University of Illinois Urbana-ChampaignUnited States
Ruoqing Zhu is an Associate Professor in the Department of Statistics at the University of Illinois at Urbana-Champaign, with a primary appointment in the College of Liberal Arts & Sciences. He also serves as an inaugural member of the Carle Illinois College of Medicine, a Faculty Fellow at the National Center for Supercomputing Applications, and an affiliated researcher with the Carl R. Woese Institute for Genomic Biology and the Center for Genomic Diagnostics. His roles include PhD Program Director and Advisory Board member of Prenosis Inc. Dr. Zhu holds a Ph.D. in Biostatistics from the University of North Carolina at Chapel Hill (2013), an MA in Statistics from Bowling Green State University (2008), and dual B.S. degrees in Mathematics and Financial Engineering from Nanjing University (2006, 2005). His postdoctoral training was at Yale University’s Department of Biostatistics (2013–2015). His research focuses on developing statistical methods for decision-making in personalized medicine and reinforcement learning, addressing challenges such as model interpretability, high-dimensional data, and distributional shifts. Key areas include uncertainty quantification, causal inference, and applications in bioinformatics, nutrition, and infectious diseases. He co-teaches courses at Carle Illinois, including Data Science Project and Foundations: Molecules to Populations , and contributes to interdisciplinary initiatives like the Personalized Nutrition Initiative. His recent work emphasizes trustworthy AI in healthcare, including sepsis prediction tools, metabolomic analysis, and biomarker discovery. He is actively involved in translational research, bridging computational methods with clinical and public health applications.
Tridas Mukhopadhyay is the Deloitte Consulting Professor of e-Business at Carnegie Mellon University's Tepper School of Business, where he has served on the faculty since 1986. His academic journey at CMU progressed from Instructor of Information Systems (1986-1987) to Assistant Professor (1987-1993), Associate Professor (1993-1997), Professor (1998-present), and Deloitte Consulting Professor of e-Business (2000-present). He also served as Director of the MS in Electronic Commerce program from 1999-2004. Ph.D. in Computer and Information Systems, University of Michigan–Ann Arbor, 1987 M.B.A. in Computer and Information Systems, Indian Institute of Management Calcutta, 1981 B. Tech. in Electrical Engineering, Indian Institute of Technology Kharagpur, 1978 Professor Mukhopadhyay's research spans multiple critical areas in information systems and technology management. His work on strategic IT use examines how organizations derive business value from information technology investments. He has conducted extensive research on business-to-business commerce, particularly focusing on e-procurement systems, web-based marketplaces, and electronic intermediation models. His cybersecurity research investigates the economic aspects of cyber security, including liability mechanisms and patch release strategies. In software engineering, he has studied productivity, quality metrics, and offshore software development contracts. His most recent publications reveal several key trends in his research trajectory. There's a growing focus on digital platform economics, examining advertising models, virtual currency systems in gaming, and sharing economy dynamics. His work increasingly incorporates behavioral aspects, studying how users respond to personalized content and how backers exert control in crowdfunded projects. Methodologically, his research employs sophisticated analytical approaches including hierarchical Bayesian models, structural equation modeling, and natural experiment designs. CART Research Frontier Award, Carnegie Mellon, 2005 Distinguished Ph.D. Alum, Michigan Business School, 2004 Best Paper, International Conference on Information Systems, 2001 Best Paper, MIS Quarterly, 1995 Xerox Research Chair, Tepper School of Business, 1988-1989 Information Systems Society Distinguished Fellow, 2012 Professor Mukhopadhyay has served on numerous editorial boards including Information Systems Research (1994-2003), Management Science (1999-2003), and MIS Quarterly (1997-1999), demonstrating his significant contributions to the field. His consulting work with major organizations including Alcoa, Chrysler, Ford, General Motors, IBM, and governmental agencies like the United States Post Office and Pennsylvania Turnpike has provided practical insights that inform his academic research. He has been actively involved in university governance through committee service including the Business Technology Faculty Search Committee and the CMU Faculty Senate. His research has been supported through various industry partnerships and academic grants, though specific grant details aren't provided in the source material. His teaching focuses on Business Computing and Strategic IT courses, reflecting his expertise in both foundational information systems concepts and strategic applications of technology in business contexts.
Ahmed Al-Rawi is an Associate Professor of News, Social Media, and Public Communication at Simon Fraser University's School of Communication. Since 2019, he has served as Director of the Disinformation Project, whose findings have been featured nationally and internationally. His academic work bridges journalism, digital media studies, and public communication with a focus on disinformation, social media dynamics, and media's role in democratic processes. Dr. Al-Rawi's research interests span disinformation studies, social media analysis, news framing, computational journalism, and the intersection of digital communication with societal issues including racism and public health crises. His work examines how digital platforms shape public discourse, influence political processes, and frame critical societal issues like the opioid crisis in Canada. He approaches these topics through interdisciplinary lenses that combine media studies, political science, and sociology. His scholarly contributions reveal consistent focus on digital communication's impact on society, with recent work examining far-right movements, conspiracy theories, and mediated racism in Canadian contexts. Earlier research explored similar dynamics in Middle Eastern contexts, particularly during the Arab Spring and in conflict zones like Iraq. Shortlisted for Gertrude Robinson Prize (2022) Radio report nominated for US national award (2004) Teaching awards at Erasmus University As an academic leader, Dr. Al-Rawi has advised numerous graduate students, served on editorial boards for prestigious journals including Journal of Popular Communication and Digital Journalism, and reviewed over 220 research papers. His practical expertise extends to consulting for governmental bodies including the Canadian Senate, House of Commons, Public Order Emergency Commission, and Elections BC.
Matthew Holden is an Associate Professor in the School of Computer Science at Carleton University. He holds a PhD (2018) and MSc (2014) from Queen's University and a BScH (2012) from Western University. His research focuses on Surgical Data Science, applying machine learning to surgical time-series data from operating rooms and simulations to improve patient outcomes and surgical training. Key areas include real-time decision support, performance assessment, and surgical efficiency through domain-knowledge integration. Research interests emphasize machine learning for surgical workflows, skill assessment via sensor data (e.g., motion tracking, EEG), and computer-assisted interventions. Notable work includes automated proficiency evaluation in cataract surgery, ultrasound-guided procedures, and neurosurgical training. His contributions span medical robotics, surgical education, and clinical decision support systems. Publications highlight advancements in surgical workflow anticipation, tool detection, and skill metrics across domains like ophthalmology, emergency medicine, and neurology. Holden advocates for interdisciplinary approaches combining computational methods with clinical expertise to enhance healthcare delivery.
Yan Delaure is Associate Professor of Fluid Mechanics at Dublin City University's School of Mechanical and Manufacturing Engineering and Deputy Director of the DCU Water Institute. His research focuses on multiphase flows, environmental hydraulics, and computational fluid dynamics applications in wastewater treatment and marine systems. Research includes microbubble dynamics for aeration, fluid-structure interactions in deformable systems, and biomimetic antifouling solutions. Recent publications explore advanced simulation methods for turbulent flows and additive manufacturing process optimization.
Huazhen Fang is an Associate Professor in the Department of Mechanical Engineering at the University of Kansas School of Engineering, where he joined in 2014. He leads the Information & Smart Systems Laboratory (ISSL) and holds a courtesy appointment in the Department of Electrical Engineering & Computer Science. His research focuses on enabling intelligence for complex systems through information-driven approaches. Dr. Fang received his Ph.D. in Mechanical Engineering from the University of California, San Diego in 2014, following an M.Sc. from the University of Saskatchewan and a B.Sc. in Computer Science & Technology from Northwestern Polytechnic University in China. He was a Visiting Faculty Fellow at Mitsubishi Electric Research Laboratories in 2022. His research interests span Systems and Control, Advanced Battery Management, Energy Storage Systems, and Robotics, with particular focus on system modeling, estimation, control design, machine learning and numerical optimization. Dr. Fang's work has significant applications in energy management, cooperative robotics, and environmental observing systems. His research has been supported by the National Science Foundation, Department of Energy, Army Research Laboratory, and Mitsubishi Electric Research Laboratories. His extensive publication record shows a clear trend toward increasingly sophisticated integration of physics-based modeling with machine learning approaches, particularly in battery management systems and autonomous vehicle control. Recent work demonstrates a growing emphasis on Bayesian inference methods, distributed control architectures, and safety-critical applications of intelligent control systems. Faculty Early Career Award from National Science Foundation (2019) University Scholarly Achievement Award (2024) Miller Professional Development Award (2022) Miller Faculty Scholar Award (2018, 2019, 2023) Wesley G. Cramer Outstanding Mechanical Engineering Faculty Award (2016) Big XII Faculty Fellowship (2015) IEEE Transactions on Transportation Electrification Prize Paper Award (2024) Dr. Fang has successfully mentored numerous graduate students through the Information & Smart Systems Laboratory, with many receiving awards for their research. His research has attracted significant funding from prestigious organizations including the National Science Foundation, Department of Energy, Army Research Laboratory, and Mitsubishi Electric Research Laboratories. He currently serves as an Associate Editor for multiple prestigious journals including Information Sciences, IEEE Transactions on Industrial Electronics, and IEEE Control Systems Letters. The Information & Smart Systems Laboratory (ISSL) under Dr. Fang's leadership has established itself as a center for cutting-edge research in information-driven smart systems. The lab focuses on pushing the frontiers of information extraction, analysis and exploitation for dynamic systems to deal with system complexity and enable system intelligence. The lab actively collaborates with industry partners and local communities, emphasizing research that serves societal needs.
Catherine Mulligan is a Distinguished Research Professor in the Department of Building, Civil, and Environmental Engineering at Concordia University, where she also serves as Director of the Concordia Institute for Water, Energy and Sustainable Systems. She was previously the Concordia Research Chair in Geoenvironmental Sustainability (Tier I) until 2021, having held this prestigious research chair since 2002 (initially as Tier II). Dr. Mulligan earned her B.Eng. and M.Eng. degrees in chemical engineering from McGill University, followed by a Ph.D. specializing in geoenvironmental engineering, also from McGill University. After 16 years working at McGill University and in industry (including positions at the Biotechnology Research Institute of the National Research Council and SNC Research Corp.), she joined Concordia University in 1999 as an Assistant Professor, was promoted to Associate Professor in 2002, and to full Professor in 2008. Her research spans multiple critical areas of environmental engineering with a focus on contamination remediation. She specializes in surfactant-enhanced washing and flushing of contaminated soils and sediments, treatment of metal-contaminated media, bioremediation techniques, and various wastewater treatment methods. Her work includes biosurfactant applications, in-situ sediment remediation, anaerobic treatment processes, membrane technologies for water treatment, and energy generation through pressure-reduced osmosis. She has developed sustainability indicators and focuses on practical applications of environmental engineering solutions. Analysis of her recent publications (2023-2025) reveals a continued leadership in environmental engineering with particular emphasis on nanotechnology applications for oil spill cleanup in sensitive coastal regions, advanced membrane technologies for water treatment and energy generation, microbially induced calcite precipitation for mining waste remediation, sustainable resource recovery approaches from waste batteries, and innovative techniques for eutrophic lake restoration. Her research demonstrates a consistent focus on practical, sustainable solutions to environmental contamination problems across diverse settings. Dr. Mulligan's scientific contributions have been recognized with numerous prestigious awards including Fellowship in the Royal Society of Canada, Canadian Academy of Engineering, Engineering Institute of Canada, and the Canadian Society for Civil Engineering. She has received the RSC Miroslaw Romanowski Medal, the Geoenvironmental Award, the A.G. Stermac Award of the CGS, and the John B. Sterling Medal of the EIC. Her Concordia-specific honors include the Provost Circle of Distinction, Concordia Sustainability Champion, and the Petro Canada Young Innovator Award (awarded twice). With over 40 years of research experience across government, industrial, and academic environments, Dr. Mulligan has supervised to completion more than 75 graduate students in Civil Engineering (MASc and PhD programs). Her research has attracted significant funding, including a $1,643,700 NSERC CREATE grant for the Institute in Water, Energy and Sustainability, which represents the first Concordia project to receive funding through this program. She has authored more than 140 refereed papers, holds three patents, and has made substantial editorial contributions as Section Editor for the Journal of Environmental Engineering, Chief Editor for Waste (MDPI), and serves on multiple other editorial boards. As Director of the Concordia Institute for Water, Energy and Sustainable Systems, Dr. Mulligan leads an interdisciplinary team focused on training students in sustainable development practices and advancing research into innovative solutions for water, energy, and resource conservation challenges. The institute represents a significant hub for environmental research and education at Concordia University.
Dr. Mohamed Hassan is an Assistant Professor in the Department of Electrical & Computer Engineering at McMaster University. His research focuses on Cyber-Physical Systems-on-Chip (iCPSoCs) , emphasizing design, analysis, and deployment for critical domains like Unmanned Aerial Vehicles (UAVs), Autonomous Cars, and healthcare systems. Key research areas include hardware/software codesign, real-time systems, embedded systems, and security. He teaches courses such as COMPENG 4DM4 (Computer Architecture) and COMPENG 4DS4 (Embedded Systems) . His work bridges foundational theories (e.g., scheduling, AI) with infrastructure-level innovations (e.g., compilers, memory systems). The Fanos Research Lab he leads explores interdisciplinary solutions for efficient CPS-on-Chip, addressing challenges in multicore predictability, memory latency, and edge computing. Recent contributions include frameworks for explainable memory-centric workloads and techniques to accelerate TinyML inference. Dr. Hassan serves on Technical Program Committees for conferences like RTAS and OSPERT, highlighting his role in advancing real-time embedded systems research.
David A. Stephens is a Professor in the Department of Mathematics and Statistics at McGill University, Montreal. He served as Chair of the Department from 2015 to 2019 and as Vice-Dean in the Faculty of Science from 2019 to 2025. His research focuses on Bayesian inference, biostatistics, causal inference, bioinformatics, and statistical genetics. He holds prestigious fellowships: International Statistical Institute (2015), American Statistical Association (2019), and Royal Society of Canada (2024). His work addresses challenges in epidemiology, HIV transmission dynamics, and clinical trial design. Key research themes include: Bayesian hierarchical modeling for infectious diseases (e.g., SARS-CoV-2, HIV) Causal inference in dynamic treatment regimes Survival analysis and censored data methods Statistical genomics and epigenetics His publications analyze public health trends, such as HIV transmission clusters in Quebec and SARS-CoV-2 seroprevalence in Canada. Methodologically, he develops novel techniques for time-series analysis, recruitment forecasting in clinical trials, and computational statistics. Notable contributions include: Advancing phylogenetic cluster inference in HIV studies Optimizing warfarin dosing strategies via SMART trials Modeling gut microbiota impacts on growth faltering in infants His academic leadership includes roles at McGill and prior experience at Imperial College London. His work bridges statistical theory and practical healthcare applications, emphasizing interdisciplinary collaboration.
Dr. Alexander Paulus serves as a Researcher at the Chair of High-Frequency Engineering within the Department of Electrical Engineering at the Technical University of Munich (TUM), School of Computation, Information and Technology. Working under Prof. Dr.-Ing. Thomas Eibert, he contributes to advanced electromagnetic research and measurement systems development at TUM's Arcisstr. 21 campus in Munich. Research Expertise His core specialization lies in near-field antenna measurement and transformation techniques, with significant contributions to phase retrieval algorithms, inverse source methods, and UAV-based electromagnetic field measurements. He addresses critical challenges including probe correction with unknown antennas, sparse sampling for directive antennas, and electromagnetic modeling of environmental effects like rain attenuation. His work bridges theoretical electromagnetics with practical antenna characterization solutions. Publication Trends From 2014-2025, Paulus has published 25+ papers focusing on near-field to far-field transformations, particularly in phaseless and multi-probe scenarios. Recent work (2023-2025) demonstrates innovation in spectral filtering, sparse reconstruction, and UAV-based systems for defect localization and wet antenna modeling. His research increasingly integrates computational techniques to solve complex inverse problems in antenna measurements. Scientific Recognition No formal awards documented in available information Academic Contributions Student Mentoring: No advisees listed in provided materials Research Funding: Grant details not specified in source text Research Environment Paulus operates within TUM's Chair of High-Frequency Engineering facilities, which include advanced near-field measurement ranges, UAV-based electromagnetic characterization systems, and laboratories for metamaterials research and electromagnetic compatibility testing. His work supports applications in 5G/6G communications, aviation navigation systems, and precision antenna diagnostics.
Prof. Hatice Gunes is a Full Professor of Affective Intelligence and Robotics at the University of Cambridge's Department of Computer Science and Technology, leading the Affective Intelligence and Robotics Lab (AFAR Lab). She holds an EPSRC Fellowship and is an EPSRC Fellow. Her research focuses on multimodal affective and social intelligence for AI systems, particularly embodied agents and robots, integrating Machine Learning, Affective Computing, and Human Nonverbal Behaviour Understanding. Key projects include the CHANSE initiative (2025–2028) for child mental health assessment via social robotics, the EPSRC Fellowship on robotic EQ for wellbeing (2019–2025), and the EU Horizon 2020 WorkingAge project. Prof. Gunes has pioneered systems like the EU SEMAINE project's SAL system, recognized with Best Demo and Paper Awards, and co-founded SensingFeeling, a spin-out company from the Innovate UK Sensing Feeling project. Her work emphasizes ethical AI and fairness, earning awards like the Best Paper Award in Responsible Affective Computing (IEEE ACII'23). She has delivered keynote talks at IEEE FG’19 and ICPR’22 and collaborates with the Department of Psychiatry and wellbeing professionals. Education: PhD in Computer Science from University of Technology Sydney (UTS) under Australian Government IPRS Scholarship Postdoctoral Research at Imperial College London (SEMAINe project) Research Interests: Multimodal affective computing, social robotics for mental wellbeing, fairness in AI systems, human-robot interaction (HRI), and ethical deployment of AI technologies. Her lab develops robots for workplace wellbeing coaching and child mental health assessment, with over 700 media coverages and partnerships with industry and healthcare sectors. Notable Achievements: Runner-up Collaboration Award (2023 VC Research Impact) Better Future Award (2023 Hall of Fame) Finalist RSJ/KROS Interdisciplinary Research Award (2021) Shortlisted Sony Women in Technology Award 2025 Labs & Teams: AFAR Lab drives interdisciplinary research in Cambridge, focusing on socially intelligent robots and AI systems that address critical societal challenges in wellbeing and mental health.
Wesley McGee serves as Associate Professor of Architecture and Director of the Fabrication and Robotics Lab (FABLab) at the University of Michigan Taubman College of Architecture and Urban Planning. He co-founded Matter Design, a studio pioneering innovative applications of advanced manufacturing in architectural production across global contexts including the US, Europe, Middle East, and Australia. Education Bachelor of Science in Mechanical Engineering, Georgia Tech Master of Industrial Design, Georgia Tech McGee's research critically interrogates material production methods in architecture through robotics and digital fabrication, developing novel connections between design, engineering, and manufacturing processes. His work explores spatial-laminated timber systems, geometrically adaptive robotic workflows, and real-time fabrication-aware form finding to create material-efficient architectural solutions. His publications trend toward integrating computational design with physical construction, emphasizing topological optimization, adaptive robotic motion planning, and additive manufacturing techniques that reduce material usage by up to 46% compared to conventional systems. Scientific Awards Architectural League Prize for Young Architects & Designers Design Biennial Boston Award ACADIA Award for Innovative Research Architect Magazine R+D Award (multiple) McGee leads NSF Regional Innovation Engines semifinalist projects including Next-Generation Factory-Built Housing and secures University of Michigan grants for climate action initiatives. His Matter Design studio collaborates with architects, engineers, and artists on exhibitions like Climate Futures and SPLAM, advancing equitable city-making through material innovation. As FABLab Director, he operates a cutting-edge robotics facility where industrial tools are reconfigured for architectural production, mentoring students in courses like ARCH 581 (Advanced Robotics) and ARCH 702 (Robotic Engagement) while pushing boundaries in mass timber and glass fabrication.
Dr. Joseph Moore is an Assistant Professor in the Department of Mechanical Engineering at Johns Hopkins University (JHU), serving as Director of the Agile and Intelligent Robotics (AIRO) Laboratory. He is affiliated with the Laboratory for Computational Sensing and Robotics (LCSR), the Institute for Assured Autonomy (IAA), and holds a Bridging Faculty appointment in the Research and Exploratory Development Department (REDD) at JHU/APL. His research focuses on computational control, machine learning, and robotics to enable agile systems operating in complex environments. Dr. Moore previously served as Robotics Group Chief Scientist at JHU/APL, leading projects on hybrid unmanned aerial-aquatic vehicles and aerobatic fixed-wing systems. He has secured funding as Principal Investigator (PI) for ONR, DARPA, and ARL programs, particularly in post-stall maneuvering control and multi-robot coordination. His work emphasizes robust control strategies for autonomous systems in constrained environments. Research interests include aerial robotics, optimization, and learning-based control. Notable contributions involve NMPC-based systems, UAV navigation, and adaptive control for uncertain environments. His recent articles highlight advancements in swarm coordination, morphing-wing UAVs, and PAC-NMPC frameworks. Dr. Moore advises students such as Mark Gonzales and Adam Polevoy. Key grants include ONR/DARPA-funded projects on post-stall flight control and Army-funded multi-robot coordination efforts. His lab (AIRO) and collaborations (LCSR, IAA) drive applied and theoretical robotics research.
Prashanth Krishnamurthy is a Research Scientist in the Department of Electrical and Computer Engineering at New York University Tandon School of Engineering. His research focuses on robotics, control systems, and cybersecurity, particularly in cyber-physical systems such as power grids and embedded devices. He holds a Ph.D. in Electrical Engineering from NYU. Key research areas include hardware security (e.g., detecting Trojans in chips), anomaly detection in critical infrastructure, and resilient control strategies for robotic systems. He has led or contributed to projects funded by the U.S. Department of Energy (DOE), Office of Naval Research (ONR), and others, including the Tracking Real-time Anomalies in Power Systems (TRAPS) initiative and hardware Trojan detection using short-term aging phenomena. Education: Ph.D., Electrical Engineering, NYU His work bridges theoretical advancements and practical implementations, such as developing FPGA-based testbeds for hardware security validation and creating AI-driven cybersecurity tools like the CRAKEN LLM agent. Collaborators include institutions like SRI International, Karlsruhe Institute of Technology, and the NYU Center for Cybersecurity. Grants include a $1.94M DOE grant for TRAPS and a $359K DURIP grant for hardware Trojan detection. His technical contributions span control systems, anomaly detection algorithms, and cybersecurity frameworks for embedded systems. He is actively involved in advancing secure cyber-physical systems through innovations in real-time monitoring, robust control mechanisms, and AI-augmented security solutions.
Dr. Zhaohai Li Professor of Statistics at George Washington University, specializing in statistical methodologies for genetic epidemiology and clinical biostatistics. His research focuses on meta-analysis techniques, empirical Bayes methods, and population-based study designs. He has contributed extensively to improving statistical approaches in clinical trials and addressing challenges in genetic association studies. Education: Ph.D. in Statistics, Columbia University, 1989 Research Interests: His work addresses critical issues in modern biostatistics including: Population stratification in genetic studies Hardy-Weinberg equilibrium testing Optimal experimental design for case-control studies Handling missing data in genetic linkage analysis Development of robust statistical tests for complex survey data Publications Overview: Dr. Li's recent work emphasizes methodological advancements in: Bayesian approaches to population genetics Meta-analytic frameworks for combining study results Statistical solutions for multi-stage clinical trials Algorithmic improvements for genome-wide association analyses Professional Contributions: His articles consistently address practical challenges in biomedical research, bridging theoretical statistics with real-world genetic and clinical applications.
