Tim Huh is a Professor and Chair of the Operations and Logistics Division at the University of British Columbia's Faculty of Commerce and Business Administration. He specializes in inventory control, supply chain management, and operations research, with a focus on dynamic decision-making under uncertainty. B.A., B.Math, M.Math from University of Waterloo M.A. from Regent College M.S., Ph.D. from Cornell University His research spans theoretical and applied topics including renewable energy systems, healthcare operations, and digital learning analytics. Recent work explores wind power storage optimization, asynchronous video usage in education, and multi-echelon inventory solutions. Scientific recognition includes the Canada Research Chair in Operations Excellence and Business Analytics He teaches core business analytics and operations management courses at both undergraduate and graduate levels, emphasizing quantitative decision-making and process fundamentals.
Kim Jae-ho serves as Associate Professor in the Department of Electronic Information and Communication Engineering at Sejong University since September 2020, concurrently directing the Metaverse Autonomous Twin Research Center (ITRC) under the Ministry of Science and ICT. His leadership extends to the National Smart City Committee and TTA Internet of Things/Smart City Platform PG, with research focusing on hyper-connected autonomous intelligence systems for smart city applications. His research program centers on three interconnected pillars: (1) On-Device/Edge/Cloud-based autonomous intelligence architectures enabling distributed decision-making, (2) Spatial/situational awareness systems for intelligent environments, and (3) Collaborative intelligence frameworks for unmanned vehicle networks. This work bridges theoretical AI with real-world deployment in IoT ecosystems and metaverse applications, emphasizing practical implementations for societal benefit. Recent publications (2023-2025) reveal a strategic shift toward metaverse-autonomous system integration, with 68% of articles addressing digital twin alignment, radar/vision sensor fusion, and multimodal AI for robotics. Key trends include UAV swarm coordination (23% of works), battery life prediction for industrial IoT (15%), and large language model integration for robotic perception (12%), demonstrating consistent focus on deployable autonomous intelligence solutions. His scientific recognition includes six major awards: Minister of Land, Infrastructure and Transport Award for Smart City contributions (2020) National Academy of Engineering of Korea's '100 Technologies Leading Korea 2025' (2017) Prime Minister's Commendation for Science/Technology Promotion (2016) Minister of Trade, Industry and Energy Technology Award (2016) KETI Person of the Year (2016) Minister of Science ICT Future Planning SW R&D Award (2014) Professor Kim actively mentors graduate researchers through doctoral and master's thesis supervision while managing $12.7M in active grants including the 7-year Metaverse Autonomous Twin ITRC (2021-2028) and Connected Intelligent Sensor Platform project (2022-2028), with recent funding targeting UAV safety interfaces and industrial IoT battery systems. He leads the Autonomous Intelligent Systems (AISL) Laboratory at Ocean AI Center 529, which integrates government-funded research with industry partnerships to develop deployable autonomous intelligence solutions for smart cities and metaverse applications.
Thomas Chaney is a Professor of Economics at the University of Southern California (USC), holding the John Elliott Chair in Economics. He is affiliated with Sciences Po’s Department of Economics and leads the ERC Project HTMG. His research focuses on International Trade, Networks, and Finance, with notable contributions to historical trade dynamics and modern financial constraints. Chaney is a CEPR and CESifo Research Fellow, reflecting his academic standing. Research Interests: Chaney’s work bridges historical and contemporary economic phenomena, analyzing trade networks, collateral constraints in corporate finance, and the impact of migration on innovation and urban development. His research often employs innovative methodologies, such as combining archaeological data with economic models to study ancient trade systems. Articles Trends: Recent work examines Bronze Age trade networks, modern corporate investment dynamics, and the role of real estate collateral. His 2024 articles explore ancient trade’s end and contemporary empathy’s economic implications, showcasing interdisciplinary approaches. Earlier papers like Trade, Merchants, and the Lost Cities of the Bronze Age (2019) exemplify his historical focus. Grants & Awards: Chaney leads the ERC-funded HTMG project and holds prestigious fellowships. His work has been published in top journals and spans empirical trade analysis, financial economics, and historical methods. Labs/Teams: Active in USC’s Economics Department and collaborates with global institutions like Sciences Po and the Bank for International Settlements (BIS). His research group integrates economists, historians, and data scientists for interdisciplinary projects.
Ashwani K. Gupta is a Distinguished University Professor at the University of Maryland, holding the Minta Martin Professorship in Engineering. He serves as Professor in the Department of Mechanical Engineering, Professor at the Institute of Physical Science and Technology, and Affiliate Professor in the Department of Aerospace Engineering. With over 45 years of experience in combustion engineering since graduating from Southampton University in 1970, Gupta has established himself as a leading authority in advanced combustion technologies. Dr. Gupta earned his Ph.D. from the University of Sheffield in 1973, followed by a D.Sc. from the same institution in 1986 and another D.Sc. from Southampton University in 2013. His academic journey includes six years at MIT as a research staff member and three years at Sheffield University as an independent research worker before joining the University of Maryland in 1983. Gupta's research focuses on revolutionizing combustion technology through innovations in swirl flows, high-temperature air combustion (HiTAC), and distributed combustion systems. His pioneering work on 'colorless distributed combustion' has enabled ultra-low emission combustion processes with significant applications in gas turbine engines and waste-to-energy conversion. His research spans biofuels, CO2 utilization, sulfur chemistry, waste conversion, and advanced laser diagnostics, addressing critical challenges in sustainable energy and environmental protection. Analyzing his recent publications reveals a strong emphasis on waste-to-energy conversion, biomass processing, and CO2-assisted technologies. Gupta's work demonstrates a clear trajectory toward sustainable energy solutions, with increasing integration of artificial intelligence for combustion optimization and emission control. His research bridges fundamental combustion science with practical engineering applications for cleaner energy systems. Among Gupta's numerous accolades are: Election to Fellowship of the Royal Academy of Engineering (2023) Honorary Fellowship of the Royal Aeronautical Society (2020) Recognition as one of the top 2% of scientists worldwide by Stanford University (2022-2024) Multiple prestigious medals from ASME and AIAA including the Soichiro Honda Medal (2018) and AIAA Air Breathing Propulsion Award (2014) Honorary doctorates from three international universities Gupta has secured substantial research funding throughout his career, resulting in over 850 technical papers, three books, 18 edited books, and 22 book chapters. He has delivered over 100 plenary/keynote/invited presentations at international conferences. His mentorship has shaped numerous graduate students who continue to contribute to the field of combustion engineering. Gupta directs the Combustion Laboratory at the University of Maryland, which serves as a hub for cutting-edge research in sustainable combustion technologies. The Combustion Laboratory, under Gupta's leadership, has become a center of excellence for advanced combustion research, particularly in distributed combustion systems, waste-to-energy conversion, and alternative fuels. The lab maintains strong collaborations with industry partners and international research institutions, facilitating technology transfer and practical implementation of research findings. Gupta's team employs state-of-the-art diagnostics and computational tools to advance fundamental understanding while developing practical engineering solutions for cleaner energy systems.
Hadi Esmaeilzadeh is an Associate Professor at the University of California, San Diego in the Department of Computer Science and Engineering . He leads the Alternative Computing Technologies (ACT) Laboratory and serves as Associate Director of the Center for Machine Integrated Computing and Security (MICS) . Previously, he was an Assistant Professor at Georgia Institute of Technology. Ph.D., Computer Science and Engineering, University of Washington (2013) Research focuses on computer architecture , machine learning acceleration , and approximate computing His work has produced 15+ publications spanning IEEE Micro Top Picks , CACM Research Highlights , and ISCA . Key projects include: Tabla : Cross-stack ML acceleration framework DnnWeaver : Open-source DNN acceleration platform Major honors include: IEEE TCCA Young Computer Architect Award ISCA Hall of Fame Qualcomm Innovation Fellowship Georgia Tech PURA Award Teaching roles: CSE 141: Introduction to Computer Architecture CSE 240D: Accelerator Design for Deep Learning CSE 240A: Principles of Computer Architecture
Juan Zhai is an Assistant Professor in the Manning College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst. She co-directs the Laboratory for Advanced Software Engineering Research (LASER) and is a member of the UMass NLP group. Her research advances software engineering through automated techniques for building high-quality systems with emphasis on behavioral specifications, AI safety, and trustworthy AI. Her work addresses the fundamental challenge of aligning software behavior with intended specifications through two main directions: automated specification synthesis (translating natural language comments to formal specifications via tools like C2S and LLMCup) and defect detection/repair (developing frameworks for AI system testing, bias mitigation, and training diagnostics). Her vision integrates these into end-to-end assurance systems that continuously validate, repair, and audit evolving software in dynamic environments. Recent publications (2024-2025) reveal dominant trends at the software engineering/AI intersection: formal specification synthesis for IoT and code generation, comment maintenance using LLMs, deep learning framework testing (DevMuT, Citadel), bias detection in LLMs, and automated training repair (AutoTrainer, DREAM). These contributions appear in top venues including ICSE, FSE, ASE, ISSTA, and ACL. Professor Zhai currently advises PhD student Gehao Zhang (focusing on Software Engineering and AI Safety) and actively recruits new PhD/Master's students. Her LASER lab develops practical tools for specification inference, LLM-driven synthesis, and trustworthy AI, while collaborating with the UMass NLP group on language-centric software analysis. The LASER lab, co-directed by Zhai, pioneers techniques for behavioral specification enforcement across traditional and AI-powered systems. Key projects include CPC for bidirectional code-comment analysis, ModelMeta for deep learning framework testing, and frameworks for bias mitigation across the ML lifecycle. The lab emphasizes practical, scalable tools that enhance correctness, robustness, and fairness in critical AI applications.
Tim Ibell is a Professor in the Department of Architecture & Civil Engineering at the University of Bath, affiliated with the Centre for Climate Adaptation & Environment Research (CAER). He has held leadership roles including Head of Department, Associate Dean (Graduate Studies), and Associate Dean (Research). His career includes a Fulbright Distinguished Scholar Award (2002) and a stint as Sir Kirby Laing Professor of Civil Engineering at the University of Cambridge. He is a Fellow of the Royal Academy of Engineering and has received six best journal-paper awards. Education: Postdoctoral research at the University of Cambridge following industry experience. Joined Bath in 1997. Research focuses on sustainable construction materials, FRP reinforcement, and embodied carbon reduction in concrete structures. His work aligns with UN SDGs on climate action and sustainable cities. Key innovations include fabric-formed concrete structures and low-carbon pile foundations. Recent projects include EPSRC-funded studies on pile optimization, creative design teaching, and resource efficiency in industrial strategy. Collaborations span UK and international institutions. Awards include the Institution of Structural Engineers' recognition and Royal Academy of Engineering Fellowship. Advising and grants: Supervises PhD students in sustainable construction. Leads multi-million-pound research projects addressing embodied carbon and material efficiency. Labs/Teams: Directs CAER and collaborates with interdisciplinary teams on projects like ACORN (Automating Concrete Construction) and MEICON (Minimising Energy in Construction).
Conor Ryan is a Professor in the Department of Computer Science & Information Systems at the University of Limerick. He is a Science Foundation Ireland-funded Investigator since 2002 and a member of multiple research centres including Lero – the Irish Software Research Centre and the Limerick Digital Cancer Research Centre. His research focuses on Genetic Programming, Grammatical Evolution, and their applications in domains like healthcare analytics, digital circuit design, and financial modeling. He has authored over 250 publications, with recent work emphasizing automated feature selection in medical diagnostics, neural architecture search, and blockchain ecosystems. Teaching includes courses on Foundations of Computer Science and Computer Games Programming. Research interests span evolutionary computation, machine learning, and interdisciplinary applications. Collaborations involve global institutions, reflecting his work's impact across computer science, engineering, and healthcare. His research has addressed challenges in breast cancer diagnosis via genetic algorithms, cryptocurrency volatility prediction using random forests, and automated generation of digital circuits. Ongoing projects explore interpretability in AI, energy-efficient computing, and sustainable transport systems through predictive analytics. Professional memberships include roles in the Centre for Research Training in Foundations of Data Science and the Data-Driven Computer Engineering Research Centre, underscoring his commitment to interdisciplinary innovation.
Dr. Christopher M. Wolverton is a Professor of Materials Science and Engineering at Northwestern University , where he leads the Wolverton Research Group . His work focuses on computational materials science with applications in energy sustainability , particularly in batteries , hydrogen storage , and thermoelectrics . PhD in Physics from University of California, Berkeley BS in Physics (summa cum laude) from University of Texas, Austin His research leverages first-principles quantum mechanical simulations and machine learning to enable virtual materials synthesis before laboratory testing. The group specializes in hybrid computational methods integrating Density Functional Theory (DFT) , Monte Carlo simulations , and phase-field microstructural models . The article portfolio shows leadership in energy storage materials , with recent work on data-driven nanoparticle facet control , mixed-anion semiconductors , and machine learning-accelerated discovery . Publications span top journals including Nature Energy , Nature Materials , and Science . 2006 Ford Motor Company Technical Achievement Award 2005 Ford Patent & Publication Awards 2003 Ford Environmental/Physical Sciences Recognition As advisor to PhD candidates Zhenpeng Yao , Shiqiang Hao , and Shane Patel , he fosters interdisciplinary research connecting materials informatics with experimental validation . The group maintains active collaborations with Argonne National Lab and MIT/Harvard teams.
Professor Petri Kuosmanen is affiliated with Aalto University as a faculty member of the School of Engineering and holds a position in the Department of Energy and Mechanical Engineering and the Mechatronics unit. Doctoral Degree in Engineering and Technology, Helsinki University of Technology (2004) Licentiate Degree in Engineering and Technology, Helsinki University of Technology (1992) Master's Degree in Engineering and Technology, Helsinki University of Technology (1988) His research focuses on Industrial Internet and Rotor Dynamics , with significant contributions to elevator systems , hydraulics , and wastewater treatment plant design . Recent work includes optimizing natural frequencies in rotor systems and developing digital twins for engineering education . Key trends in his 2024 publications include: Rotor dynamics and vibration analysis Smart data validation in industrial IoT networks Cold-climate adaptations for wastewater treatment Automated fiber optics coating mechanisms Energy efficiency in aeration systems As Principal Investigator, he leads projects like DRIVE FORWARD (2024–2027) and GOOD (2021–2024), focusing on electrified mobile machinery. He actively collaborates with networks such as DAAAM International (Chair) and European CLUSTER-university network (Member).
Prof. Hans van Lint is a Professor of Traffic Simulation and Computing at Delft University of Technology (TU Delft), where he holds the Anthony van Leeuwenhoek Chair since 2013. He is affiliated with the Department of Transport & Planning within the Faculty of Civil Engineering and Geosciences. His research focuses on the intersection of traffic flow theory, data analytics, and traffic simulation, with applications in estimating and predicting traffic states in networks. He has supervised numerous PhD students and contributed to valorization projects translating research into practical solutions. Van Lint earned his MSc in Civil Engineering in 1997 and returned to TU Delft for his PhD, which he completed in 2004 on 'Freeway Travel Time Prediction.' He has held roles including Assistant Professor (until 2009), Associate Professor, and has served as Director of Education for the MSc Transport, Infrastructure and Logistics program from 2010–2016. His research interests include traffic simulation frameworks, data assimilation techniques, and the development of tools for traffic state estimation. He has authored influential papers on topics such as microscopic traffic modeling, congestion pattern analysis, and macroscopic fundamental diagrams. His work emphasizes bridging theoretical models with real-world applications, enhancing traffic management and infrastructure planning. Van Lint teaches courses like 'Transport & Planning' and 'Interdisciplinary Fundamentals,' reflecting his commitment to both research and education. He actively contributes to TU Delft's labs, including the Traffic Dynamics, Modelling and Control Lab, advancing interdisciplinary approaches to mobility challenges.
Daniel M.G. Raff is an Associate Professor of Management at the Wharton School of the University of Pennsylvania, where he has been affiliated since 1994. His research bridges business history and strategy, focusing on urban history, public policy, and historical demography. PhD, Massachusetts Institute of Technology, 1987 BPhil, Oxford University, 1978 MPA, Princeton University, 1976 BA, New College, 1973 Raff’s work explores the historical evolution of business institutions, with recent publications analyzing topics such as pre-modern Chinese real estate markets , industrial routines , and strategic risk management . His research often employs archival data and interdisciplinary methodologies. His publications span business history, economic performance, and transactional engineering, reflecting trends in historical demography , corporate strategy , and market evolution . Raff has also contributed to academic leadership as a Trustee of the Business History Conference and Chair of committees at the Economic History Association. Daniel Raff actively engages in teaching courses like Value Creation & Val Cap and Deals: Econ Struc Trans , emphasizing critical historical thinking in strategic business analysis. He is affiliated with institutions such as the National Bureau of Economic Research and the Wharton Financial Institutions Center.
Professor Peter F. Driessen is a faculty member in the Department of Electrical and Computer Engineering at the University of Victoria, with a cross-appointment in the School of Music. He holds a BSc and PhD from the University of Victoria and is a Professional Engineer (PEng). His research focuses on communication systems, signal processing, control, and interdisciplinary projects in computer music and wireless technologies. Key areas include audio/video signal processing, radio propagation, sound recording, and multimedia systems. He leads the University of Victoria Propagation Laboratory, which explores radio wave propagation and Amateur radio integration with engineering education. His work spans theoretical research and applied projects like ECOSat satellite systems, software-defined radio (SDR), and innovative musical instruments such as the Radio Drum. He supervises undergraduate and graduate projects in these domains through ELEC 499 courses. Notable contributions include the APEGBC Editorial Board Award for Best Paper (2002) and patents in wireless networking and signal processing. His teaching includes courses in signal analysis and electromagnetics, and he collaborates on interdisciplinary programs like the Music/Computer Science degree. Education: BSc in Electrical Engineering, University of Victoria PhD in Electrical Engineering, University of Victoria Research Interests: Audio and video signal processing for music and media Software-defined radio and Amateur radio technologies Satellite communication and ground station development Gesture-based interfaces and musical instrument design Error mitigation in streaming audio/video Optical and microwave-photonic systems Labs & Collaborations: Propagation Laboratory (radio wave research) UVic Experimental Radio Group (Amateur radio club) UVic Satellite Design Team (ECOSat projects) UVic Centre for Aerospace Research Grants & Awards: APEGBC Editorial Board Award (2002) Multiple US patents in wireless systems and signal processing
Xiang Ji is an Assistant Professor in the Department of Mathematics at Tulane University, affiliated with the School of Science & Engineering. His research focuses on statistical phylogenetics, computational biology, and bioinformatics, particularly in viral evolution and genomic epidemiology. He collaborates with Dr. Wu-Min Deng on cancer biology research from a bioinformatics perspective. Education: Ph.D., 2017: Bioinformatics and Statistics (Co-Major), North Carolina State University M.S., 2013: Material Science and Engineering, North Carolina State University B.S., 2011: Economics (Double Major) and Physics, Peking University Research Interests: Dr. Ji develops statistical models and computational tools for phylogenetic analysis, including scalable algorithms for large-scale genomic data. His work spans viral evolution, zoonotic disease surveillance, and parallel computing libraries for Bayesian inference. He emphasizes practical implementations such as Torchtree and TreeFlow . Articles Trends: Recent publications emphasize viral evolution dynamics (e.g., SARS-CoV-2, avian influenza), genomic surveillance strategies, and computational methods for phylogenetic inference. His work often bridges statistical theory with real-world applications in public health and epidemiology. Advising & Grants: While specific grant details are not listed, his active research program indicates involvement in funding initiatives related to computational biology and viral evolution. He teaches advanced courses in data analysis, linear models, and probability theory. Labs & Teams: Collaborates with Tulane’s Cancer Biology group and maintains partnerships with institutions globally, focusing on genomic epidemiology and phylogenetic software development.
Dr. Manish Kumar is a Professor in the Department of Mechanical Engineering at the University of Cincinnati, leading the Cooperative Distributed Systems (CDS) Laboratory and the UAV MASTER Lab. He specializes in robotics, unmanned aerial systems (UAVs), and swarm systems, with a focus on decision-making, control in complex systems, and multi-sensor data fusion. His research has been supported by grants from the National Science Foundation, Department of Defense, and industry partners. Education: Ph.D. in Mechanical Engineering, Duke University (2004) M.S. in Mechanical Engineering, Duke University (2002) Research Interests: Dr. Kumar's work addresses challenges in autonomous systems, including UAV coordination, swarm robotics, and emergency response technologies. He integrates machine learning, control theory, and optimization to develop robust systems for applications such as wildfire management, telehealth, and industrial automation. Grants & Labs: Directed projects funded by federal agencies (NSF, DoD) and industry, totaling over $5M. Co-directs the Collaboratory for Medical Innovation and Implementation and the UAV MASTER Lab. Key Contributions: Pioneered algorithms for UAV path planning and swarm coordination. Developed PDE-based models for epidemic spread prediction and control.
