Peter Nilsson is a Professor of Economics at the Institute for International Economic Studies (IIES) , Stockholm University. He also holds a guest professorship at Linnaeus University and serves as a research fellow at IFAU , Uppsala Center for Labor Studies , CESifo , and CEPR . Previously, he was a postdoctoral fellow at Stanford University and obtained his PhD from Uppsala University (2010). Research Focus: His work bridges Labor Economics , Health Economics , and Environmental Economics , analyzing how early-life exposures (alcohol, lead), workplace dynamics, and policy interventions (unemployment insurance, congestion pricing) shape long-term socioeconomic outcomes. Key themes include Environmental Health Impacts on Cognition and Crime Labor Market Responses to Insurance Policies Peer Effects in Workplace Behavior Policy Design for Social Equity Scientific Awards: Nilsson has been recognized through research fellowships at leading institutions and editorial roles, including Associate Editor at The Economic Journal since 2021. His work has been featured in American Economic Review , Journal of Political Economy , and NBER platforms. Key Contributions: He provided testimony for Connecticut’s HB-5045 to reduce childhood lead exposure and contributed to Sweden’s Corona Commission report on pandemic responses. His empirical methods combine natural experiments with administrative datasets to identify causal relationships in health, labor, and environmental economics.
Yonatan Bisk is an Assistant Professor at Carnegie Mellon University within the Language Technologies Institute (with courtesy appointment in Robotics Institute). His research bridges Natural Language Processing , Robotics , and Embodied AI , focusing on language grounding, theory of mind, and multimodal interaction. Education : Ph.D. in Computer Science from University of Illinois at Urbana-Champaign Postdoctoral Experience : USC ISI, University of Washington, Allen Institute for AI Industry Appointments : Microsoft Research, Meta AI His research emphasizes embodied language systems and social intelligence in AI . Recent projects include WebArena for autonomous agents, SOTOPIA for social reasoning, and HomeRobot for open-vocabulary manipulation. He leads the REAL Center (Robotics, Embodied AI, and Learning) to foster interdisciplinary collaboration. Key scientific awards include selection for the DARPA ISAT Study Group (2024). He teaches courses like "Talking to Robots" and "Multimodal Machine Learning" while serving as area chair/editor across NLP, Robotics, and ML communities.
Raul Astudillo Marban is a Postdoctoral Scholar Research Associate in the Department of Computing and Mathematical Sciences at Caltech, hosted by Professor Yisong Yue. He will join MBZUAI as a tenure-track Assistant Professor in August 2025. His research focuses on adaptive learning and decision-making in complex, data-intensive environments, with applications in personalized healthcare, engineering design, and scientific discovery. He earned his Ph.D. in Operations Research and Information Engineering from Cornell University under Professor Peter Frazier and holds an undergraduate degree in Mathematics from the University of Guanajuato and the Center for Research in Mathematics. His work integrates Bayesian optimization and machine learning to address real-world challenges such as protein engineering, plant breeding, and computational biology. Key contributions include steering generative models with experimental data, preferential multi-objective optimization, and cost-aware Bayesian strategies. He has received recognition as a Rising Star in Management Science and Engineering (Stanford) and a Rising Star in Data Science (University of Chicago/UCSD). Recent research highlights include optimizing protein fitness through generative models, active learning in directed evolution, and Bayesian optimization for budget allocation in agriculture. His publications span top venues like NeurIPS, Nature Communications, and TMLR. He actively recruits students/researchers for projects in machine learning and optimization.
Dr. Wei Peng is a Professor in the Department of Media and Information at Michigan State University, specializing in health communication technology design and human-computer interaction. Her research explores behavior change mechanisms through interactive media. Ph.D. in Communication from University of Southern California (2006) Key research areas include: Psychological and social effects of interactive media AI-driven health promotion systems Conversational agents for wellness Digital games for physical activity Mobile health applications Combating health misinformation through technology Her 2024-2021 publications demonstrate expertise in AI ethics, health gamification, and technology-based behavior change. Grant collaborations include: National Science Foundation (NSF) - Sensor-enabled family routines for child obesity prevention Robert Wood Johnson Foundation (RWJF) - Exergame development Scientific recognition includes multiple ICA Top Paper Awards and MSU Teacher-Scholar honors. She actively serves on editorial boards of: Journal of Communication Health Communication Games for Health Journal BMC Public Health Currently advising in AI applications for health misinformation and persuasive technology research.
Amit Kumar is the Jaswinder and Tarwinder Chadha Chair Professor in the Department of Computer Science and Engineering at IIT Delhi. His research focuses on combinatorial optimization, online algorithms, and algorithmic fairness. He has taught courses such as Approximation Algorithms (COL 754), Design and Analysis of Algorithms (COL 351), and Numerical Analysis (COL 726). His work spans theoretical computer science with applications to clustering, scheduling, and fairness in evaluation processes. Research Interests Kumar's research emphasizes developing efficient algorithms for online and dynamic settings, particularly in constrained optimization and biased evaluation systems. He explores theoretical foundations of clustering, load balancing, and resource allocation, with recent contributions to fair food delivery systems and coreset constructions. Publications His recent work includes advancements in online convex paging (STOC 2025), consensus clustering (SODA 2025), and fairness-aware algorithms (AAAI 2024). Over 70 papers across top venues like STOC, SODA, and ICML reflect his expertise in algorithm design and analysis. Awards Best Paper Award at ISAAC 2023 for 'Clustering What Matters in Constrained Settings' Teaching & Mentorship Kumar instructs graduate and undergraduate courses in algorithms, data structures, and numerical methods. He advises students through these courses and collaborates with researchers on NSF-funded projects related to approximation algorithms and streaming systems.
Professor Jennifer Whitty is an applied health economist at the University of East Anglia , affiliated with the Norwich Medical School and the Centre of Research Excellence in Telehealth . Her research bridges health economics, patient preferences, and health policy, with a focus on quality of life valuation and economic evaluation. Education: Doctor of Philosophy (Griffith University, 2008), Graduate Diploma in Clinical Pharmacy (University of Queensland, 2002), Bachelor of Pharmacy (University of Wales, 1992) Her work emphasizes person-centered methodologies , particularly discrete choice experiments, to evaluate patient and public preferences for healthcare delivery and outcomes. Key research areas include: Treatment burden and quality of life in chronic diseases like cystic fibrosis Economic evaluation of pharmaceuticals and health technologies Asset-based approaches to community health Priority-setting frameworks in health policy Prof. Whitty has secured over AU$27 million in research funding from organizations including the NHMRC and National Institute for Health and Care Research , and serves on editorial boards for Medical Decision Making and Applied Health Economics and Health Policy .
Nicole Koschate-Fischer is Professor and holds the GfK Chair for Marketing Intelligence at Friedrich-Alexander University Erlangen-Nuremberg (FAU), where she currently serves as Dean of Research at the Faculty of Business, Economics and Social Sciences. She is spokesperson for the interdisciplinary research focus "Customer Insights" and founding director of the Experimental Lab for Business Insights Nuremberg (ELAN). Previously, until September 30, 2024, she served as spokesperson for the Institute of Marketing and head of the Master's in Marketing program. Professor Koschate-Fischer earned her doctorate and habilitation from the University of Mannheim after completing a degree in business administration and psychology. Her academic journey includes membership in the interdisciplinary Collaborative Research Center "Concepts of Rationality, Decision Behavior, and Economic Modeling" at Mannheim, along with research stays as visiting scholar at University of Florida and University of Texas at Austin. She has held professorships at Technical University of Kaiserslautern and HEC Paris, and served as visiting professor at University of Vienna and Central University of Finance and Economics in Beijing. Research Interests Professor Koschate-Fischer's research spans customer insights , digital marketing , pricing and product management , and marketing analytics . Her work investigates consumer behavior in digital contexts, brand partnerships, life event impacts on purchasing decisions, and the psychological aspects of pricing. She employs experimental research methods and mediation analysis to understand causal relationships in consumer decision-making processes. Her publication record demonstrates consistent high-impact research in leading journals including Journal of Marketing, Journal of Marketing Research, and Journal of the Academy of Marketing Science. Recent work focuses on digital communication phenomena like emoji usage in electronic word-of-mouth, conversational agent interactions, and the application of behavioral pricing principles in charitable contexts. Professional Recognition Full member of the Bavarian Academy of Sciences and Humanities Member of the Board of Academic Trustees of the Center for Advanced International Marketing Knowledge (AiMark) Editorial board member of Journal of International Marketing Professor Koschate-Fischer regularly serves as reviewer for leading international academic journals and presents her research at both academic and practitioner-oriented conferences. Her work receives funding from organizations including the German Research Foundation (DFG), and she maintains active collaborations with renowned companies across various industries. She has directed the Experimental Lab for Business Insights Nuremberg (ELAN) since its founding, creating a hub for interdisciplinary customer insights research that bridges academic rigor with practical business applications.
Andrea Bajcsy serves as an Assistant Professor in the Robotics Institute and School of Computer Science at Carnegie Mellon University, leading the Interactive and Trustworthy Robotics Lab (Intent Lab). Her work focuses on enabling robots to safely interact with open-world environments through novel algorithms in control theory and machine learning. Her educational background includes a Ph.D. in Electrical Engineering & Computer Science from UC Berkeley under Anca Dragan and Claire Tomlin, followed by a postdoctoral position with Jitendra Malik and industry experience at NVIDIA's Autonomous Vehicle Research Group. Research centers on quantifying robot confidence, computing safe interaction policies for nuanced hazards (tearing, spilling, breaking), and aligning AI with human values. Key methodologies integrate optimal control, reinforcement learning, dynamic game theory, and deep learning, applied to robotic arms, quadrotors, quadrupeds, and autonomous vehicles. Core areas include safety for physical human-robot interaction, robot learning for manipulation, and world modeling. Recent publications (2024-2025) reveal a concentrated effort on uncertainty-aware safety mechanisms, out-of-distribution adaptation, and language-based safety specification. Her work increasingly bridges conformal prediction with interactive learning while leveraging vision-language models for real-time policy steering, as evidenced by multiple CoRL, RSS, ICRA, and ICLR acceptances. Scientific Awards: NSF CAREER Award (2025) Advises four active PhD students (Kensuke Nakamura, Ravi Pandya, Junwon Seo, Yilin Wu) and leads research funded by the NSF CAREER grant. Organizes community initiatives including the Northeast Systems and Control Workshop and ICRA workshops on Safely Leveraging VLMs in Robotics and Public Trust in Autonomy. Directs the Intent Robotics Lab, which develops theoretical frameworks and practical implementations for open-world robot safety. The lab maintains strong industry ties through NVIDIA collaborations and emphasizes real-world deployment across multiple robotic platforms.
Mark Yatskar is an Assistant Professor in the Department of Computer and Information Science at the University of Pennsylvania. His research focuses on the intersection of natural language processing, computer vision, and fairness in machine learning. He earned his PhD from the University of Washington under advisors Luke Zettlemoyer and Ali Farhadi, and previously worked as a Young Investigator at the Allen Institute for Artificial Intelligence. Education: PhD in Computer Science, University of Washington (Advisor: Luke Zettlemoyer & Ali Farhadi) Research Interests: Yatskar's work explores how language can structure visual perception and mitigate human biases in machine learning systems. Key themes include: Natural language as a scaffold for visual intelligence Bias characterization and control in machine learning systems His lab currently investigates projects like language-guided bottlenecks, annotator cognitive heuristics, and gender bias amplification. Teaching: CIS 5300: Computational Linguistics (2021-2024) CIS 7000: Language and Vision (2020) CIS 6300: Efficient NLP (2023, 2025) Awards: Best Paper Award at EMNLP (Gender Bias Amplification Research) Advising & Grants: Yatskar advises a team of PhD/Master's students and actively seeks motivated researchers. His group has explored funding in areas like interpretable AI, multimodal reasoning, and dataset bias mitigation. Labs/Teams: Leads the Penn NLP & Vision Lab, focusing on projects like MolMo/PixMo open models, ViUniT visual unit tests, and bias mitigation frameworks.
Atsuko Tanaka is an Associate Professor in the Department of Economics at the University of Calgary. Her research focuses on labor markets, health economics, and public policy, particularly examining topics such as female labor supply, skill investment, and pension reforms. She holds a Ph.D. in Economics from the University of Wisconsin-Madison (2013), alongside advanced degrees from Cornell University and the University of Tokyo. Education Ph.D. Economics, University of Wisconsin-Madison (2013) M.S. Economics, University of Wisconsin-Madison (2010) M.S. Applied Economics and Management, Cornell University (2007) B.A. Agricultural Economics, University of Tokyo (2004) Research Interests Tanaka’s work explores how health shocks, financial constraints, and policy interventions influence labor market outcomes. She investigates topics such as post-educational skill accumulation via college loans, strategic medical treatment choices under reimbursement reforms, and the macroeconomic effects of pension system transitions. Her research combines rigorous econometric methods with real-world administrative data to inform evidence-based policy. Awards and Grants SSHRC Connection Grant (2022, co-PI: Apostolos Serletis) National Science Foundation Extreme Science Grant (2021) SSHRC Insight Development Grant (2016) Susan Jane Blake Kocin Award, University of Wisconsin-Madison (2011) Grants and Collaboration Her research has been supported by major grants, including SSHRC and NSF funding. She collaborates with scholars on projects like analyzing physician behavior under reimbursement reforms, auditing firm dynamics, and international aid allocation strategies. Her work bridges theoretical models with empirical evidence to address complex socio-economic challenges.
Hoda Heidari is the K&L Gates Career Development Assistant Professor in Ethics and Computational Technologies at Carnegie Mellon University (CMU), with joint appointments in the Machine Learning Department and the Institute for Software, Systems, and Society. She is affiliated with the Human-Computer Interaction Institute and the Heinz College of Information Systems and Public Policy, and co-leads the university-wide Responsible AI Initiative and K&L Gates Initiative for Ethics and Computational Technologies. Education: PhD in Computer and Information Science (University of Pennsylvania), MSc in Statistics (Wharton School) Her research focuses on the Ethical, Societal, and Policy Implications of AI , particularly fairness and accountability in high-stakes domains. Her work includes evaluating risks/benefits of general-purpose AI, human-AI decision-making systems, and AI governance frameworks. She has received multiple awards, including best paper honors at AIES, FAccT, and SAT-ML. Her research is supported by the NSF Program on Fairness in AI, PwC, CyLab, Meta, and J. P. Morgan. Recent Publications examine generative AI safety, fairness measurement, AI incident documentation, and ethical governance. Her teaching includes courses on Responsible AI, ML Ethics, and Societal Decision-Making, with a focus on preparing students to critically analyze AI's societal impact. Scientific Awards: Best Paper (AIES 2024, FAccT 2021, SAT-ML 2023), Exemplary Track Award (EC 2021) Grants: NSF, PwC, CyLab, Meta, J. P. Morgan She advises doctoral students and postdocs across CMU departments and collaborates with interdisciplinary teams. Her service includes organizing AI safety workshops and advising on NIST guidelines for AI red-teaming.
Navid Azizan is the Alfred H. (1929) and Jean M. Hayes Career Development Assistant Professor at Massachusetts Institute of Technology (MIT), holding dual appointments in the Department of Mechanical Engineering (in Control, Instrumentation & Robotics) and the Schwarzman College of Computing's Institute for Data, Systems & Society (IDSS). He is also a Principal Investigator in the Laboratory for Information & Decision Systems (LIDS), and a faculty member of the MIT Statistics and Data Science Center, the Center for Computational Science and Engineering, and the Operations Research Center. Dr. Azizan received his PhD in Computing and Mathematical Sciences from the California Institute of Technology (Caltech) in 2020, his MSc in Electrical Engineering from the University of Southern California in 2015, and his BSc in Electrical Engineering with a minor in Physics from Sharif University of Technology in 2013. Prior to joining MIT, he completed a postdoc at Stanford University's Autonomous Systems Laboratory and was a research scientist intern at Google DeepMind. His research spans the intersection of machine learning, systems and control, mathematical optimization, and network science. Dr. Azizan's work focuses on developing principled learning and optimization algorithms for reliable intelligent systems, with applications to autonomy and sociotechnical systems. His research has significant implications for creating trustworthy AI systems that can operate effectively in complex, uncertain environments. Dr. Azizan's recent publications demonstrate a strong focus on uncertainty quantification, reliable AI systems, constrained optimization, and control-oriented learning. His work bridges theoretical foundations with practical applications, particularly in autonomous systems where safety and reliability are paramount. His research group has made notable contributions to areas including neural network verification, multi-agent reinforcement learning, and adaptive inference techniques for large language models, with several papers featured on MIT News and selected for oral presentations at top conferences. Alfred H. (1929) and Jean M. Hayes Career Development Professorship (2025-present) Frank E. Perkins Award for Excellence in Graduate Advising (2025) List of Outstanding Academic Leaders in Data from the CDO Magazine (2024, 2023) Amazon Science Hub Research Award (2023) Outstanding UROP Faculty Mentor (2023) Esther and Harold E. Edgerton (1927) Career Development Chair (2022-2025) Information Theory and Applications (ITA) Gold Graduation Award (2020) Dr. Azizan has been recognized for his excellence in graduate advising, receiving the Frank E. Perkins Award for Excellence in Graduate Advising in 2025. During the pandemic, he founded and co-organized the 'Control meets Learning' virtual seminar series, connecting researchers across disciplines. His work has attracted significant research funding from industry partners including Google, Amazon, and MathWorks, supporting both fundamental research and practical applications in reliable intelligent systems. The Azizan Lab at MIT brings together researchers from mechanical engineering, computer science, and applied mathematics to tackle challenges at the intersection of learning and control. The lab emphasizes both theoretical foundations and practical implementations, with a particular focus on developing algorithms that provide guarantees of performance and safety. Current research directions include uncertainty quantification in AI systems, constrained optimization for neural networks, and control-oriented learning for autonomous systems, with applications spanning robotics, transportation, and complex sociotechnical systems.
Dr. Metin Uyanik is a Senior Lecturer at the School of Economics, The University of Queensland. He holds a PhD from Johns Hopkins University (2016) and previously worked as a Postdoctoral Research Fellow at the University of Rochester's Wallis Institute of Political Economy. His research focuses on Economic Theory, Game Theory, Political Economy, Computational Economics, and Mathematical Economics. His work has been published in top-tier journals such as Economic Theory , Games and Economic Behavior , and Journal of Mathematical Economics . Education: Bachelor of Economics, Bogazici University Masters (Research) of Economics, Koc University Doctor of Philosophy, The Johns Hopkins University Research Interests: Dr. Uyanik's research bridges theoretical and applied economics, emphasizing foundational mathematical approaches. His work explores general equilibrium theory, discontinuous games, topological methods in economics, and welfare economics. Key themes include the analysis of non-convex economies, fixed-point theorems, and the integration of axiomatic frameworks with behavioral assumptions. Teaching: He teaches Advanced Microeconomics, Economics for Commerce, and Introduction to Strategic Thinking at UQ. His pedagogical focus includes mathematical rigor and practical applications of economic theory. Collaborations & Future Work: Collaborations with scholars like M. Ali Khan and Richard P. McLean highlight his engagement with complex theoretical frameworks. Ongoing projects include studies on large production economies, myersonian common knowledge, and computational methods in equilibrium analysis.
Professor Christopher Carman is the Stevenson Professor of Citizenship at the University of Glasgow, holding a PhD from the University of Houston. He has served in leadership roles including Head of Subject (Politics & International Relations), Head of the School of Social and Political Sciences, and Deputy Head of the School. His research focuses on political representation, electoral processes, public opinion, and Scottish politics, with notable contributions to studies on the Scottish Parliament and rural-urban political divides. Carman has led the Scottish Election Study (SES) since 2011 and co-leads the NORFACE-funded RUDE project on European rural-urban dynamics. He also contributes to the Glasgow-Nankai Joint Graduate School and the Stevenson Trust, fostering citizenship education and democratic research. Education: PhD in Political Science, University of Houston (2000). Previous academic roles include professorships at the Universities of Strathclyde and Pittsburgh. Research Interests: Political representation alternatives (e.g., public petitions systems), electoral behavior, Scottish and UK politics, direct democracy, and comparative legislative politics. Recent work addresses rural-urban divides in Europe and political compromise in democratic systems. Key Projects: Scottish Election Study (SES), Rural and Urban Divide in Europe (RUDE), and studies on political scandals and multilevel governance. His publications span electoral studies, comparative politics, and political behavior, with a focus on institutional trust and democratic engagement. Grants and Funding: ESRC and NORFACE grants support his research. The Stevenson Trust supports his work on citizenship education and public lectures.
Prof. Mark Heitmann is a Professor of Marketing & Customer Insight at the University of Hamburg Business School. He holds a visiting appointment at Nova School of Business and Economics. His research focuses on AI-driven marketing strategies, social media analytics, brand equity, and consumer decision-making. He has held academic roles at institutions including the University of St. Gallen and Christian-Albrechts-University in Kiel before joining Hamburg in 2011. Academic Career: Holds a PhD (2004) and post-doctoral Habilitation (2007) from the University of St. Gallen. Visiting researcher at Columbia University and the Max Planck Institute for Human Development. Research Interests: Applications of artificial intelligence in marketing Social media and digital transformation Ethical consumer behavior Brand self-expression and visual design Marketing technology (MarTech) innovations Key Achievements: Over 20 peer-reviewed publications in top journals like Journal of Marketing Research and Harvard Business Review . Award-winning research includes the MSI/H. Paul Root Award and IJRM-EMAC Best Article Award. Active in translating research into scalable commercial solutions through software-as-a-service ventures. Team & Collaborations: Leads a research team including M.Sc. candidates Sammar Rath, Julia Rosada, Maximilian Witte, Tijmen Jansen, Claus Hegmann-Napp, and Magdalena Heynicke. Engages in interdisciplinary projects with industry partners.
