جست‌وجوی استاد و پژوهشگر

Simon Deakinمشاهده پروفایل

استاد

• Tort Law
• Contract Law
• Labour Law
• +۷ مورد دیگر

Professor Simon Deakin is a Fellow and Director of Studies in Law at Peterhouse, University of Cambridge, specializing in private law (tort and contract law) and labour law. He teaches on the undergraduate Law Tripos and the LLM programme, with research focusing on law and economics, artificial intelligence, and historical legal analysis. Current research on Is Law Computable? and AI ethics Co-editor of computational law essay collection Developed Cambridge Leximetric Database for quantitative legal analysis His research spans tort law, corporate governance, digital economy regulation, and sustainability. Recent work explores the Anthropocene's legal implications and labour law's computational approaches. Scientific awards include the Cambridge Students' Union teaching prize (2023) He supervises doctoral students annually and contributes to legal education through widely used textbooks. As a Centre for Business Research (CBR) affiliate, he advances data-driven analysis of global labour regulation.

Jeremy J. Michalekمشاهده پروفایل

استاد

• Vehicle Electrification
• Life Cycle Assessment
• Consumer Behavior
• +۱۲ مورد دیگر

Jeremy J. Michalek is a Professor of Mechanical Engineering and Engineering and Public Policy at Carnegie Mellon University. He serves as Director of the Design Decisions Laboratory and co-Director of the Vehicle Electrification Group, with affiliations in multiple sustainability-focused institutes including the Center for Climate and Energy Decision-Making. Education: Ph.D. in Mechanical Engineering (University of Michigan, 2005) Research spans vehicle electrification , life cycle analysis , consumer behavior , and green design . His recent publications focus on battery economics, charging infrastructure impacts, and equity considerations in transportation technologies. Key awards include the NSF CAREER Award , ASME Best Paper Award , and George Tallman Ladd Research Award . Michalek's work has been featured in major media outlets including The New York Times , The Atlantic , and BBC , with policy briefings presented on Capitol Hill. Current research explores EV supply chains, climate resilience, and transportation equity.

Abolfazl Asudehمشاهده پروفایل

دانشیار

• Algorithm Design
• Data Science
• Artificial Intelligence
• +۴ مورد دیگر

Abolfazl Asudeh is an Associate Professor in the Department of Computer Science at the University of Illinois Chicago and director of the Innovative Data Exploration Laboratory (InDeX Lab) . He is a Senior Member of ACM and IEEE , serving as Associate Editor for IEEE Transactions on Knowledge and Data Engineering , VLDB Ambassador , and VLDB Endowment Liaison to NSF . His research focuses on Algorithm Design for Data and AI problems , emphasizing efficient, accurate, and responsible solutions through Approximation Algorithms , Randomized Methods , and Computational Geometry . Recent work explores LLM optimization ( Needle ), fair data structures ( FairHash ), and responsible AI frameworks ( Chameleon ). Scientific awards include Communications of the ACM Research Highlight Google Research Scholar Award SIGMOD 2019 Research Highlight Best of VLDB 2020 SIGMOD 2017 Reproducibility Award Grants: NSF IIS-2348919 (2024-2027): Fairness-aware Data Structures NSF IIS-2107290 (2021-2024): Collaborative Fairness Research The InDeX Lab develops systems like Needle (image retrieval) and RSR (matrix multiplication). His work integrates fairness , reliability , and computational efficiency across data structures , LLMs , and responsible AI implementations.

Sebastian Seungمشاهده پروفایل

استاد

• Neuroscience
• Machine Learning
• Connectomics
• +۵ مورد دیگر

Sebastian Seung is a Professor at Princeton University , affiliated with both the Department of Computer Science and the Princeton Neuroscience Institute . His career spans Harvard University (Ph.D., 1990), Bell Laboratories, and Massachusetts Institute of Technology before joining Princeton in 2014. An External Member of the Max Planck Society and 2008 Ho-Am Prize recipient, Seung merges machine learning with neuroscience . Research Focus : Pioneering connectomics , Seung developed technologies for reconstructing neural circuits from high-resolution brain images, including FlyWire for collaborative brain mapping. His work explores brain function, development, and plasticity , drawing parallels between fly visual systems and convolutional networks . Awards & Affiliations : 2008 Ho-Am Prize in Engineering External Member, Max Planck Society Technical Contributions : Led breakthroughs in 3D connected component labeling and high-throughput EM imaging for mammalian brains, partnering with NIH’s BRAIN Initiative to scale connectomics to whole mouse brains. Seung’s team has shifted from EM analysis to interpreting connectomes , focusing on neural circuit function and biological mechanisms in flies and mice. His lab alumni network spans institutions, advancing AI and neuroscience globally.

• Behavioural Economics
• Evolutionary Game Theory
• Social Networks
• +۵ مورد دیگر

Friederike Mengel is a Professor of Economics at the University of Essex and holds a Visiting Professorship at Erasmus University Rotterdam. She is also a Fellow of the Academy of Social Sciences (UK). Her research focuses on Behavioural Economics , integrating Game Theory , Evolutionary Dynamics , and Social Network Analysis . Key research themes include social influence in networks , opinion dynamics , emergence of social norms , and links between social identity, bounded rationality, and discrimination . Recent work explores Covid-19 impacts on productivity and innovation in hybrid work environments . Her scientific awards include the Best Paper Award from Quantitative Economics (2018) and recognition as an Academy of Social Sciences Fellow. Her publications span topics like cooperation in viscous populations , strategic behavior in repeated games , and gender bias in opinion aggregation , with media coverage in outlets like The Economist and Financial Times .

James C. Geeمشاهده پروفایل

استاد

• Biomedical Image Analysis
• Medical Imaging Computing
• Image Segmentation
• +۵ مورد دیگر

James C. Gee is a Professor of Radiologic Science in Radiology at the University of Pennsylvania's Perelman School of Medicine. He serves as Director of the Penn Image Computing and Science Laboratory and Co-Director of the Translational Biomedical Imaging Center , with affiliations in Bioengineering and Applied Mathematics graduate groups. His research focuses on biomedical image analysis, specialization in segmentation, registration, and morphometry applied to neurodegenerative diseases and multi-organ systems. Education : B.S. in Computer Science/Electrical Engineering (University of Washington, 1987), Ph.D. in Computer and Information Science (University of Pennsylvania, 1996) Research : Quantitative medical imaging methods, brain connectomics, neurodegeneration mapping, and translational imaging technologies Publications : 15+ recent works on AI-driven image analysis for Alzheimer's disease, cardiac amyloidosis, and radiomics applications Leadership : Directs MSE-DS Online Degree Program, co-chairs Radiology DCOAP Committee, and founded RISE (Radiology Initiative to Support Inclusive Excellence) His laboratory develops advanced computational tools like ITK-SNAP for biomedical imaging, with applications in both in vivo clinical imaging and ex vivo histology . The work spans cross-disciplinary collaborations in computer science, neuroscience, and clinical medicine.

Qi Longمشاهده پروفایل

استاد

• Genomics
• Computational Biology
• Biostatistics
• +۱۰ مورد دیگر

Qi Long is a Professor at the University of Pennsylvania, holding joint appointments in the Department of Biostatistics, Epidemiology and Informatics (Perelman School of Medicine), Department of Computer and Information Science (School of Engineering and Applied Science), and Department of Statistics and Data Science (The Wharton School). He serves as Founding Director of the Center for Cancer Data Science, Associate Director of the Penn Institute for Biomedical Informatics, and Associate Director for Quantitative Data Science at the Abramson Cancer Center. His research bridges statistical and machine learning (ML/AI) method development with biomedical applications, focusing on precision medicine and population health. Education : Ph.D. (2005) and M.S. (2003) in Biostatistics from University of Michigan; B.S. (1998) in Computer Science from University of Science and Technology of China. Research interests include: Robust statistical and ML/AI methods for big health data (-omics, EHRs, imaging, mHealth) Multimodal data integration and subgroup heterogeneity analysis Missing data, causal inference, Bayesian methods, and clinical trials Data privacy, algorithmic fairness, and responsible AI in healthcare Foundation models and agentic AI for biomedicine His publications focus on privacy-preserving AI, fairness-aware ML, and integrative models for multi-omics and EHRs. Recent work explores LLMs and watermark detection in hybrid human-AI settings. Scientific Awards : Elected fellow: AAAS, ASA, IMS, ISI, AMIA He leads large NIH- and ARPA-H-funded initiatives, directing statistical coordinating centers for national clinical trials. His lab trains numerous PhD/Master’s students and postdocs, many of whom hold prestigious academic or industry positions.

Jonnie Pennمشاهده پروفایل

استاد آموزشی

• History of Artificial Intelligence
• AI Ethics
• Technology and Society
• +۵ مورد دیگر

Dr. Jonnie Penn is an Associate Teaching Professor of AI Ethics and Society at the University of Cambridge, where he teaches in the Department of History and Philosophy of Science. He holds multiple prestigious affiliations including as a Faculty Associate at Harvard's Berkman Klein Center, Senior Research Fellow at the Leverhulme Centre for the Future of Intelligence, and Research Fellow at St. Edmund's College. His educational background includes First Class Honours from the University of Cambridge and degrees from McGill University. His research explores the deep historical relationships between notions of efficiency and authority in computer science, artificial intelligence, and management science, with particular focus on systems theory, complex science, and technocracy within AI Ethics. Penn's scholarly work reveals consistent themes across decades of research: the historical genealogy of power in AI systems, critical examinations of algorithmic governance, and the social implications of digital technologies. His publications span from technical analyses of data ecologies to broader societal critiques of corporate influence on AI development. #1 New York Times Bestselling Author FRSA (Fellow of the Royal Society for Arts) MIT Media Lab Assembly Fellow Google Technology Policy Fellow Fellow of the British National Academy of Writing As Project Development Lead of the 'Histories of AI' initiative at the Leverhulme Centre for the Future of Intelligence, Penn connects a global network of scholars examining the social, political, and economic ramifications of intelligent systems. He has co-chaired workshops at leading academic conferences including HSS, SHOT, NeurIPS, ICML, and ICLR, and has presented research to the United Nations, European Parliament, and UK House of Lords. His current work focuses on 'decomputerisation' as a critical framework for understanding our relationship with technology.

Tristan A.F. Longمشاهده پروفایل

دانشیار

• Evolutionary genetics
• Behavioral ecology
• Experimental evolution
• +۳ مورد دیگر

Dr. Tristan A.F. Long is an Associate Professor in the Department of Biology at Wilfrid Laurier University's Faculty of Science in Waterloo, Ontario. A behavioral ecologist and evolutionary geneticist, he focuses on sexual selection and the role of female mate preference variation in evolutionary change. With teaching responsibilities for large introductory biology courses like BI111 and BI393, he has developed innovative active learning techniques using playing cards, iClickers, and role-playing games to teach population genetics and ecological principles. University of Western Ontario - BSc in Honours Ecology and Evolution (1999) University of Guelph - MSc in Zoology (2001) Queen’s University - PhD in Biology (2005) University of California Santa Barbara - Postdoctoral Fellow (2005-2009) University of Toronto - Postdoctoral Fellow (2009-2010) His research examines how female Drosophila melanogaster vary in their mating preferences and how these differences shape evolutionary trajectories. He has published extensively on reproductive plasticity, sexual conflict, and environmental interaction effects. His laboratory combines experimental evolution with computational modeling to explore genetic trade-offs and behavioral adaptations. Scientific awards include the Laurier Teaching Award for Sustained Excellence (2017). He has developed innovative classroom techniques like the Battle of the Beaks exercise for teaching adaptive evolution and an iClicker-based population genetics simulation using playing cards. His 2024 BI393 biostatistics course policy strongly discourages generative AI use due to concerns about educational integrity and environmental impact.

• Health IT
• Healthcare Analytics
• Healthcare Operations Management
• +۵ مورد دیگر

Gaurav Jetley is an Assistant Professor in the Department of Computer Information Systems at Colorado State University. Education: PhD in Business Administration (Information Systems) from Muma College of Business, University of South Florida Research Interests: Focuses on healthcare technology, including health IT, healthcare analytics, and healthcare operations management. Employs data-driven methodologies, machine learning, and econometric techniques to solve complex problems in health information systems. Scientific Contributions: Recent publications highlight his work in EHR quality, racial bias in ICU pain measurement, and health IT workflow optimization, demonstrating interdisciplinary applications of business analytics in healthcare. Teaching: Instructs graduate and undergraduate courses in data mining and analytics.

Benjamin Shoreمشاهده پروفایل

دانشیار

• Pediatric Orthopedic Surgery
• Cerebral Palsy
• Hip Reconstruction
• +۳ مورد دیگر

Benjamin Shore, MD, MPH, FRCSC, is Associate Professor of Orthopedic Surgery at Harvard Medical School and a practicing pediatric orthopedic surgeon at Boston Children’s Hospital. He serves as Co-Director of the Cerebral Palsy and Spasticity Center and Director of the Pediatric Orthopaedic Surgery Fellowship. Education and Training Undergraduate: Biology, University of Victoria, 1999 MPH: Harvard School of Public Health, 2013 MD: University of Western Ontario, 2003 Residency: Orthopedic Surgery, University of Western Ontario, 2008 Fellowship 1: Pediatric Orthopedics, Royal Children's Hospital, Melbourne, 2009 Fellowship 2: Pediatric Orthopedics, Boston Children’s Hospital, 2010 Research Focus Dr. Shore’s research centers on improving outcomes for children with cerebral palsy and other complex musculoskeletal conditions. His work spans hip surveillance and reconstruction, gait abnormalities, trauma care, and the implementation of evidence-based surgical pathways. He has pioneered investigations into anesthesia protocols, infection prevention, and patient-reported outcome measures for pediatric orthopedic populations. Scientific Awards St. Giles Young Investigator Award (POSNA) Clinician Scientist Development Program Award (CSDP) Charles H. Hood Foundation Child Health Research Award Leadership & Multi-Disciplinary Teams At Boston Children’s Hospital, Dr. Shore leads a high-performance team within the Cerebral Palsy and Spasticity Center that integrates orthopedic surgery, neurology, physical therapy, and social work to deliver patient- and family-centered care. He mentors fellows and residents and actively contributes to national consensus projects using Delphi methodology to standardize surgical indications in cerebral palsy.

Omobolanle Ogunseijuمشاهده پروفایل

استادیار

• Workforce Development
• Construction Safety
• Artificial Intelligence
• +۷ مورد دیگر

Omobolanle Ogunseiju is an Assistant Professor in the School of Building Construction at Georgia Institute of Technology . She holds a Ph.D. in Environmental Design and Planning from the Department of Building Construction at Virginia Tech. Education: Ph.D. in Environmental Design and Planning, Virginia Tech Current Role: Assistant Professor, Georgia Tech School of Building Construction Her research focuses on integrating wearable robotics and Artificial Intelligence (via digital twin , cyber-physical systems , and data sensing ) to improve construction workforce safety, health, and well-being . She explores ethical implications of automation in construction, particularly in human-technological dynamics. Key research trends include: Advancing smart communities through robotics and AI Exoskeleton evaluation for ergonomic risk reduction Mixed reality environments for construction education Data analytics for cognitive and physical risk assessment Professional identity development in construction engineering students Industry-academia alignment for sensing technology integration Scientific awards: Outstanding Doctoral Candidate, Myers-Lawson School of Construction Outstanding Doctoral Student, College of Architecture and Urban Studies at Virginia Tech Teaching philosophy emphasizes experiential learning , engagement techniques , and hierarchical assessments . She developed the Construction Cost Management course at Georgia Tech and will lead Construction Technology courses. Previously, she taught Smart Construction , Building Systems Technology , and Wireless Sensing in Construction Management at Virginia Tech.

Ruurd Jaarsmaمشاهده پروفایل

استاد

• Orthopaedic Trauma
• Orthopaedic Paediatrics
• Biomechanical Engineering
• +۱ مورد دیگر

Professor Ruurd Jaarsma serves as Clinical and Academic Director of Orthopaedics and Trauma Surgery for the Southern Adelaide Local Health Network, practicing at Flinders Medical Centre and Flinders Private Hospital. He holds full membership in Flinders University's College of Medicine and Public Health, Flinders Health and Medical Research Institute, and Medical Device Research Institute within the College of Science and Engineering, bridging clinical practice and academic research since relocating from the Netherlands in 2004. His educational credentials include: MD from University of Groningen, Netherlands (1994) Orthopaedic Surgeon certification from Dutch College of Orthopaedic Surgeons (2003) PhD from University of Nijmegen, Netherlands (2004) FRACS (Orth) from Royal Australasian College of Surgeons (2009) FA(Orth)A from Australian Orthopaedic Association (2012) Research centers on orthopaedic trauma, paediatric orthopaedics, and biomechanical engineering of implants, with specialized focus on rotational malalignment after long bone nailing. His work directly supports UN Sustainable Development Goal 3 (Good Health and Well-being) through trauma care innovation and surgical education. Current investigations integrate machine learning with fracture diagnostics to improve clinical decision-making. Recent publications demonstrate strong AI integration in orthopaedic trauma, featuring machine learning algorithms for scaphoid fracture probability estimation, deep learning classification of tibial plateau fractures, and open-source neural networks for distal radius fracture detection. Concurrent clinical trials address compartment syndrome diagnosis while biomechanical studies examine acetabular fracture outcomes, reflecting his dual focus on computational innovation and clinical validation. His scientific recognition includes: 2006 Burns Alpers Award for excellence in teaching from Flinders University As Director of Orthopaedic Training, he supervises Australian Orthopaedic Association accredited fellowships with registered interests in orthopaedic surgery, biomechanical engineering, and musculoskeletal medicine. His supervisory framework emphasizes translational research connecting biomechanical principles with surgical practice. External engagement includes active participation in SA State Trauma Committees, driving statewide improvements in trauma systems and surgical protocols. Professor Jaarsma maintains clinical-academic synergy through Flinders Medical Centre's orthopaedic department, where he leads trauma service development while directing research initiatives in the Medical Device Research Institute. His current projects focus on AI-driven fracture assessment tools and biomechanical optimization of implant systems, with ongoing collaborations across the Machine Learning Consortium and international orthopaedic networks.

Mark Burrisمشاهده پروفایل

استاد

• Travel behavior economics
• Value pricing for highways
• Price elasticity of travel demand
• +۷ مورد دیگر

Mark Burris is the Herbert D. Kelleher Professor in the Department of Civil & Environmental Engineering at Texas A&M University's College of Engineering, where he also serves as Division Head of Transportation & Materials Engineering. He is additionally a Research Engineer with the Texas A&M Transportation Institute, demonstrating his dual commitment to academic research and practical transportation solutions. With a career spanning over two decades since joining Texas A&M in 2001, Burris has established himself as a leading expert in transportation economics and traveler behavior. Burris's research focuses on the intersection of transportation economics, behavioral psychology, and infrastructure management. His work primarily investigates traveler responses to pricing mechanisms, particularly value pricing and high-occupancy toll (HOT) lanes. He has pioneered research combining traditional transportation engineering with behavioral economics to understand seemingly irrational traveler choices, such as paying to use express lanes that are sometimes slower than toll-free alternatives. His research has significantly advanced the understanding of travel time value, reliability valuation, and how psychological factors influence transportation decisions. Analysis of Burris's recent publications reveals a strong trend toward integrating behavioral economics with transportation engineering, with increasing attention to equity considerations in road pricing, the impacts of emerging technologies like autonomous and connected vehicles, and innovative methods for measuring traveler responses. His work consistently addresses practical transportation challenges while advancing theoretical understanding of travel behavior. Burris has served in prominent leadership roles, including a six-year term as chair of TRB's transportation economics committee. He has advised numerous federal agencies, serving on NCHRP panels and participating in FHWA expert forums on road pricing. His expertise is widely recognized in both academic and professional transportation circles. As an educator, Burris has advised over 60 graduate students and numerous undergraduates, teaching core courses including CVEN 307 (Introduction to Transportation Engineering), CVEN 454 (Urban Planning for Engineers), and CVEN 632 (Transportation Engineering: Economics). His research portfolio includes substantial funding from FHWA, NCHRP, and various state transportation agencies, with recent projects focusing on behavioral economics applications to managed lanes, vehicle miles traveled fee equity, and the impact of emerging mobility technologies.

Eldan Cohenمشاهده پروفایل

استادیار

• Machine Learning
• Deep Learning
• Optimization
• +۶ مورد دیگر

Eldan Cohen serves as an Assistant Professor of Industrial Engineering within the Department of Mechanical & Industrial Engineering at the University of Toronto's Faculty of Applied Science and Engineering. His academic journey includes a PhD from the same department followed by a postdoctoral fellowship in Computer Science at the University of Toronto and the Vector Institute for Artificial Intelligence. His educational background is detailed as follows: PhD in Mechanical & Industrial Engineering, University of Toronto Postdoctoral Fellowship in Computer Science, University of Toronto and Vector Institute for Artificial Intelligence Dr. Cohen's research centers on machine learning, deep learning, heuristic search, and optimization with strong emphasis on interpretable and human-compatible AI systems. His work bridges theoretical advancements with practical applications in healthcare (e.g., patient-physician interaction analysis, surgical safety diagnostics), automated planning, natural language processing, and software engineering. Recent projects develop interpretable clustering methods for medical data and optimization techniques for constrained sequence generation. Analysis of his 2023-2025 publications reveals a concentrated focus on healthcare AI applications, particularly using large language models for clinical text analysis and diagnostic support systems. Significant work also addresses interpretable machine learning for medical imaging, diverse plan selection in optimization, and constrained sequence generation in domains like vehicle routing. No major scientific awards or fellowships are documented in the available information. As an academic advisor, Dr. Cohen mentors graduate students in mechanical and industrial engineering, guiding research in optimization and machine learning. His OptiMaL research group fosters collaboration between computer science and industrial engineering to solve real-world decision-making challenges through human-centered AI approaches. The Optimization and Machine Learning (OptiMaL) research group, led by Dr. Cohen, serves as the primary hub for developing scalable, interpretable AI solutions for complex healthcare, planning, and engineering problems, with active projects in medical diagnostics and automated planning systems.