Prof Kulwant Singh is a Professor of Strategy and Policy at the NUS Business School, National University of Singapore. His research focuses on strategy, management, organizational behavior, applied economics, and business systems in regional and global contexts. He holds a permanent academic appointment since January 2022. Teaching philosophy emphasizes contextualizing content for Singapore/Asia-Pacific business environments through case studies and combining theoretical frameworks with practical applications. He prioritizes interactive seminars to enhance student engagement and theoretical understanding in strategy education. Research interests include corporate diversification strategies, political ties' impact, alliance portfolio management, institutional transitions, and innovation dynamics in emerging markets. His work bridges universal strategic theories with Asia-specific business practices. Award-winning contributions include developing teaching materials for regional business contexts and advancing understanding of strategic competition in complex environments. Active in academic leadership through conference organization and editorial roles in strategy research.
Yan Liu is a full professor in the Thomas Lord Department of Computer Science at the University of Southern California (USC), serving as Director of the USC Machine Learning Center within the Viterbi School of Engineering. He holds courtesy appointments in the Ming Hsieh Department of Electrical Engineering and the Quantitative and Computational Biology Department. Before joining USC in 2010, he was a research staff member at IBM's T.J. Watson Research Center. He earned his M.S. and Ph.D. from Carnegie Mellon University. His research focuses on machine learning for time series, physics-informed AI, and interpretable models, with applications in healthcare, sustainability, and social media. Notable projects include developing AI for surgical training, analyzing misinformation on social platforms, and predicting cancer treatment outcomes. He has held leadership roles in top conferences like ICLR and ACM KDD, and serves as Associate Editor-in-Chief of TPAMI and Board Member of ICLR. Education: Ph.D., Carnegie Mellon University Affiliations: USC Machine Learning Center, Viterbi School of Engineering Service: General Chair (ICLR 2023, ACM KDD 2020), Program Chair roles across multiple conferences His lab, the Melady Group, emphasizes foundational ML advancements and interdisciplinary applications. Recent work includes physics-aware neural networks and time-series foundation models.
Jessica Lin is an Associate Professor in the Department of Computer Science at George Mason University, with a focus on data mining and time series analysis. She has published extensively on topics including motif discovery, anomaly detection, clustering, and symbolic representation of time series data. Ph.D., M.S., and B.S. in Computer Science from UC Riverside (2005, 2002, 1999) Her research spans efficient algorithms for mining massive time series datasets, extending to multimedia data like images and texts. She has developed tools such as GrammarViz and SAX for pattern visualization and symbolic analysis. Recent publications highlight advancements in variable-length motif discovery, interpretable classification frameworks, and anomaly detection. Her work appears in top conferences like AAAI, ICDM, and SDM, as well as journals including Knowledge and Information Systems and Data Mining and Knowledge Discovery . Dr. Lin has advised numerous Ph.D. students, many of whom have taken academic or industry positions. She has served on editorial boards and program committees for conferences such as KDD, ICDM, and ECML-PKDD.
Dr. Kenneth Joseph is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo , part of the School of Engineering and Applied Sciences . He serves as Associate Director of the Institute for Artificial Intelligence and Data Science and leads the Computation and Equity Lab (cubelab) , focusing on social inequality through computational measures and models. Education: PhD, MS, and BS in Societal Computing from Carnegie Mellon University (2016, 2012, 2010) Research Interests: Computational Social Science, Network Science, Gender Studies, and AI for Social Good Notable Work: Gender disparities in academia, predictive modeling for foster care and urban policy, and social media rumor analysis Awards: UB Exceptional Scholar—Young Investigator Award (2021) Advising: Mentored students like Yuhao Du, Jason Yan, Arjunil Pathak, and Navid Madani on projects spanning Twitter bios, foster youth services, and algorithmic fairness.
William Yang Wang serves as the Mellichamp Professor of Artificial Intelligence at the University of California, Santa Barbara (2019-present). He directs the UCSB Center for Responsible Machine Learning, the Mind and Machine Intelligence Initiative, and the UCSB NLP Group. His research focuses on theoretical foundations and practical algorithms for AI, particularly in NLP, LLMs, and neuro-symbolic reasoning. PhD in Computer Science from Carnegie Mellon University Active in AI theory and applications (2016-present) Research interests span multiple AI domains, with special emphasis on NLP and responsible machine learning. He has pioneered datasets like HybridQA, TabFact, and VaTeX, enabling advancements in multi-hop QA, fact verification, and video-language tasks. His work combines statistical relational learning with modern deep learning paradigms. Recent publications center around multimodal reasoning, knowledge graph integration, and responsible AI development. He has received numerous accolades including the IEEE SPS Pierre-Simon Laplace Award (2024) and NSF CAREER Award (2021). Karen Sparck Jones Award (2022) DARPA Young Faculty Award (2018) IBM Faculty Award Mentoring 15+ PhD and postdoc researchers who now hold positions at Microsoft Research, Amazon, Meta GenAI, and academic institutions like Arizona and Rutgers. His lab maintains active collaborations with industry partners through initiatives like ChipAgents.ai, which he founded as CEO.
Huining Li is an Assistant Professor in the Department of Computer Science at North Carolina State University . Her research focuses on Internet of Things (IoT) , cybersecurity , and mobile computing , with a specialized emphasis on mobile health (mHealth) technologies. Education: Ph.D. in Computer Science and Engineering from University at Buffalo (2024). Her work addresses privacy-preserving sensing mechanisms , biomarker measurement , and fairness in dynamic mobile environments , developing systems for chronic wound care, Parkinson’s disease management, and mental health therapy. Recent publications highlight innovations in mmWave biometrics , machine learning for health diagnostics , and non-contact monitoring . Scientific Awards: Best Paper Awards (SenSys 2019, BodyNet 2021, ICHI 2022) Best Paper Candidate (SenSys 2022) Harold O. Wolf Achievement Award (2024) EECS Rising Star (2023) NIH mHealth Training Institute Scholar (2025) She teaches courses in Mobile Health Systems and Applications and Computer Networks , and actively serves on NSF panels , TPC committees (ACM MobiSys, IEEE-EMBS BSN), and as Associate Editor for journals like Elsevier Smart Health.
Randy H. Ewoldt is the Alexander Rankin Professor in the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign (UIUC), part of the Grainger College of Engineering. He holds the Kritzer Faculty Scholar distinction and has been a faculty member since 2011, progressing from Assistant to Associate Professor before his current rank. His research focuses on fluid mechanics and rheology of complex fluids, with interdisciplinary applications in bioengineering, manufacturing, and robotics. Education includes a PhD and MS in Mechanical Engineering from MIT (2009 and 2006) and a BS from Iowa State University (2004). He has held visiting roles, including Guest Professor at ETH Zurich (2018). Research interests span rheology of complex fluids, nonlinear viscoelasticity, and material design. Notable contributions include pioneering work on protorheology and yield-stress fluids. His work often combines experiment and theory, emphasizing practical applications. Awards include the 2025 Society of Rheology Fellowship, PECASE (2017), and multiple teaching accolades. He advises on advanced fluid mechanics and rheology courses, including TAM 435, TAM 534, and ME 310. Labs/Teams: Ewoldt Research Group focuses on fluid mechanics and rheology, collaborating on projects like 3D printing and material design. Recent highlights include studies on embedded solvent exchange printing and viscoelastic fluid behavior.
Olga Papaemmanouil is a Professor of Computer Science at Brandeis University and Senior Associate Provost for Academic Affairs and Curriculum. She is affiliated with the Michtom School of Computer Science and the Volen National Center for Complex Systems. Ph.D. in Computer Science, Brown University (2008) M.S. in Information Systems, University of Economics and Business, Athens (2001) B.S. in Computer Science and Informatics, University of Patras, Greece (1999) Her research focuses on data management, integrating machine learning with cloud databases, query optimization, and performance prediction. She has pioneered techniques for interactive data exploration, reinforcement learning in query scheduling, and economic models for database provisioning. Recent publications highlight her work on learned query optimizers , deep reinforcement learning for database operations, and platform-independent neuroscience data interfaces . NSF Career Award (2013) Amazon Research Award (2019) Huawei Innovation Research Awards (2017, 2018) SIGMOD Best Demonstration Award (2015) Paris Kanellakis Fellowship (2002) She has secured multiple NSF grants and developed systems like Neo (learned query optimizer) and XCloud (performance management for cloud data services). Her work bridges database systems and machine learning for scalable data analytics.
Professor Rainer Böhme is a prominent academic in the field of IT security and privacy at the University of Münster's School of Business and Economics, Department of Information Systems. He also holds a professorship for Security and Privacy at the University of Innsbruck's Institute of Computer Science. His research spans multiple dimensions of digital security, with particular expertise in steganography, digital forensics, privacy-enhancing technologies, and the economic aspects of cybersecurity. Dr. Böhme earned his Doctoral Degree from TU Dresden's Faculty of Computer Science in 2008, following studies in Communications, Economics and Computer Science at Technische Universität Dresden and Université Paris XII. His academic journey includes positions as Assistant Professor at the University of Münster (2010-2015), Postdoctoral Fellow at the International Computer Science Institute in Berkeley (2009-2010), and Scientific Staff at TU Dresden's Chair of Privacy and Data Security. His research interests focus on steganography and steganalysis, digital forensics, privacy-enhancing technologies, security and usability, economic and behavioral aspects of information privacy, virtual currencies, and the economics of information security. His work bridges technical security mechanisms with economic and behavioral considerations, creating a unique interdisciplinary approach to cybersecurity challenges. Analysis of his recent publications reveals a strong trend toward the economics of security, particularly regarding blockchain technologies, cryptocurrency, and privacy valuation. His work increasingly examines the intersection of technical security mechanisms with market dynamics, regulatory frameworks, and user behavior. The research spans theoretical game-theoretic models, empirical studies of user behavior, and practical applications in digital forensics and privacy protection. Program Co-Chair, Financial Cryptography and Data Security (2015) Program Co-Chair, New Security Paradigms Workshop (NSPW) (2015) General Chair, 8th International Conference on IT Security Incident Management & IT Forensics (2014) Organizer and Program Co-Chair, 1st Workshop on Bitcoin Research (2014) Associate Editor, Electronic Commerce Research (since 2013) Associate Editor, EURASIP Journal on Information Security (since 2013) Professor Böhme has supervised multiple Master's theses in Information Systems, including work on static code analysis for smart contracts, remote maintenance protocol security, and application protection requirements in retail banking. His research is supported by significant grants from the German Federal Ministry of Research, Technology and Space, the DFG, and the EU FP7 program, with projects focusing on digital forensics, privacy-enhancing technologies, and cryptocurrency crime prevention. He leads the IT Security Research Group at the University of Münster, which investigates theoretical and applied aspects of information security with particular emphasis on the economic dimensions of security decisions.
Jason M. LaBelle is a Professor of Anthropology at Colorado State University (CSU), affiliated with the College of Liberal Arts. He serves as Director of the Center for Mountain and Plains Archaeology (CMPA) and Curator of the Archaeological Repository of CSU (AR-CSU). His research focuses on hunter-gatherer societies, particularly in the Intermountain West, emphasizing subsistence, mobility, and pre/post-contact Native American cultures. His work spans environments from the Great Plains to high alpine regions, with specialties in Clovis/Folsom cultures, communal hunting practices, and lithic technology. LaBelle teaches courses in archaeology, lithic technology, and public archaeology. He oversees CMPA projects funded by federal agencies like the National Park Service and the Bureau of Land Management, supporting student training in fieldwork, lab analysis (lithics, faunal studies), and report writing. His lab houses extensive collections from Colorado’s South Platte and Colorado River Basins, including alpine artifacts. He actively engages with tribal partners and the public through outreach, conferences, and NAGPRA coordination. LaBelle’s recent research includes studies on lithic quarries, ice patch archaeology, and Bayesian chronology modeling. His publications address prehistoric mobility, site chronology, and cultural resource management. He values interdisciplinary collaboration and student mentorship, aiming to bridge academic and applied archaeology.
Lorraine (Xiang) Li is an Assistant Professor in the Department of Computer Science at the University of Pittsburgh’s School of Computing and Information (SCI). Her research focuses on the intersection of natural language processing, commonsense reasoning, knowledge representation, and machine learning, particularly in designing probabilistic models and evaluation methods for implicit commonsense knowledge in language. Li holds a PhD from the University of Massachusetts, Amherst, and previously worked as a young investigator with the Mosaic team at AI2. She has an M.S. in Computer Science from the University of Chicago, where she conducted research at TTIC. Her work emphasizes advancing AI’s ability to reason contextually and generate robust, human-like understanding through probabilistic frameworks. Key research themes include bias detection in reasoning models, iterative model editing, domain adaptation with LLMs, and evaluating commonsense through probabilistic measures. Her recent publications explore challenges like confirmation bias in chain-of-thought reasoning and geographical robustness in object recognition. Li actively contributes to the NLP community, serving on program committees for ACL, EMNLP, NAACL, and ARR. Though no formal awards are listed, her prolific publication record reflects her impact in AI research. She currently leads research in procedural knowledge models (e.g., Plasma) and long-tail knowledge generation, advancing foundational AI methodologies.
Charles F. Harvey is a Professor in the Department of Civil and Environmental Engineering at the Massachusetts Institute of Technology (MIT), where he investigates hydrology, carbon cycling, and groundwater contamination. His work spans tropical peatlands, arsenic pollution in South Asia, and coastal groundwater dynamics, with field sites in Borneo, Bangladesh, and Vietnam. Education: B.A. in Mathematics (Oberlin College, 1986), M.S. in Applied Earth Science (Stanford University, 1992), Ph.D. in Geological and Environmental Sciences (Stanford University, 1996). Harvey’s research focuses on hydrogeology , carbon sequestration , and contaminant transport . He explores how groundwater flow and biogeochemical processes interact in tropical peatlands and coastal systems, with significant implications for climate change and water security. His recent publications emphasize tropical peatland hydrology , arsenic mobilization , and coastal groundwater exchange , integrating field experiments, remote sensing, and computational models. Scientific Awards AGU Fellow GSA Fellow Meinzer Award (GSA) Prince Sultan bin Abdulaziz International Prize for Water M. King Hubbert Award for Hydrology NSF Young Investigator Award Harvey leads the Harvey Lab , mentoring students and researchers in projects ranging from groundwater arsenic mitigation to coastal marsh biogeochemistry . His work bridges terrestrial and marine systems , addressing critical planetary challenges.
Dr. Edward Wei is a Research Fellow at the University of Sydney Business School's Institute of Transport and Logistics Studies (ITLS), where he has been since 2018. His work focuses on transport modeling, urban mobility, and policy analysis, with an emphasis on post-pandemic commuting patterns and sustainable transport initiatives. He holds a PhD from the University of Technology Sydney (UTS), an MBus from Queensland University of Technology (QUT), and a BEc from UIBE in China. Dr. Wei's research explores the intersection of work arrangements (e.g., hybrid work, flexi-time) and their impacts on transportation demand, urban planning, and environmental sustainability. His recent projects include developing state-wide transport models, analyzing micro-mobility adoption, and assessing the role of non-traditional mobility service providers in MaaS frameworks. Key areas of expertise include discrete choice modeling, transport demand forecasting, and policy evaluation. His publications span over 30 peer-reviewed articles, with recent contributions emphasizing post-pandemic commuting behavior, zero-emission truck transitions, and sustainable university travel strategies. His academic contributions bridge theoretical transport economics with practical policy applications, addressing challenges such as car tolling regimes, public transport patronage optimization, and the integration of remote work patterns into urban planning frameworks.
Eduardo Azevedo is the John M. Bendheim and Thomas L. Bendheim Professor of Business Economics and Public Policy at the Wharton School , University of Pennsylvania. He holds a courtesy appointment as Professor of Economics and was awarded the 2016 Sloan Foundation Fellowship. His research integrates economic theory with practical applications across science and business domains. His research interests include: Market design Selection markets Social science genetics Experimental economics Game theory Recent publication trends focus on: Economic theory applications to healthcare and digital markets Empirical Bayes methods in A/B testing Adverse selection in insurance markets Strategic behavior in two-sided matching Evolutionary behavioral economics He serves as an instructor for BEPP2500 - Managerial Economics , emphasizing real-world application of microeconomic theory to business problems. His work also involves software development for economic research, including MATLAB-based empirical Bayes tools for analyzing treatment effects in large-scale experiments. Scientific awards : Sloan Foundation Fellow (2016)
Prof. Dr. Steffen Marburg is a Full Professor at the Chair of Acoustics of Mobile Systems within the TUM School of Engineering and Design at the Technical University of Munich. His research focuses on numerical methods in vibroacoustics, structural optimization, and acoustic modeling for applications in automotive, maritime, and musical instrument domains. Education: PhD from Technical University of Dresden (1998). Academic Career: Junior Professor at TU Dresden (2004), Chair of Technical Dynamics at University of the Federal Armed Forces Munich (2010), Full Professor at TUM (2015–present). Editorial Roles: Co-Editor-in-Chief of Journal of Theoretical and Computational Acoustics, Associate Editor of Journal of the Acoustical Society of America, Editor of Acoustics Australia and Mechanical Systems and Signal Processing. His research integrates computational acoustics, boundary element methods, and machine learning to address noise control and structural optimization challenges. Recent work explores acoustic metamaterials, viscothermal losses, and data-driven modeling. He has co-authored over 150 publications and led advancements in multifrequency solution methods and noise-insulating structures. Scientific awards include the Innovation Award of the Industrieclub Sachsen e.V. (1999). His editorial contributions and leadership in journals highlight his influence in computational acoustics and structural dynamics.
