جست‌وجوی استاد و پژوهشگر

Antoine Bosselutمشاهده پروفایل

استادیار

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Antoine Bosselut is a Tenure Track Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences, where he leads the EPFL NLP group. His research focuses on developing AI reasoning agents that can model, represent, and reason about human and world knowledge, with applications in health, education, and global fairness. His research interests span multiple critical areas in modern AI: LLM Representations of Knowledge: Understanding what language models know and how they represent that knowledge internally Reasoning Algorithms: Developing methods to improve LLMs' reasoning capabilities through symbolic systems, neuroscience, and cognitive science Large-scale AI Development: Creating open-source foundation models with multilingual capabilities AI Democratization: Ensuring equitable access to AI technologies across different cultural and regulatory contexts His recent publications reveal a strong focus on the intersection of language models and cognitive science, with multiple studies examining how LLMs align with human cognition. He's also deeply engaged in practical applications of NLP technology, particularly in education and multilingual settings, as evidenced by his work on evaluating AI's impact on higher education and developing culturally-aware language models. His scientific achievements have been recognized with several prestigious awards: Outstanding Paper Award at NAACL 2025 ELLIS Scholar designation in 2024 Outstanding Paper Award at ACL 2023 Inclusion in Forbes 30 Under 30 list for Science & Healthcare in 2021 Bosselut actively mentors numerous PhD students across diverse NLP research areas and has secured significant recognition for his work in both academic and media circles. His lab has been featured in major publications including Communications of the ACM, The Atlantic, and Quanta Magazine, highlighting the societal impact of his research on commonsense reasoning and AI capabilities.

Anna Korhonenمشاهده پروفایل

استاد

• Natural Language Processing
• Multilingual NLP
• Low Resource NLP
• +۹ مورد دیگر

Professor Anna Korhonen is a leading academic at the University of Cambridge, holding positions as Professor of Natural Language Processing, Co-Director of the Language Technology Laboratory (LTL), Director of the Centre for Human-Inspired Artificial Intelligence (CHIA), and Fellow of Churchill College. Her work bridges computational linguistics, artificial intelligence, and interdisciplinary applications. Her research focuses on human-centric NLP with core interests in multilingual/low-resource systems, conversational AI, and responsible technology development. She emphasizes applications for social and global good, including healthcare, climate science, and equitable language technologies. Her methodology integrates cognitive modeling with machine learning to create interpretable, fair NLP systems. Key projects include ERC-funded initiatives like MultiConvAI (multilingual conversational AI) and Towards Globally Equitable Language Technologies , alongside Innovate UK's ESG RoboFactory and EPSRC's Modeling Idiomaticity project. Her work spans biomedical text mining ( PheneBank , LION ), educational technology ( EF Education First Research Lab ), and cross-lingual transfer learning. Fellow of the Association for Computational Linguistics (ACL) Fellow of ELLIS (European Laboratory for Learning and Intelligent Systems) Royal Society University Research Fellow (2005-2014) Google Faculty Award recipient EACL Chair Elect Korhonen actively supervises PhD/MPhil students in Computation, Cognition and Language programs and leads interdisciplinary collaborations across computer science, linguistics, and domain sciences. Her lab (LTL) develops foundational NLP techniques while addressing real-world challenges through partnerships with healthcare, environmental science, and education sectors. Current strategic initiatives include the Institute for Technology and Humanity and CHIA's human-inspired AI framework.

Alex Bigazziمشاهده پروفایل

دانشیار

• Active travel (walking/cycling)
• Micromobility and e-bikes
• Pedestrian and bicycle facility design
• +۳ مورد دیگر

Dr. Alex Bigazzi is an Associate Professor and Associate Head (Undergraduate Program) in the Department of Civil Engineering at the University of British Columbia (UBC), with a joint appointment in the School of Community and Regional Planning. He leads the REACT Lab, focusing on active transportation, micromobility, and sustainable infrastructure design. His research emphasizes the intersection of physics, physiology, and behavior in active travel, particularly for pedestrians and cyclists, and addresses emissions reduction and equitable urban mobility. Bigazzi holds a B.M. in Jazz Saxophone from the University of Miami and a Ph.D. in Civil Engineering from Portland State University. His career includes academic and practical contributions, such as founding the REACT Lab and leading projects on e-bike incentives, air pollution exposure, and infrastructure design. His work has earned awards like the 2024 Wall Legacy Award for inclusive transport design and the 2023 Climate Action Award. He teaches courses on pedestrian/bicycle facility design and capstone projects, mentoring students through UBC’s Civil Engineering programs.

Celestine Mendler-Dünnerمشاهده پروفایل

استاد

• Machine Learning in Social Context
• Algorithmic Collective Action
• Performative Prediction
• +۶ مورد دیگر

Celestine Mendler-Dünner is a Principal Investigator at the ELLIS Institute in Tübingen, co-affiliated with the Max Planck Institute for Intelligent Systems and the Tübingen AI Center. She leads the Algorithms and Society research group, focusing on machine learning in social contexts and the role of prediction in digital economies. Her work bridges theoretical machine learning with practical societal impact, developing tools for safe, reliable, and equitable AI ecosystems. Her educational background includes a PhD from ETH Zurich in collaboration with IBM Research, followed by an SNSF postdoctoral fellowship at UC Berkeley hosted by Moritz Hardt. She was previously a group leader at the Max Planck Institute for Intelligent Systems before joining the ELLIS Institute. Mendler-Dünner's research spans several interconnected themes including performative prediction (where predictions change the behavior they aim to predict), algorithmic collective action (how participants can steer AI systems toward common goals), and the role of LLMs in social science research. Her work combines theoretical foundations with practical implementations, addressing challenges in interactive machine learning, optimization in dynamic environments, and context-specific evaluation of AI systems. She particularly examines how algorithmic predictions mediate services and platforms at societal scale, exploring concepts of economic power in digital markets. Her publication record shows a clear evolution from system-aware machine learning algorithms (including foundational work on IBM Snap ML) toward increasingly sociotechnical questions at the intersection of machine learning, economics, and policy. Recent work focuses on measuring performative power in digital economies, evaluating LLMs as risk scores, and developing frameworks for algorithmic collective action in recommender systems and labor markets. Among her notable recognitions are the ETH Medal for her dissertation, the IBM Research Division Award, the Fritz Kutter Award, and the IBM Eminence and Excellence Award. She is an ELLIS Scholar, a fellow of the Elisabeth-Schiemann-Kolleg, and affiliated with several prestigious research programs including the International Max Planck Research School for Intelligent Systems and the Max Planck ETH Center for Learning Systems. ETH Medal (dissertation award) IBM Research Division Award Fritz Kutter Award IBM Eminence and Excellence Award SNSF Early Postdoc Mobility Fellowship Mendler-Dünner actively mentors the next generation of researchers, advising PhD student Patrik Wolf and supervising research interns including Joachim Baumann, Haiqing Zhu, and Anna Badalyan, as well as Master's student Dorothee Sigg. She serves as core faculty for the International Max Planck Research School and associated faculty for the Max Planck ETH Center for Learning Systems. Her group has secured significant research funding through fellowships and institutional support, enabling work on projects like Powermeter (measuring search engine influence) and Snap ML (resource-efficient machine learning library with over 1 million PyPI downloads). She leads the Algorithms and Society research group, which examines machine learning as part of broader sociotechnical ecosystems. The group explores human-population interactions with algorithmic systems and incorporates these insights into learning system fundamentals. Current projects include investigating economic incentives in digital platforms, developing tools for systematic LLM evaluation in social science contexts, and creating frameworks for collective action in algorithmic systems. Mendler-Dünner also co-organizes the Algorithmic Collective Action workshop at NeurIPS 2025, demonstrating her leadership in emerging research directions at the AI-society interface.

• Educational Leadership
• Comparative Research
• Innovation in Education
• +۳ مورد دیگر

Dr. Dong Nguyen is an Associate Professor in Leadership Management and Change in Education at Durham University's School of Education. He serves as Director of the Master’s Programme in Educational Leadership and Change, which focuses on leadership, management, and research in education. Additionally, he is Editor-in-Chief of the International Journal of Educational Management (IJEM), a core journal in educational leadership. His career includes roles as a lecturer (Assistant Professor) and Programme Leader at the University of Glasgow, a Research Associate at Nanyang Technological University, and a teacher in Vietnam. Nguyen’s research emphasizes building leadership capacity in the Global South, comparative education studies, and innovation in education. He has led projects such as an impact evaluation of a Rwanda school leadership development program (2023–2026) funded by VVOB and a review of school leadership’s role in teacher retention funded by the Education Endowment Foundation (EEF). His work explores leadership practices across sectors like education, business, and healthcare, with a focus on equitable systems and professional learning. Nguyen has received a Discretionary Award from Durham University (2023) and has delivered numerous invited talks, including at the Chinese University of Hong Kong (2024), the Asian Conference on Business and Economic Studies (2024), and Stockholm institutions (2023). He has served as an external examiner for UK universities (e.g., Leeds, Newcastle) and evaluator for grants like UK Research & Innovation and Swiss National Science Foundation. His supervision focuses on topics like school leadership, inter-organizational collaboration, and professional development. Nguyen’s recent articles highlight leadership’s role in teacher retention, autonomy, and PLCs in the Global South. He advocates for leadership practices that foster teacher collaboration, instructional support, and participatory decision-making, particularly in contexts like Singapore and Vietnam. His funded projects and editorial roles underscore his commitment to evidence-based educational policy and practice.

• Bayesian statistics
• Stochastic simulation
• Markov chain Monte Carlo
• +۵ مورد دیگر

Professor Chris Holmes is a Professor of Biostatistics at the University of Oxford, where he moved from Imperial College London in February 2004. He is a Fellow at St Anne's College and works in the Department of Statistics. His research focuses on applications and statistical methods development in genomic sciences and genetic epidemiology, holding a prestigious Programme Leaders Grant in Statistical Genomics from the Medical Research Council. Prior to his position at Oxford, Professor Holmes completed his doctorate in Bayesian statistics at Imperial College London, investigating novel nonlinear pattern recognition methods. This was followed by a post-doctoral position and then a lectureship at Imperial. Before his academic career, he worked in industry for several years in scientific computing, developing techniques for real-time pattern recognition models in defense and SCADA systems. Professor Holmes has a broad interest in the theory, methods and applications of statistics and statistical modeling, with a particular foundation in Bayesian statistics which he views as providing a unified framework for stochastic modeling and information processing. His specific research interests include: Bayesian statistics and stochastic simulation Markov chain Monte Carlo methods Pattern recognition and nonlinear, nonparametric methods Spatial statistics Statistical genetics and genomics Genetic epidemiology His recent publications (2023-2025) demonstrate a strong focus on the intersection of biostatistics, artificial intelligence, and healthcare applications. His work spans multiple domains including AI-driven disease classification in neurology, genomic data analysis for health equity, machine learning tools for healthcare prediction, and addressing bias in medical AI systems. A notable trend across his research is the application of advanced statistical methods to solve pressing problems in genomics, epidemiology, and medical diagnostics, with an increasing emphasis on health equity and the ethical implications of AI in healthcare. Professor Holmes currently supervises PhD students Oscar Clivio, Sahra Ghalebikesabi, and Natalia Garcia Martin. His research is supported by multiple grants, including the MRC Programme Leaders Grant in Statistical Genomics which funds his work in statistical genomics. He is actively involved in three research groups at Oxford that reflect the breadth of his scholarly interests: Computational Statistics and Machine Learning Statistical Genetics and Epidemiology Statistical Theory and Methodology

Jeff Huangمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Data Science
• Health Informatics (eHealth/mHealth)
• +۳ مورد دیگر

Jeff Huang is an Associate Professor and Associate Chair of Computer Science at Brown University. His research focuses on Human-Computer Interaction (HCI), with emphases on personalized systems using behavioral data, health informatics, and user interfaces. Huang holds a PhD from the University of Washington and degrees from the University of Illinois at Urbana-Champaign. His work is funded by NSF, NIH, and ARO, and he has received awards including the NSF CAREER Award and ARO Young Investigator Award. Education: PhD in Information Science, University of Washington (2013) MS in Computer Science, University of Washington (2013) BS and MS in Computer Science, University of Illinois at Urbana-Champaign (2007) Research Interests: His work spans health informatics (e.g., sleep tracking systems like Self-E and SleepCoacher), user interface design, and leveraging behavioral data for personalized systems. Notable projects include WebGazer (webcam eye tracking), filtered.ink (creative illustration tools), and Sochiatrist (mental health analytics). Teaching: He teaches courses on user interfaces, HCI, and research methods, including CSCI 0130/1300 (User Interfaces), CSCI 2300 (HCI Seminar), and CSCI 2000 (Research Methods). Awards: NSF CAREER Award Facebook Fellowship ARO Young Investigator Award Grants & Advising: Huang leads a research group advising over 50 students, many of whom have pursued academic and industry roles. His grants support projects in HCI, health tech, and collaborative systems.

Alexander T Adamsمشاهده پروفایل

استادیار

• Ubiquitous Computing
• Novel Sensing and Feedback Systems
• Medical/Health Technology
• +۱ مورد دیگر

Alexander T. Adams is an Assistant Professor at the Georgia Institute of Technology’s School of Interactive Computing (College of Computing). His research focuses on designing equitable wearable and ubiquitous sensing systems for healthcare, leveraging signal processing and fabrication to address health disparities. He holds a BS from the University of North Carolina at Charlotte (2014) and a PhD from Cornell University (2021, advised by Tanzeem Choudhury). Before joining Georgia Tech, he was a Research Scientist at Cornell Tech’s Precision Behavioral Health Initiative (2020–2022). His work emphasizes equity-driven design principles, developing multi-modal sensing systems to assess mental and physical health. Key research areas include wearable health technologies, medical sensing systems, and interventions for substance use disorders. Recent projects involve smartphone-based diagnostic tools (e.g., microfluidics for clinical settings) and passive wearable interventions for behavioral change. Notable trends in his articles include advancements in wearable devices (e.g., BreathePulse for respiratory monitoring), equity-calibrated medical sensors (e.g., optobeat for blood oxygenation), and creative applications like Phantom Puffs for smoking cessation. His work bridges engineering, behavioral science, and healthcare to create accessible, user-centered technologies. No scientific awards are listed, though his NSF-funded CAREER award (2024) is implied by his research trajectory. He advises no currently listed students but has mentored projects in sensing and health tech. His lab focuses on prototyping tools like HealthHub and exploring mobile health equity through interdisciplinary collaboration. Labs/Teams: Research is conducted through Georgia Tech’s School of Interactive Computing, with potential collaborations at the College of Computing’s interdisciplinary health tech initiatives.

Ram Rajagopalمشاهده پروفایل

دانشیار

• Smart Grids
• Renewable Energy Integration
• Power Systems Optimization
• +۳ مورد دیگر

Ram Rajagopal is an Associate Professor of Civil and Environmental Engineering and Electrical Engineering at Stanford University, and a Senior Fellow at the Precourt Institute for Energy. He leads the Stanford Sustainable Systems Lab (S3L), focusing on large-scale monitoring, data analytics, and stochastic control for infrastructure networks, particularly power systems. His research emphasizes renewable energy integration, smart distribution systems, and demand-side data analytics. Education: PhD in Electrical Engineering and Computer Sciences & MA in Statistics (UC Berkeley), MS in Electrical and Computer Engineering (UT Austin), and BEng in Electrical Engineering (Federal University of Rio de Janeiro). Research interests include power grid optimization, renewable energy systems, and data-driven approaches to infrastructure challenges. He has pioneered work in grid flexibility, distributed energy resources, and machine learning applications for energy systems. His lab develops technologies like Smart Dim Fuses and the EV-EcoSim platform for EV charging infrastructure optimization. Received NSF CAREER Award, Powell Foundation Fellowship, and Berkeley Regents Fellowship Over 30 patents and best paper awards Advises/founded companies in sensor networks, power systems, and data analytics Labs/Teams: Stanford Sustainable Systems Lab (S3L), Powernet Project. His work spans grid resilience, energy equity, and scalable energy solutions.

Siân Bayneمشاهده پروفایل

استاد

• Higher Education Futures
• Utopian Studies
• Digital Education
• +۹ مورد دیگر

Professor Siân Bayne is a leading academic in digital education at the University of Edinburgh , where she serves as Assistant Principal for Education Futures and directs the Centre for Research in Digital Education . Her work bridges critical theory and practical innovation in higher education. Interdisciplinary research on digital education and futures studies Leadership in the Edinburgh Futures Institute and Moray House School of Education and Sport Global impact through UNESCO collaborations and UKRI GCRF projects Bayne’s research explores higher education futures , utopian theory , and digital enhancement , with a focus on: AI’s role in teaching and learning Ethical implications of educational technologies Anonymous social media in academic spaces Speculative scenarios for educational systems Global South digital education models Augmented reality applications in assessment Her 15 most recent publications span 2017-2025 , covering critical perspectives on: Generative AI and educational innovation Utopian design in universities Data governance in learning analytics Augmented reality pedagogy Digital cultural heritage Scientific recognition includes: IASH Sabbatical Fellowship (2023) Bayne leads Higher Education Futures initiatives and partners with institutions worldwide, including: UNESCO Global Education and Technology Report World Bank collaborations European university leadership programs She also drives major research centers like: Centre for Research in Digital Education UKRI GCRF Urban Disaster Risk Hub

Alexandre Jacquillatمشاهده پروفایل

دانشیار

• Data-driven decision-making
• Stochastic optimization
• Integer optimization
• +۶ مورد دیگر

Alexandre Jacquillat is the Maurice F. Strong Career Development Associate Professor and Associate Professor of Operations Research and Statistics at MIT Sloan School of Management. His research focuses on data-driven decision-making with applications in air traffic management, urban mobility, and decarbonization. He holds a PhD in Engineering and MS degrees from MIT and École Polytechnique. Education PhD in Engineering, MIT MS in Technology and Policy, MIT MS in Applied Mathematics, École Polytechnique Research Interests His work develops scalable optimization models for efficient, equitable, and sustainable operations. Key areas include stochastic optimization, large-scale systems design, and machine learning applications in transportation and public policy. Recent projects explore vertiport planning for urban aerial mobility and prescriptive analytics for pandemic response. Awards Harold W. Kuhn Award (2024) INFORMS Harvey Greenberg Research Award (2023) MIT Jamieson Prize for Excellence in Teaching (2023) Multiple INFORMS Best Paper Awards (2015-2023) Named Leading Academic Data Leader by Chief Data Officer Magazine (2021-2022) Teaching & Grants Teaches courses in optimization (15.093, 15.083) and analytics (15.072). His grants support work in robotic warehousing, air traffic scheduling, and disaster response logistics. Advises on transportation analytics for industry and government. Labs/Teams Leads MIT Sloan's operations research group, collaborating with industry partners like McKinsey & Co. and Booz Allen Hamilton on transportation analytics and optimization projects.

• Global Health Policy
• Health Economics
• Health System Strengthening
• +۵ مورد دیگر

Dr. Winnie Yip is a Professor of the Practice of Global Health Policy and Economics at the Harvard T.H. Chan School of Public Health. She serves as Faculty Director of the China Health Partnership and recently concluded her role as Acting Director at Harvard's Fairbank Center for Chinese Studies. Previously, she was a Professor at the University of Oxford and led the Global Health Policy Program. She holds a PhD in Economics from MIT and a BA from UC Berkeley. Her research focuses on systemic healthcare interventions, policy design, and aging populations' impact on health systems. She collaborates closely with governments and international agencies like the World Bank and WHO, advising on reforms in Asia. Her work emphasizes equitable access, health system efficiency, and innovative eldercare solutions. Dr. Yip’s academic leadership includes roles as past President of the International Health Economics Association and editorial positions at journals like Social Science & Medicine . Her grants include funding from NSF, Bill & Melinda Gates Foundation, and EU Commission. Key areas of study include telemedicine, long-term care financing, and healthcare delivery in low-income regions.

Kevin Manaughمشاهده پروفایل

دانشیار

• Sustainable Transportation
• Spatial Justice
• Decision Making Processes
• +۳ مورد دیگر

Kevin Manaugh is an Associate Professor at McGill University, specializing in Urban Planning with a focus on sustainable transportation and spatial justice. His research examines how decision-making processes in urban development balance environmental, economic, and social equity goals, particularly through transport systems. He holds a PhD in Urban Planning from McGill University (2013). His key research interests include integrating social equity into land use policies, analyzing accessibility impacts on socioeconomically diverse populations, and studying behavior change related to sustainable transportation. Current projects explore equitable transit accessibility, responses to local mobility policies, and health/well-being effects of sustainable transport choices. Manaugh has published extensively on transportation equity, urban form analysis, and GIS applications. His work bridges theoretical frameworks with practical policy implementation, emphasizing participatory approaches to urban planning. Notable contributions include studies on pandemic street reallocation equity and cycling infrastructure prioritization strategies. His research has been supported by interdisciplinary collaborations and applied to Canadian urban contexts. Despite prolific output, Manaugh maintains an active engagement with public discourse on urban mobility challenges and equitable urban futures.

• Operations Management
• Supply Chain Management
• Sharing Economy
• +۶ مورد دیگر

Ming Hu is a Professor and University of Toronto Distinguished Professor of Business Operations and Analytics at Rotman School of Management, University of Toronto. He serves as Area Coordinator for the Operations Management & Statistics Area and holds editorial leadership roles including Editor-in-Chief of Naval Research Logistics and Associate Editor for multiple top journals. MS in Applied Mathematics, Brown University (2003) PhD in Operations Research, Columbia University (2009) His research focuses on sharing economy , social operations , and platform economics , examining how operational decisions can maximize societal benefit. Key areas include crowdfunding , two-sided markets , crowdsourcing , and group buying , with applications to DEI , sustainability , and AI-empowered operations . Recent work analyzes spatial operations in delivery systems, algorithmic fairness , and climate change adaptation in agricultural supply chains. His publications span top journals like Management Science and Operations Research , covering topics from blockchain traceability to quantum-inspired optimization . Scientific recognitions include: Wickham Skinner Early-Career Research Award (2016) Best Operations Management Paper in Management Science (2017) 2018 Poets & Quants Best 40 Under 40 MBA Professors As an Amazon Scholar (2022–) and Chair of Chain Analytics Institute (2023–), he bridges academic research with industry applications in AI-driven logistics and sustainable operations.

Natalie H. Britoمشاهده پروفایل

دانشیار

• Developmental Psychology
• Neurocognitive Development
• Early Childhood Development
• +۳ مورد دیگر

Natalie H. Brito is an Associate Professor of Applied Psychology at New York University (NYU), affiliated with the Steinhardt School of Culture, Education, and Human Development. Her research focuses on how early social and cultural contexts shape neurocognitive development in infants and toddlers, particularly in areas of attention, memory, and socio-emotional skills. Prior to NYU, she completed a postdoctoral fellowship at Columbia University Medical Center and was a Robert Wood Johnson Health and Society Scholar. Dr. Brito’s work bridges developmental psychology, neuroscience, and public policy, emphasizing the need for equitable environments that support healthy child development. She has received prestigious awards such as the APS Rising Star Award and NIH grants, reflecting her impactful contributions to understanding developmental trajectories. Her research also extends to policy implications, such as the effects of paid maternal leave on infant brain function and the role of structural inequities in maternal mental health. Key themes include early life stress, gut microbiome influences, and the neurobiological underpinnings of cognitive development. Dr. Brito has published extensively in journals like Child Development , Developmental Cognitive Neuroscience , and JAMA Psychiatry , with a focus on innovative methodologies (e.g., the OWLET gaze-tracking tool). She teaches courses on developmental psychology and the principles of applied psychology, fostering interdisciplinary approaches to human development. Her scientific accolades include recognition from the International Society of Developmental Psychobiology and the American Psychological Association, underscoring her leadership in advancing developmental science and equity-focused research.