosis. She has advised students advancing to top tech companies and PhD programs. Awards include the Best Paper Award (2013) and leadership roles in organizations like the Mathematical Association of America and Council on Undergraduate Research. Leonard’s work bridges computational theory and practical impact, with over 30 publications spanning shape modeling, data analysis, and education. She directs research teams and collaborates internationally on projects like the SkelNetOn Challenge, advancing geometric understanding through AI and deep learning.

Steve SmithView profile

Senior Lecturer

• Sport Performance Psychology
• Deliberate Practice Environments
• Athlete Development
• +3 more

Dr. Steve Smith is a Senior Lecturer in Sport Coaching and Psychology at the University of Winchester. He holds a PhD from the same institution, focusing on psychological influences in practice environments, alongside a sports therapy undergraduate degree from the University of Chichester and an MProf from Solent University. He is a Qualified Teacher Learning and Skills (QTLS) holder with extensive teaching experience across various educational domains. His research emphasizes sport performance psychology, particularly the role of coaches in shaping deliberate practice environments for athlete development. Practical expertise includes international badminton competition/coaching and grassroots football coaching. Key areas of study involve soccer tactics, badminton biomechanics, and optimizing practice-to-competition transitions. Recent publications (2019-2025) analyze youth football scanning patterns, badminton landing mechanics, and practice environment models using mixed-methods approaches. Collaborations with sports organizations inform his work, though no major awards are listed. He advises on curriculum development and has pioneered action research methodologies for coaching practice assessment.

Brittany BondView profile

Assistant Professor

• Organizational Behavior
• Organizational Theory
• Economic Sociology
• +5 more

Brittany Bond is an Assistant Professor of Organizational Behavior at Cornell University's Industrial and Labor Relations (ILR) School. As an organizational theorist and economic sociologist, she investigates how status recognition influences labor market outcomes, with specific focus on how personnel management systems shape careers and impact firm performance. Her research has been published in top journals including Organization Science and Sociological Science, and has been featured by the US Census Bureau's Research Matters Blog and Wharton Business Radio. Bond earned her PhD from MIT Sloan's Economic Sociology Program in May 2020. Prior to her doctoral studies, she worked as an economist in the Office of the Chief Economist of the US Commerce Department, with a detail at the U.S. Census Bureau's Center for Economic Studies. She holds an MS in Public Policy and Management from Carnegie Mellon University's Heinz College and a BA in International Economic Relations from American University in Washington DC. Her research examines the consequences of 'status recognition mismatch,' focusing on discrepancies between professionals' status and performance. Bond studies how talent recruitment systems, performance management practices, and recognition mechanisms shape career trajectories and organizational effectiveness. Her work has significant implications for strategic talent management in competitive environments, particularly regarding how organizations can retain high-performing employees through appropriate recognition systems. Bond's publication record reveals a consistent theme examining recognition systems within organizations and their behavioral consequences. Her work spans forced ranking systems, specialist performance dynamics, referral networks, and the psychological impacts of recognition mismatch. She employs innovative methodologies combining archival data with experimental approaches, as evidenced by her research using Major League Baseball data to study specialist performance and internal Census Bureau data for labor market analysis. Bond has received significant recognition for her scholarly contributions: William H. Newman All-Academy Award for Best Paper Based on a Dissertation (2020) Louis R. Pondy Best Dissertation Paper, Organization and Management Theory Division of the Academy of Management (2020) Finalist, INFORMS/Organization Science Best Dissertation Proposal Competition (2019) Bond teaches courses on power and influence at multiple levels. Her graduate course ILROB 5260, 'Being Effective: Power and Influence,' provides students with tools for understanding organizational power dynamics. She also teaches ILROB 3260, 'Power and Influence: Building Power from Nothing,' for undergraduates, and the Macro OB PhD Seminar (ILROB 7220). Previously at MIT Sloan, she taught 'People, Teams, and Organizations' as a course section instructor. Her current research portfolio includes investigations into overrecognition effects, platform changes and evaluative behavior, gender differences in internal job applications, burnout interventions for veterinarians, and the trickle effects of HR implementation. Bond collaborates across disciplines to examine complex organizational phenomena, often bridging sociology, management, and economics perspectives.

• Pharmaceutical Policy
• Medication Adherence
• Healthcare Quality Improvement
• +5 more

Richard Segal, Ph.D., is a Professor in the Department of Pharmaceutical Outcomes & Policy at the University of Florida College of Pharmacy, with a joint appointment in the Department of Pharmacotherapy and Translational Research. His research focuses on improving medication use safety and quality, particularly through optimizing prescribing practices and collaborative healthcare models. A renowned leader in pharmacy education, he has received numerous teaching awards including the 2024 Faculty Teaching Excellence Award and the 2021 University of Florida Teacher of the Year. His contributions span over 200 peer-reviewed publications and include seminal work on Therapeutic Outcomes Monitoring (TOM), a pharmacist-led intervention to reduce drug-related issues. Key research areas include medication adherence in marginalized populations, healthcare quality improvement, and health equity in diabetes and chronic disease management. Dr. Segal has led and co-investigated over 30 grants, including major initiatives like the Florida-California Cancer Equity Center and studies funded by the NIH and CDC. He teaches advanced research and clinical pharmacy courses, mentoring students in pharmaceutical outcomes and policy. His accolades include the 2011-2016 American Managed Care Pharmacy Crisafi Endowed Chair and the 2001 Blue Cross Blue Shield Research Mentorship Award. His work has shaped national medication therapy management practices and policy.

Lisa EhrlingerView profile

Researcher

• Data quality
• Knowledge graphs
• Ontologies
• +5 more

Lisa Ehrlinger is a Senior Researcher at the Information Systems Research Group within the Digital Engineering Faculty of the University of Potsdam. She holds a PhD in Engineering Sciences ("passed with distinction") and an MSc in Computer Science from Johannes Kepler University Linz (JKU), both with distinction. Her work bridges academic research and industrial application. Her research focuses on Data Quality , Knowledge Graphs , Ontologies , Semantic Technology , Data Catalogs , and Data Integration , particularly with NoSQL databases. She has over 7 years of applied research experience at the Software Competence Center Hagenberg GmbH (SCCH), including project management and team leadership. Her recent publications emphasize SHACL validation , Data Stream Pollution , Dashboard Design , and Ontology-Driven Analysis , reflecting trends in data quality automation , semantic modeling , and industrial data governance . She co-chaired the Quality of Databases (QDB) workshop (2023, 2024) and serves on the MIT CDOIQ Symposium review board (since 2023). Her outreach includes lecturing at JKU and reviewing for journals like ACM Journal of Data and Information Quality (JDIQ) and Elsevier Journal of Information Fusion .

• Human Cognitive Evolution
• Decision-Making Under Risk
• Evolutionary Psychology
• +3 more

Andreas Wilke is a Professor in the Department of Psychology at Clarkson University, affiliated with the Lewis School of Health & Life Sciences. His research focuses on the evolutionary basis of human decision-making, particularly under conditions of risk and uncertainty. He holds a Ph.D. in Psychology from the Free University of Berlin and has conducted postdoctoral research at institutions including UCLA and the Konrad Lorenz Institute. Wilke's work integrates cognitive psychology with evolutionary biology, exploring topics such as foraging behavior, risk perception, and the 'hot hand' fallacy. He has secured grants from the National Science Foundation and Clarkson University, and his research has been presented at conferences like the Human Behavior and Evolution Society meetings. Education: Ph.D. in Psychology (2006) and M.A. in Psychology (2002), Free University of Berlin. Key Research Interests: Evolution of decision-making under uncertainty, foraging strategies, cognitive biases, and cross-cultural studies. Grants: NSF Grant SES-2116145 (2021–2023), multiple Clarkson University awards for research on randomness perception and statistical thinking. Wilke’s research emphasizes interdisciplinary collaboration, linking psychological findings to anthropology and ecology. His lab examines how evolutionary pressures shape cognitive mechanisms, including studies using virtual reality to simulate foraging scenarios. Recent work investigates children’s understanding of randomness and spatial reasoning, highlighting developmental perspectives.

Longin Jan LateckiView profile

Professor

• Computer Vision
• Medical Imaging
• Digital Geometry and Topology
• +6 more

Dr. Longin Jan Latecki is a Professor in the Department of Computer and Information Sciences at Temple University. His research focuses on computer vision, medical imaging, digital geometry, and artificial intelligence. He has held editorial roles, including Associate Editor-in-Chief of Pattern Recognition and roles on the editorial boards of Computer Vision and Image Understanding and Journal of Imaging . He has organized events like the Asian Conference on Pattern Recognition and chaired the PhD Track in Artificial Intelligence. His research spans topics such as shape-based object detection, video mining, and robot mapping. Notable projects include the Shape-Based Image Search Engine and work on Well-Composed 3D Images . He has authored over 300 publications and advised numerous PhD students in areas like medical imaging, computer vision, and data mining. Dr. Latecki has collaborated on projects such as ClimatePub4KG for climate modeling and SciDMT for scientific mention detection. His work emphasizes practical applications, including dental imaging analysis, autonomous robotics, and multimedia transmission optimization. He teaches courses like Mathematical Concepts in Computing and Artificial Intelligence .

Ryan EllerView profile

Senior Lecturer

• Genetics
• Genomics
• Computational Biology
• +6 more

Ryan Eller is a Senior Lecturer in the Department of Biology, Forensic & Investigative Sciences at Indiana University. He holds a Ph.D. in Genetics from Purdue University (IUPUI) and a B.S. in Biology from Butler University. His research focuses on utilizing computational tools to extract and analyze genetic information from human DNA. His primary research interests include Genetics/Genomics, Computational Biology and Bioinformatics, Artificial Intelligence, and Statistics. Eller's work explores how DNA stores information about ancestral histories, disease susceptibility, and human phenotypes, with applications spanning from medical fields to forensics to population genetics. Analysis of his recent publications reveals a strong focus on the genetic architecture of human facial features through genome-wide association studies (GWAS). His research spans multiple populations and examines various aspects of craniofacial morphology, including eyebrow thickness, eyebrow color, cranial vault shape, and the relationship between face and brain shape. His computational approach is evident in his development of analytical pipelines for genomic data. Eller actively seeks students interested in genetics, computational biology, bioinformatics, machine learning, and programming (Python, R) for research opportunities, noting that all his work is computational in nature rather than wet lab research.

Greg AloupisView profile

Professor

• Computational Geometry
• Algorithms
• Robotics
• +4 more

Greg Aloupis is an Industry Professor in the Department of Computer Science and Engineering at New York University's Tandon School of Engineering. He holds a Ph.D. from McGill University (2005), with postdoctoral research at Carleton University (Canada), Université Libre de Bruxelles (Belgium), and Academia Sinica (Taiwan). He served as a Visiting Assistant/Associate Professor at Tufts University from 2013 to 2017. His research focuses on computational geometry, algorithms, robotics, and theoretical computer science, with notable contributions to reconfigurable robotics, geometric algorithms, and data depth analysis. Education: Ph.D. in Computer Science, McGill University, 2005 Postdoctoral research at Carleton University, ULB, and Academia Sinica His research interests include computational geometry applications in robotics, modular robot reconfiguration, geometric transformations, and algorithmic game theory. Over 50 publications in top venues such as Computational Geometry: Theory and Applications, Discrete & Computational Geometry, and Theoretical Computer Science. Courses taught include undergraduate and graduate algorithms courses (CS-2413, CS-6033) and discrete mathematics.