Wei Xu is an Associate Professor at Georgia Institute of Technology's College of Computing and School of Interactive Computing, with affiliations to the Machine Learning Center. Their research bridges machine learning, natural language processing, and social media with focus areas in large language models, cultural bias mitigation, multilingual capabilities, and human-AI collaboration in text evaluation. NSF CAREER and Google Academic Research Award recipient Director of NLP X Lab PhD from New York University, BSMS from Tsinghua University Research interests span: Multilingual Multicultural LLMs addressing representational gaps and cultural adaptation in language models (NAACL 2025, ACL 2024); Robustness and Reasoning through dynamic AGI evaluations (ACL 2024, EMNLP 2024); Interdisciplinary NLP applications in security, healthcare, and law (EMNLP 2024, ACL 2024). Recent publications focus on multilingual alignment (NAACL 2025), privacy risk estimation (arXiv 2025), cultural bias analysis (ACL 2024), and medical text simplification (EMNLP 2024). Key themes include bias mitigation, multimodal processing, and practical LLM evaluation. Scientific Awards : NSF CAREER, Google/Sony/Criteo research awards, ACL'24 Best Social Impact Award, COLING'18 Best Paper Advising 15 PhD/MS/BSMS students including Yao Dou (human-centered LLM evaluation), Tarek Naous (multilingual LLMs), and alumni like Chao Jiang (Apple AI/ML) and Yang Chen (NVIDIA research scientist). Teaches graduate courses on NLP and LLMs.
Abhijit Banerjee is a Professor in the Department of Economics at the Massachusetts Institute of Technology (MIT). His research focuses on development economics, public health policy, and social protection programs, particularly addressing poverty and inequality in low- and middle-income countries. He has conducted large-scale experiments evaluating interventions such as conditional cash transfers, universal basic income, and healthcare policies. Key areas of interest include the design and implementation of anti-poverty programs, behavioral economics, and the long-term health impacts of infectious diseases like COVID-19. His work often integrates experimental methods to assess policy effectiveness, with contributions to global health studies and economic development strategies. Notably, his research on the RECOVERY trial evaluates treatments for hospitalized COVID-19 patients, while other studies explore financial spillover effects of electronic government transfers in Indonesia and savings behavior interventions in Chile. Banerjee has collaborated on projects analyzing post-COVID-19 health outcomes, labor market dynamics in India, and the role of trusted messengers in public health communication during crises. Despite the breadth of his contributions, specific details about his educational background, grants, or lab affiliations are not explicitly provided in the source text.
Yuri Bobbert is a Professor of Information System Science at Antwerp Management School (AMS), part of the University of Antwerp. He holds dual PhDs from Radboud University and the University of Antwerp, focusing on IT performance measurement. His career includes roles as Global Group CSO of NN Group and UWV (Government), leading cybersecurity integrations during mergers like NN Group and Delta Lloyds. As CEO of B-ABLE (IT consultancy), he developed cybersecurity frameworks. Currently, he advises on NIS2 compliance and Zero Trust strategies. His research spans cybersecurity ROI, regulatory frameworks (e.g., NIS2), and leadership in digital security. Education PhD in Information Systems (Radboud University) PhD in Cybersecurity (University of Antwerp) Research Interests Cybersecurity governance and compliance ROSI (Return on Security Investment) CISO leadership and board communication Zero Trust architecture Risk quantification in digital ecosystems Publications & Books Authored books: Strategic Approaches to Digital Platform Security Assurance , Cybersecurity in 60 Minutes , and Digital Security Leadership Over 100 peer-reviewed publications on cybersecurity performance and governance Grants & Awards Recipient of NIS2 implementation research grants Contributor to EU cybersecurity policy discussions Labs & Teams Leads AMS cybersecurity education programs and collaborates with ON2IT on global cybersecurity strategies.
Robert JOLIET is an Associate Professor of Finance at IÉSEG School of Management in France. He holds a Ph.D. in Economics and Management from HEC-ULg Management School (Belgium) and has held various academic leadership roles, including Director of Academic Development and Academic Director of the PGE (MSc in Management). His research focuses on finance, portfolio management, SRI (Socially Responsible Investing), and corporate finance, with a particular emphasis on international expansion, capital structure, and sustainable investment strategies. Education: 2008: Ph.D. in Economics and Management, HEC-ULg Management School, Belgium 2004: Master of Advanced Studies (DEA), Management Sciences (Finance), University of Liège, Belgium 2002: Master of Science in Business Engineering (Finance), University of Liège, Belgium Research interests span SRI fund dynamics, corporate social responsibility valuation, international debt policies, and market liquidity. Notable contributions include analyzing the impact of SRI mutual funds on corporate governance and environmental practices, and exploring the stability of sovereign debt structures in the Eurozone. Awards include the 2005 FORTIS Award (Third Prize) and the 2003 E.G. de Barsy Doctoral Fellowship. He has published extensively in journals like Economics Letters and Journal of Banking & Finance . Academic leadership roles include directing programs and departments at IÉSEG, alongside coordinating the Finance Track and managing academic development initiatives. His teaching focuses on financial data analysis, active portfolio management, and investment strategies in capital markets. He is a member of the LEM (Laboratoire d'Économie Moderne) research group and contributes to interdisciplinary research in finance and economics.
Arman Cohan is an Assistant Professor in the Department of Computer Science at Yale University, where he leads the Yale NLP Lab since its founding in January 2023. His research spans natural language processing and machine learning with emphasis on language modeling, representation learning, retrieval systems, and specialized domain applications including scientific discovery and AI for science. His primary research interests include: Natural Language Processing Machine Learning Large Language Models Information Retrieval AI for Science Scientific Problem-Solving Recent publications (2025) demonstrate intense focus on evaluating and advancing LLM capabilities across multimodal reasoning, scientific claim verification, financial domain applications, and biological modeling. The lab consistently produces high-impact work accepted at top-tier conferences including ACL, EMNLP, and ICLR, with 11 papers at ACL 2025 alone. Scientific awards include: Best Paper Award at AI4Research Workshop (IJCAI 2024) Outstanding Paper Award at EACL 2023 Best Paper Award at ACL 2024 for Olmo language model research Professor Cohan actively advises PhD students including Kaili Liu, Jacob Dunefsky, Alan Li, Yilun Zhao, and has graduated researchers such as Linyong Nan (now at Zoom) and Ansong Ni (now at Meta). The lab maintains strong industry partnerships and receives substantial research funding as evidenced by its prolific output and conference presence. The Yale NLP Lab hosts the annual New England NLP Workshop and regularly features speakers from leading institutions including Meta AI, Allen Institute for AI, and DeepMind, fostering a collaborative environment for advancing NLP research.
Sean Cao serves as Associate Professor (with tenure) at the Robert H. Smith School of Business, University of Maryland, where he is Director and Co-founder of the AI Initiative for Capital Market Research. He also holds an affiliation as professor at Harvard Business School's D 3 Institute. His academic journey began with a Ph.D. from the University of Illinois at Urbana-Champaign. Dr. Cao's research focuses on the intersection of artificial intelligence and capital markets, with particular expertise in how machine learning transforms financial analysis, corporate disclosure practices, and investment decision-making. His work examines the evolving relationship between human analysts and AI systems, blockchain applications in financial reporting, and the strategic adaptation of corporate communications for machine readership. He has pioneered research on the "AI divide" among investor groups and developed frameworks for human-AI collaborative stock analysis. His publication portfolio spans top journals including Journal of Financial Economics, Review of Financial Studies, Journal of Accounting Research, and Management Science. The research demonstrates consistent thematic progression toward increasingly sophisticated AI applications in finance, with recent work exploring distributed ledger technologies for auditing, machine learning for extracting private information from disclosures, and the economics of greenwashing in ESG funds. His studies frequently combine textual analysis with traditional financial metrics to uncover novel market insights. Fama-DFA Prize from Journal of Financial Economics for best paper in capital markets and asset pricing Michael J. Brennan Award from Review of Financial Studies Deloitte Initiative for AI and Learning award for developing trustworthy AI for social equity PanAgora Asset Management's Dr. Richard A. Crowell Memorial Prize Multiple best paper awards from Midwest Finance Association, Global AI Finance Conference, and Asian Finance Association Dr. Cao has delivered over 200 invited research talks at major institutions including the Central Bank of Japan, Central Bank of Thailand, and U.S. Securities and Exchange Commission. He serves as Guest Associate Editor for Management Science and has co-chaired Review of Financial Studies conferences on FinTech and Machine Learning. His educational initiatives include a widely adopted free AI textbook for finance and accounting that has been implemented at universities worldwide including Indiana University, UT Dallas, and University of Minnesota. As Director of the AI Initiative for Capital Market Research, Dr. Cao leads a multidisciplinary team exploring practical AI applications in finance. The initiative has secured significant funding including a $150,000 grant from GRF CPAs & Advisors. His research group maintains strong industry connections through partnerships with regulatory bodies, financial institutions, and technology companies, facilitating the translation of academic research into practical financial applications.
Robert Ghrist is the Andrea Mitchell University Professor at the University of Pennsylvania with dual appointments in the Department of Mathematics and the Department of Electrical and Systems Engineering. He serves as Associate Dean for Undergraduate Education for Penn Engineering. His educational background includes a B.S. in Mechanical Engineering from the University of Toledo (1991), and M.S. and Ph.D. degrees in Applied Mathematics from Cornell University (1994, 1995). Ghrist's research bridges pure and applied mathematics, focusing on applied algebraic topology , dynamical systems , and geometric methods in data science. His work extends to network theory, topological data analysis, and computational geometry, with applications spanning robotics, neuroscience, and social dynamics. Key innovations include developing sheaf-theoretic approaches for networked systems and persistence homology techniques for high-dimensional data. Analysis of his recent publications reveals a strong emphasis on lattice-theoretic frameworks , topological robotics , and network dynamics , with emerging applications in neural data interpretation and geometric computing. His research consistently integrates category theory with real-world engineering challenges. Significant scientific recognition includes: Presidential Early Career Award (PECASE, 2004) Scientific American 'Top 50' Research Leader (2007) Mathematical Association of America's Chauvenet Prize (2013) University of Pennsylvania Lindback Award for Distinguished Teaching (2015) DoD National Security Science and Engineering Faculty Fellowship (NSSEFF, 2015) Ghrist leads multiple federally funded research initiatives supported by AFOSR, DARPA, NSF, and ONR. He directs the development of educational tools including the Calculus BLUE/GREEN Project video series and custom GPTs for mathematical pedagogy. His open online courses have reached over 100,000 learners globally.
Jiaxuan You is an Assistant Professor at the Siebel School of Computing and Data Science, University of Illinois at Urbana-Champaign, leading the U Lab focused on achieving Artificial General Intelligence (AGI) in digital environments. His research spans graph neural networks (GNNs), relational data, foundation models, and machine learning systems. PhD and MS in Computer Science from Stanford University (2021) Developed GraphGym and PyTorch Geometric (PyG) for graph learning Core member at Kumo AI (2021-2023) His research explores: Graph-enhanced LLMs: Integrating relational structures into foundation models AGI Development: Self-optimizing AI agents and tool utilization ML Systems: Scalable architectures and redundancy-free computation Interdisciplinary Applications: Financial networks, crop yield prediction, and metro systems Recent publications focus on temporal reasoning, multi-agent dynamics, and hybrid architectures for LLMs. He actively develops open-source tools like DBGYM and GraphRouter. Scientific recognition includes: JPMC PhD Fellowship Baidu Scholarship Best Student Paper at AAAI 2017 World Bank Big Data Innovation Challenge winner He mentors PhD and intern students, emphasizing machine learning systems expertise. His lab collaborates on AGI workshops (e.g., ICLR 2024) and industry projects.
Marlon Dumas is a Professor of Information Systems at the University of Tartu's Faculty of Science and Technology, with a 20-year academic career spanning Estonia and Australia. He holds a PhD in Computer Science from the University of Grenoble 1, France, and has served as Head of Chair and Programme Director in Software Engineering programs. Specializes in Business Process Management (BPM) and Process Mining Current research focuses on prescriptive process monitoring, simulation modeling, and data privacy Recipient of 25+ scientific awards, including multiple Test of Time Awards and the Estonian National Research Award in Technical Sciences Editorial leadership: Area Editor for Information Systems (Elsevier) and ERC Starting Grant Panel Chair His work bridges theoretical advancements in BPM with practical applications in financial services and anti-money laundering. He has developed tools like SIMOD, Kronos, and Kairos for process optimization and analysis. His research integrates AI/ML techniques (reinforcement learning, causal inference) with traditional process modeling. Key trends in his recent publications include: Prescriptive monitoring systems combining causal inference and machine learning Privacy-preserving process mining techniques (differential privacy, anonymization) Resource availability modeling and multi-objective process optimization LLM applications for process analysis and intervention policies Scientific honors include: 2024 BPM Best Paper & Prototype Awards 2023 ICPM Best Prototype Award 2019 ERC Advanced Grantee 2017 Estonian National Research Award in Technical Sciences 2019 MODELS Test of Time Award 2017 BPM Best Prototype Award He has mentored PhD candidates as thesis examiner and contributed to 30+ conference program committees, including General Co-Chair roles at ESEC-FSE 2019 and CAiSE 2018. His work has been supported by European Research Council grants and Estonian Science Foundation projects.
Gilbert Fridgen is Full Professor in Digital Financial Services and holder of the PayPal-FNR PEARL Chair at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT). He leads the FINATRAX research group focusing on blockchain, digital identity, and sustainable digital solutions. His research explores decentralized technologies in finance, energy systems, and public administration. Current projects investigate blockchain applications in industrial demand response, NFT markets, EU digital identity wallets, and DeFi institutional adoption. Prof. Fridgen examines the intersection of technology with regulatory frameworks and user behavior in energy and financial systems. He collaborates extensively with industry partners including PayPal and Spuerkeess. Prof. Fridgen actively contributes to EU digital policy discussions, particularly regarding the European Digital Identity Wallet framework and decentralized finance governance.
Mohammad Saifur Rahman is the Daniels School Chair in Management and a Professor of Management Information Systems at the Mitch Daniels School of Business, Purdue University. Previously, he was an Associate Professor at the Haskayne School of Business, University of Calgary. His academic journey includes significant leadership roles such as co-chairing the Conference on Information Systems and Technology (CIST) in 2013 and serving as president of the INFORMS eBusiness Society in 2014. Currently, he serves as an associate editor for both Management Science and Information Systems Research (ISR). Ph.D. in Management Information Systems, Krannert School of Management, Purdue University (2008) MBA in Management Information Systems, Southern Illinois University (2004) BS in Computer Science, Southern Illinois University (2002) Rahman's research primarily focuses on the economic implications of digital transformations. His work examines how digitization affects consumer behavior, market structures, and business strategies across various industries. He investigates the value of digital traces in driving consumer behavior and improving decision-making, particularly in omnichannel retail environments. His research on the sharing economy has revealed important insights about economic disparities, showing how platforms like Airbnb provide economic benefits to predominantly white neighborhoods while failing to generate similar spillover effects in predominantly Black or Hispanic neighborhoods. His recent publications reveal a consistent focus on the intersection of technology, economics, and social impact. Rahman's work frequently examines how local market structures interact with digital platforms to create or exacerbate economic inequalities. His research spans multiple disciplines including information systems, economics, marketing, and operations management, with a particular emphasis on empirical studies using real-world data from major companies like Walmart and Cisco. CICP Faculty Commercialization Award (2020) INFORMS Sandy Slaughter Early Career Award (2018) World's Top 40 Business School Professors Under 40 by Poets and Quants (2017) Jay N. Ross Young Faculty Scholar Award (2015) Dean's Award for Outstanding Research Achievement (University of Calgary, 2014) Rahman has secured substantial research funding from organizations including Social Sciences and Humanities Research Council (SSHRC), Adobe Systems ($50,000 grants in 2017 and 2020), Trask Innovation Fund ($21,218), and NSF I-Corps ($50,000). He has advised numerous PhD students and collaborated with industry partners to translate research into practical applications. Rahman co-founded RightFit Analytics, a precision health analytics solution that utilizes AI to learn success patterns in healthcare. He has organized significant academic events including the Krannert-Walmart Data Dive (believed to be the first data dive on a college campus) and the Dawn or Doom Data Dive in cooperation with Cisco. Rahman actively engages with industry through consulting and collaborative research projects. His work with Walmart, Cisco, and other major corporations demonstrates his ability to bridge academic research with practical business applications. He has been particularly active in studying how AI and big data analytics can be leveraged to improve business decision-making while addressing potential negative consequences like algorithmic bias and economic inequality.
Antonio Rangel is the Bing Professor of Neuroscience, Behavioral Biology, and Economics at the California Institute of Technology (Caltech), where he also serves as Head Faculty in Residence. He is a faculty member in the Division of Humanities and Social Sciences (HSS) with research focusing on the computational and neurobiological basis of value-based decision-making. Dr. Rangel received his educational training at prestigious institutions: B.Sc. from Caltech in 1993 M.S. from Harvard University in 1996 Ph.D. in 1998 Professor Rangel's research lies at the intersection of neuroscience, economics, and psychology, with a focus on understanding how the brain makes decisions. His work investigates the neural mechanisms underlying value computation, choice processes, self-control, and social decision-making. Using a multidisciplinary approach that combines functional magnetic resonance imaging (fMRI), eye-tracking, computational modeling, and behavioral experiments, his lab has made significant contributions to the field of neuroeconomics. His research has revealed how value signals are represented in the brain, how attention influences choice, and the neural basis of self-control failures. Professor Rangel has pioneered methods for studying decision processes with high temporal resolution using eye-tracking data, demonstrating how fixation patterns relate to value computations and choice outcomes. His work spans from theoretical frameworks of value-based decision-making to practical applications in behavioral public economics. Professor Rangel's work has been recognized with prestigious awards: 2019 NOMIS Distinguished Scientist Award 2018 Fellow of the Association for Psychological Science As an academic leader, Professor Rangel has mentored numerous students and researchers who have gone on to make their own contributions to neuroscience and economics. His lab, the Rangel Neuroeconomics Laboratory at Caltech, serves as a hub for interdisciplinary research, bringing together students and scholars from neuroscience, economics, psychology, and computer science. The lab has received significant funding to support its research on the neural basis of decision-making, including support from the NOMIS Foundation. The Rangel Neuroeconomics Laboratory is equipped with state-of-the-art facilities including fMRI analysis capabilities, eye-tracking systems, and computational resources for modeling decision processes. The lab fosters a collaborative environment where researchers apply methods from experimental economics and cognitive neuroscience to unravel the complexities of human decision-making.
Felipe Csaszar is a Professor of Strategy and Chair of the Strategy Department at the University of Michigan's Ross School of Business. His research focuses on decision structures' impact on innovation, financial performance, and social outcomes, with particular attention to cognitive frameworks, organizational processes, and AI's role in decision-making. He holds a PhD and MA from the Wharton School, University of Pennsylvania. Education: PhD in Strategy, University of Pennsylvania (2009) MA in Strategy, University of Pennsylvania (2007) Research Interests: Strategic decision-making under AI integration Cognitive and structural drivers of innovation Organizational decision processes and design Formal modeling and empirical strategy research Editorial Roles: Senior Editor, Strategy Science and Management Science Former Editor, Organization Science Co-editor, Handbook of AI and Strategy Professional Experience: Prior role: Assistant Professor at INSEAD Previous career: CEO of an internet startup and Head of Research at an asset management firm Labs/Teams: Leading the Strategy Science division at INFORMS Co-chair of the SMS Behavioral Strategy division
Dr. Sezgin Ayabakan is an Associate Professor in the Department of Management Information Systems at the Fox School of Business and Management, Temple University . He holds a PhD in Management Science from the University of Texas at Dallas, with a focus on Management Information Systems (MIS), an MS in Industrial and Systems Engineering from the University of Florida, and a BS in Industrial Engineering from Bilkent University in Turkey. His research focuses on healthcare analytics , particularly exploring how health information technology (HIT) impacts healthcare costs, quality, and utilization. Key research interests include data analytics applications in healthcare and social media, the business value of information systems, and open-source production strategies. He has examined topics such as telehealth efficacy, electronic health record (EHR) adoption challenges, hospital readmission reduction programs, and the interplay between healthcare IT and clinician well-being. Dr. Ayabakan teaches undergraduate and graduate courses in information systems, including MIS 2101: Digital Systems and SBM 3586: Diamond Peer Teachers - Internship II . His work has been published in top-tier journals like MIS Quarterly and Health Services Research and Management Epidemiology , with recent studies addressing telehealth utilization, EHR strategy impacts, and the role of organizational routines in clinician satisfaction. While no formal awards are listed, his contributions to healthcare IT research demonstrate significant academic impact. His advisory and grant activities are not detailed in the provided text, but his research often intersects with practical healthcare system challenges, suggesting potential collaborations with healthcare institutions and policy organizations.
Jose Apesteguia is an ICREA Research Professor at the Department of Economics and Business, Universitat Pompeu Fabra, Barcelona, Spain. His research focuses on behavioral economics, decision theory, experimental economics, and game theory, with particular emphasis on topics such as behavioral heterogeneity, rationality measures, stochastic choice models, and social preferences. Apesteguia has collaborated extensively with scholars like Miguel A. Ballester and Jörg Oechssler, producing influential work on topics ranging from imitation dynamics to the impact of language on moral decisions. His research integrates theoretical frameworks with experimental methods, exploring how individuals make decisions under uncertainty, time preferences, and social contexts. Key contributions include the development of measures of rationality and welfare, as well as analyses of behavioral adaptation and the role of information in competitive environments. His work frequently bridges economic theory with empirical validation, addressing real-world issues such as rule compliance in public institutions and team performance in organizations. Apesteguia’s publications span top journals including the American Economic Journal: Microeconomics , Journal of Economic Theory , and Econometrica . He teaches advanced courses on bounded rationality and behavioral decision theory at the undergraduate and graduate levels. His research has been applied to fields like finance (e.g., copy trading behavior) and public policy (e.g., promoting compliance in libraries).
