Colin Raffel , currently an Associate Professor at the University of Toronto and Associate Research Director at the Vector Institute , is a leading researcher in machine learning and natural language processing . His career spans roles at Hugging Face (Faculty Researcher), Google Brain (Senior Research Scientist), and UNC Chapel Hill (Assistant Professor). Education: PhD in Electrical Engineering (Columbia), MA in Music/Science (Stanford), BA in Mathematics (Oberlin) Key affiliations: Google Brain (2016-2020), Hugging Face (2021-present), Vector Institute (2023-present) His research focuses on language model development , attention mechanisms , efficient machine learning , and music information retrieval . Recent work explores model merging , parameter-efficient fine-tuning , and data-constrained language models . Teaching : Has instructed courses at University of Toronto and UNC Chapel Hill on Neural Networks , Deep Learning , and Information Theory . Academic service includes organizing ICLR workshops and serving as Senior Area Chair for NeurIPS and EMNLP . Notable awards : NSF CAREER (2022), Caspar Bowden Award (2023), NeurIPS Outstanding Paper (2023) Key contributions : Core developer of WT5 , Git-Theta , and mir_eval software
Cheryl Gaimon holds the Esther and Edward J. Brown Chair and serves as a Regents' Professor at the Scheller College of Business, Georgia Institute of Technology. She is Faculty Director of the Management of Technology (MoT) Certificate Program, which she helped establish, and teaches across all academic levels including executive education. Professor Gaimon initiated the Operations Management Program and served as its first Area Coordinator for seven years. Her academic credentials include: Ph.D. in Operations Research from Carnegie Mellon University M.S. in Industrial Administration (Operations Management) from Carnegie Mellon University B.S. in Mathematics and Economics (Magna Cum Laude) from Brooklyn College, City University of New York Professor Gaimon's research centers on managing knowledge-based resources in technology-driven environments. Her work spans Innovation and Management of Technology , Knowledge Management and Outsourcing , New Product/Process Development , Alliances for Innovation , and Sustainability Research . She examines how firms navigate technological change through strategic resource allocation, knowledge transfer, and sustainable operations, with increasing emphasis on environmental strategies in recent years. Her publication trajectory reveals consistent focus on operations management within technological evolution—from foundational work on technology acquisition and capacity planning to contemporary studies on environmental strategies and multidisciplinary technology management. Key journals featuring her research include Management Science , Operations Research , and Production and Operations Management . Major recognitions include: Regents' Professor designation (2005) by the Georgia Board of Regents The 1999 Georgia Tech Research Award for doctoral student development Brady Family Award for Faculty Research Excellence (2014) Best Department Editor Award for POM (2024) POMS Fellow status and Distinguished Service Award (2009/2014) As an educator, she has mentored doctoral students and shaped curriculum through the MoT program. Her professional leadership includes serving as POMS President (2008-2009), founding co-President of the POMS College on Product Innovation and Technology Management, and editorial roles at top journals including Management Science and Production and Operations Management . Professor Gaimon directs the interdisciplinary Management of Technology Certificate Program, fostering cross-departmental collaboration for technology management research and education while advancing sustainability integration in operations.
Roberto Martin-Martin is an Assistant Professor of Computer Science at the University of Texas at Austin, where he leads the Robot Interactive Intelligence (RobIN) Lab. His research bridges robotics, computer vision, and machine learning to enable robots to operate autonomously in human-centric environments like homes and offices. Previously, he was a Postdoctoral Scholar at the Stanford Vision and Learning Lab working with Fei-Fei Li and Silvio Savarese, and an AI Researcher at Salesforce AI. Education: Ph.D. and M.Sc. in Robotics from Technische Universität Berlin (TUB), advised by Professor Oliver Brock B.Sc. from Universidad Politécnica de Madrid Dr. Martin-Martin's research focuses on developing AI algorithms that combine reinforcement learning and imitation learning with advanced planning and control to address core challenges in robot perception. His work spans mobile and whole-body manipulation, dexterous and contact-rich interactions, and long-horizon tasks in unstructured environments. He takes inspiration from human cognition through psychology and cognitive science to develop solutions for skills ranging from simple pick-and-place operations to complex tasks like cooking and furniture assembly. His recent publications demonstrate a strong trend toward enabling robots to learn from human demonstrations, particularly through video, and to safely adapt these demonstrations to their own morphology. There's significant emphasis on mobile manipulation, bimanual tasks, and developing hardware that supports robust robot learning through trial and error. His work shows increasing integration of large language models and vision-language models to enhance robot understanding and task execution. Scientific Awards: RSS Pioneer (2020) Winner of Amazon Picking Challenge (2015) RSS Best Systems Paper Award (2016) ICRA Best Paper Award IROS Best Mechanism Award Amazon Faculty Award AAAI Young Faculty IJCAI Early Faculty Nominated for Best Paper at IROS (2014, 2017) Dr. Martin-Martin advises PhD students including Arpit Bahety, who is working on mobile manipulation and learning. He serves as Chair of the IEEE Technical Committee on Mobile Manipulation and is a co-founder of QueerInRobotics. His research is supported by industry partnerships and academic funding sources that enable his lab to develop both hardware and software innovations in robotics. He directs the Robot Interactive Intelligence (RobIN) Lab at UT Austin, which takes a holistic approach to robot intelligence, developing both the hardware (like the BaRiFlex gripper) and software frameworks necessary for robots to learn from interaction. The lab's research addresses the full pipeline from perception to action, with particular emphasis on learning from human demonstrations, safe exploration, and adapting to novel objects and environments.
Haijun Xia is an Assistant Professor at the University of California, San Diego (UCSD), where he directs the Foundation Interface Lab and contributes to the Cognitive Science and Design Lab. His work focuses on Human-Computer Interaction (HCI) and Human-AI Collaboration , emphasizing the development of dynamic, malleable interfaces that integrate human cognition with intelligent systems to enhance thinking and working paradigms. Education: Bachelor's, Tsinghua University Master's and PhD, University of Toronto His research spans generative AI , interface design , and creative collaboration , with applications in data visualization, programming, and scholarly work. He advocates for treating information as a malleable material that can be flexibly manipulated by users and AI agents. Recent publications highlight advancements in: 2025 CHI Conference - Generative user interfaces, malleable overview-detail designs, and compositional structures for human-AI co-creation 2024 CHI Conference - Structured design space exploration with LLMs, ASCII diagram analysis, and adaptive presentation systems 2023 CHI/UIST Conferences - Data particle visualization, contextual logging tools, and metaphor generation for science communication Scientific recognitions include: Multiple Best Paper Awards and Honorable Mentions at CHI and UIST Hellman Fellowship and grants from NSF , Microsoft , Google , Meta , Apple , and Adobe He actively recruits undergraduate and graduate interns and has an upcoming postdoc position in early 2025 for researchers interested in foundational interface development.
Andrew Stephen is the L’Oréal Professor of Marketing and Deputy Dean for Faculty and Research at Saïd Business School, University of Oxford. He leads the Marketing faculty and directs the Oxford Future of Marketing Initiative, focusing on emerging technologies like AI and data-driven strategies in marketing, media, and advertising. His research explores digital marketing, consumer behavior, and the impact of new technologies, earning him recognition as a top global marketing scholar. His academic contributions span leading journals such as the Journal of Consumer Research and Harvard Business Review. He serves as editor of the Journal of Consumer Research, co-editor of the International Journal of Research in Marketing, and actively engages with industry through councils like the Mobile Marketing Association’s Brand Safety Council. Teaching responsibilities include marketing curriculum oversight and courses across MBA, Executive MBA, and DPhil programs, focusing on digital transformation, marketing analytics, and the future of marketing. His work bridges academic rigor with industry relevance, addressing challenges in tech-enabled marketing and global brand strategies. Awards: Top marketing academic in the UK (AMA), featured in Poets & Quants’ top 40 under 40, multiple research excellence awards. Labs/Initiatives: Oxford Future of Marketing Initiative, fostering collaborations with leading companies to tackle industry challenges. Grants/Advising: Extensive industry partnerships and academic grants not explicitly detailed in the text.
Panos Ipeirotis is a Professor at the Leonard N. Stern School of Business at New York University, affiliated with the Department of Technology, Operations, and Statistics. He also serves as the George A. Kellner Faculty Fellow and is associated with the Center for Data Science and Computer Science departments at NYU. PhD in Computer Science (Columbia University, 2004) MSc in Computer Science (Columbia University, 2001) BSc in Computer Engineering & Informatics (University of Patras, 1999) His research spans crowdsourcing, machine learning, human-AI collaboration, online labor markets, and social media analytics. He pioneered human-machine loop systems that combine human and machine intelligence to achieve superior outcomes. His work has applications in data quality assurance, visual media search (e.g., Google Project Glass), and economic valuation of user-generated content. Recent publications focus on algorithmic fairness in hiring systems, occupational segregation analysis, and theoretical advancements in crowdsourcing consensus mechanisms. Earlier work includes foundational studies on data quality in crowdsourcing platforms, economic impacts of product reviews, and query optimization for text-centric tasks. 2015 Lagrange Prize in Complex Systems NSF CAREER Award SIGKDD Test of Time Award (2020) Multiple Best Paper awards (WWW 2011, KDD 2008, SIGMOD 2006) He has received significant grants, including a $1.5 million Google Research Grant (2013) for integrating crowdsourcing with machine learning algorithms. His work bridges computer science, economics, and social psychology, with implications for policy-making and business strategy.
Bahar Asgari is an Assistant Professor in the Department of Computer Science at the University of Maryland, College Park. She holds appointments in CS, UMIACS, and ECE, and directs the Computer Architecture and Systems Lab (CASL). Her research focuses on domain-specific architecture design, near memory processing, and reconfigurable computing. Before joining UMD, she worked at Google, contributing to system optimization and memory utilization strategies. Education: Ph.D., Georgia Institute of Technology, 2021. Research Interests: Developing energy-efficient architectures for sparse problems, scientific computing acceleration, FPGA optimizations, and reconfigurable hardware systems. Her work addresses challenges in memory efficiency, parallelization, and hardware-software co-design across domains like machine learning and IoT. Key Awards: 2024 UMD Excellence in Teaching Award 2023 DOE Early Career Award Advising & Grants: Supervises 9 graduate students and leads projects sponsored by NSF, DOE, and industry partnerships. Her lab explores systolic arrays, near-data processing, and fault-tolerant computing. Labs/Teams: Directs CASL, which builds next-generation computing systems through hardware innovation and algorithm-architecture co-design.
Associate Professor Mark Humphery-Jenner is a distinguished faculty member at the University of New South Wales (UNSW) Business School, specifically within the School of Banking and Finance. With an exceptional academic pedigree including multiple PhDs from prestigious institutions worldwide, he has established himself as a leading researcher at the intersection of finance, law, and corporate governance. Dr. Humphery-Jenner's educational background demonstrates remarkable breadth and depth, featuring PhDs from UNSW, Tilburg University, and Leiden University, along with master's degrees from Columbia University and the University of Washington. His undergraduate achievements include a BCom with First Class Honours and University Medal, and an LLB with First Class Honours, both from UNSW. This multidisciplinary foundation spanning business, law, and finance informs his comprehensive research approach. His research spans corporate finance, venture capital, and law, with particular focus on how legal frameworks shape financial decision-making and corporate behavior. Humphery-Jenner has published extensively in top-tier finance journals including the Journal of Financial Economics, Journal of Financial and Quantitative Analysis, Review of Finance, and Journal of Corporate Finance, as well as leading management journals such as Strategic Management Journal and Journal of International Business Studies. His scholarly contributions address critical issues in executive compensation, securities litigation, corporate governance, and private equity markets. Analysis of his recent publications reveals a sophisticated research trajectory increasingly focused on the relationship between litigation risk and financial reporting practices, corporate governance mechanisms, and investor protection frameworks. His work demonstrates particular attention to Australian regulatory contexts while maintaining a strong international comparative perspective, especially regarding Asian capital markets and cross-border investment. With substantial industry experience including work in investment banking and consulting for hedge funds, Humphery-Jenner brings practical insights to his academic work. He has been teaching in various capacities since 2006 and has served as an assistant professor in finance since 2012, contributing significantly to business education at UNSW. His professional background enhances his ability to bridge theoretical research with real-world financial practice.
Gerald L. Neuman is the J. Sinclair Armstrong Professor of International, Foreign, and Comparative Law at Harvard Law School (HLS), where he serves as Director of the Human Rights Program. His expertise spans human rights, constitutional law, immigration law, and international legal frameworks. Previously, he taught at the University of Pennsylvania Law School (1984-1992) and Columbia Law School (1992-2006). Research Interests: Neuman's work focuses on: Human rights in populist and pandemic contexts Transnational constitutionalism Immigration law and extraterritorial constitutional rights Age discrimination as a human rights violation Impeachment's role in human rights protection Indirect discrimination analysis Selected Trends: His recent articles examine pandemic-era immigration policies ( Title 42 ), impeachment mechanisms for human rights violations, and age discrimination frameworks. Publications show consistent engagement with: Constitutional law intersections Comparative legal analysis Administrative law critiques Human rights treaty body applications Scientific Contributions: Neuman's work appears in leading journals like Harvard International Law Journal and Harvard Human Rights Journal . He has organized workshops on indirect discrimination related to: Sexual orientation/gender identity Chronological age Religious practice Disability rights Pandemic policy impacts He has served as a UN expert workshop organizer and contributed to international human rights literature through edited volumes and treaty analysis.
Subodha Kumar is the Paul R. Anderson Distinguished Chair Professor of Statistics, Operations, and Data Science at Temple University’s Fox School of Business. He serves as the Founding Director of the Center for Business Analytics and Disruptive Technologies and has a secondary appointment in Information Systems. His roles include Ph.D. Program Concentration Director for Operations and Supply Chain Management. With over 240 publications, he ranks #1 globally in Information Systems Research publishing and holds a robotics patent. His research focuses on AI, blockchain, healthcare analytics, and cybersecurity, with notable contributions to digital transformation and operations management. Awards include the INFORMS ISS Distinguished Fellow and POMS Fellow. He advises major journals like Production and Operations Management and organizes conferences like POMS 2018. Media mentions span NYT, WSJ, and CBS. Education: University of Washington faculty Texas A&M University faculty Research Interests: Dr. Kumar explores AI applications, blockchain in fintech, healthcare system optimization, and supply chain analytics. He investigates cybersecurity’s operational impacts and data mining strategies. His work bridges theory and practice, addressing challenges in digital transformation and platform economies. Publications Trends: Recent work emphasizes digital platforms (e.g., blockchain adoption, telemedicine impact), organizational behavior (real-time feedback systems), and healthcare operations (personalized treatment algorithms). He frequently collaborates internationally, with studies appearing in Management Science, Information Systems Research, and Decision Sciences. Awards & Recognition: Changjiang Scholars Chair (China) ISB Visiting Professorship POMS Executive Editor Grants & Labs: Secured NIH grants for health analytics projects. Leads Temple’s analytics center fostering industry partnerships. Active in editorial roles (e.g., Production and Operations Management Journal Deputy Editor). Teaching: Offers courses in data science, optimization methods, and innovation entrepreneurship at graduate/undergraduate levels.
Professor Sara Baker is a Professor of Developmental Psychology and Education at the University of Cambridge's Faculty of Education and a Fellow at Darwin College, where she served as Vice Master from 2021-2024. She is also a 2022 Senior Fellow in the Science of Learning with UNESCO-IBE/IBRO. Her work bridges cognitive science and educational practice, focusing on how children develop executive functions and self-regulation skills. Baker leads the Early Years Library project, co-founded the Research Centre for Play in Education, Development and Learning (PEDAL), and is a founding member of the Global Executive Functions Initiative. Sara Baker specializes in the science of learning, with research aimed at improving children's lives by identifying factors at home and school that support their agency over learning. Her work emphasizes developing executive functions and self-regulation through playful learning approaches. She uses lab-based experiments and collaborates with educators to translate cognitive science research into educational contexts. Her research spans multiple countries including the UK, USA, Mexico, Denmark, Slovakia, South Korea, Ghana, Rwanda, Nigeria, Kenya, South Africa, and more, reflecting a strong commitment to culturally relevant and globally applicable educational practices. Analysis of Professor Baker's recent publications reveals a strong focus on executive functions, self-regulation, and playful learning across diverse cultural contexts. Her work increasingly addresses cultural adaptation of assessment tools and educational practices, particularly for Global Majority countries. There's a clear trajectory from basic cognitive research toward practical applications in educational settings, with growing emphasis on teacher training, culturally relevant assessment, and the role of play in early childhood development. Her interdisciplinary approach connects developmental psychology, educational theory, and practical classroom applications. 2022 Senior Fellow in the Science of Learning with UNESCO-IBE/IBRO Professor Baker leads the doctoral program in the Faculty of Education and serves as an Academic Project Director in the School of Humanities and Social Sciences. She is the Cambridge academic lead on the Close the Gap partnership between Cambridge and Oxford, focused on postgraduate widening participation. Her research has been funded by prestigious organizations including the Newton Trust, Cambridge Humanities Research Grant, Economic and Social Research Council, LEGO Foundation, Nuffield Foundation, and Office for Students/Research England. She actively supervises doctoral students and seeks highly motivated candidates for October 2026 entry whose research aligns with her focus areas. Professor Baker co-founded and is actively involved with the Research Centre for Play in Education, Development and Learning (PEDAL), which investigates how children's play affects their development. She leads the Early Years Library project, a curated collection of evidence-based practices for early years educators, and is a founding member of the Global Executive Functions Initiative. Her work with the Connections international professional learning network focuses on self-regulation, while the Close the Gap project addresses widening participation in postgraduate education between Oxford and Cambridge.
Wim Gevers is a faculty member at the Université libre de Bruxelles (ULB) and leads the CS4S – Cognitive Control & Sleep laboratory within the CRCN research centre. His work bridges cognitive psychology, neuroscience and sleep research to understand how the brain exerts control over thoughts and actions and how sleep contributes to these processes. Research Interests Cognitive Control & Metacognition: Investigating how subjective experiences such as confidence and the "urge-to-err" guide strategic adjustments in behaviour. Working Memory & Ordinal Cognition: Examining how order information is maintained and manipulated, and how these processes relate to mathematical competence. Sleep, Memory & Decision Making: Exploring how sleep-dependent consolidation influences motor learning and decision strategies. Across his 2022–2025 publications a clear trend emerges: a focus on metacognitive monitoring —how humans evaluate their own cognitive states—and the role of emotional and temporal context in shaping those evaluations. Studies range from reaction-time introspection and confidence judgements in perceptual tasks to the impact of aging and depression on metacognitive accuracy. Doctoral Supervision & Mentoring Whitney Stee (PhD 2024) – Sleep-dependent structural brain reorganization & motor learning Gaia Corlazzoli (PhD 2024) – Subjective experience in decision-making Myrtille Dewulf (PhD 2023) – Ordinal coding mechanisms in working memory Rebeca Sifuentes-Ortega (PhD 2023) – REM sleep and memory reactivation All dissertations were defended at ULB, Faculté des Sciences psychologiques et de l’éducation, with Wim Gevers formally listed as Promotor . Laboratory & Collaborative Networks As head of CS4S, Gevers coordinates a multidisciplinary team that combines behavioural experimentation, EEG/MEG, computational modelling and sleep polysomnography. The lab is embedded in the larger CRCN ecosystem, fostering collaborations with groups such as CO3 (consciousness), LCLD (language & deafness), and UR2NF (neurofunctional imaging).
Adam Bonica is an Associate Professor in the Department of Political Science at Stanford University . His research integrates data science and politics , focusing on money in politics , campaigns and elections , judicial politics , and political methodology . Research Interests : Data Science, Political Ideology, Campaign Finance, Judicial Polarization, Quantitative Modeling Contact : Encina Hall West, Room 307, Stanford, CA 94305-6044 | Email : bonica@stanford.edu | Phone : (650) 725-7987 His work has been published in leading journals such as the American Journal of Political Science , Political Analysis , Journal of Economic Perspectives , Journal of Law, Economics, and Organization , and JAMA Internal Medicine . Bonica co-authored The Judicial Tug of War , which explores the politicization of the American judiciary. He has developed comprehensive databases like DIME (Database on Ideology, Money in Politics, and Elections) to advance research on political ideology and campaign finance. Recent publications include analyses of ideological persuasion in U.S. elections, judicial reform dynamics, and supervised machine learning applications in political methodology. His research spans topics such as clerk hiring as ideological indicators , professional networks in fundraising , and polarization trends among physicians and legal professionals .
Jeff Moher is an Associate Professor of Psychology and Co-Chair of the Department of Psychology at Connecticut College, where he has been teaching since 2017. He also serves as the Data, Information, and Society Pathway Co-Coordinator, demonstrating his leadership within the institution. His educational background includes a Ph.D. and M.A. from Johns Hopkins University and a B.S. from the University of Michigan. This strong academic foundation has prepared him for his research and teaching career in cognitive psychology. Moher's research focuses on cognitive psychology and cognitive neuroscience, particularly visual attention and cognition in action. His work investigates why distractions occur, when they are likely to arise, and what mechanisms humans can harness to avoid them. He has found that humans employ various cognitive mechanisms to minimize distractions based on explicit knowledge, task goals, object properties, and recent experience, though he has also discovered surprising limitations in attentional selection. His research is particularly relevant given that over 3,000 people are killed annually in the United States from distracted driving. His recent publications show a consistent trajectory examining attentional mechanisms, distraction, and visual processing across different contexts. His work frequently employs sophisticated methodologies to measure both cognitive and motor responses to distractions, revealing how seemingly minor distractions can accumulate to induce serious performance costs. Moher's research is currently funded by grants from the National Science Foundation and the National Institutes of Health, indicating the significance and quality of his work. He likely mentors numerous students through the department's research groups, contributing to their development as researchers. He directs the CAMELab (Center for Attention, Movement, and Embodied Learning), which utilizes multiple methodologies including eye-tracking, electroencephalography, three-dimensional reach-tracking, and psychophysics to approach questions about attention and distraction. Current projects in his lab explore why salient distractors cause people to give up quickly during visual search, the brain mechanisms involved in learning to ignore distractions, how internal distractions impact physical interactions with the world, and how hand movement paths reveal information about attentional processes.
Susanne Weis is a Research Professor and Group Leader of the 'Variability of the Brain' group at the Department of Brain and Behavior (INM-7), part of the Institute of Neuroscience and Medicine (INM) at Research Center Jülich GmbH. Her work focuses on understanding brain variability through advanced neuroimaging techniques and machine learning, with particular emphasis on sex differences, hormonal influences, and clinical applications in mental health. Her research interests include neuroimaging methodologies, machine learning applications in cognitive neuroscience, and the structural-functional relationships underlying brain variability. She investigates how factors like sex hormones and naturalistic stimuli (e.g., movies) affect brain connectivity and cognitive performance, aiming to improve diagnostic and predictive tools for disorders such as schizophrenia and Alzheimer’s disease. Publications highlight her contributions to developing datasets (e.g., SpEx), analyzing confound leakage in ML models, and exploring meta-analytic networks during naturalistic viewing. Her work bridges basic science and clinical impact, addressing challenges in interpreting neuroimaging data and advancing personalized medicine approaches. In her role as a group leader, Weis oversees research projects and collaborates with interdisciplinary teams. She is affiliated with the Helmholtz Association and contributes to the broader scientific community through her research in neuroimaging and computational neuroscience.
