Jon Weissman is a Professor of Computer Science at the University of Minnesota, Twin Cities. His research focuses on distributed systems, edge and cloud computing, and high-performance computing (HPC), aiming to enhance performance, reliability, and energy efficiency. Education: Ph.D. in Computer Science, University of Virginia (1995) M.S. in Computer Science, University of Virginia (1989) B.S. in Applied Mathematics and Computer Science, Carnegie-Mellon University (1984) His research explores edge and cloud computing, IoT, and HPC, including subtopics like storage systems, resource management, and security. Publications highlight trends in adaptive prefetching, compressed sensing for medical devices, and IoT-informed autoscaling. Scientific Awards: NSF CAREER Award (1995) Senior Member, IEEE He has advised Ph.D. students like Albert Jonathan, Kwangsung Oh, and Francis Liu. His lab is located in 4-204A Keller Hall, and he serves on steering committees for conferences like HPDC.
Thomas Pasquier is an Assistant Professor in the Department of Computer Science at the University of British Columbia, affiliated with the Systopia Lab and UBC Security & Privacy Group. His research focuses on digital provenance, system auditing, intrusion detection, and performance optimization. He investigates systems security through provenance graph analysis, developing practical frameworks for intrusion detection (including PROVNET and Kairos) and provenance summarization tools. His work combines machine learning with systems research to enhance cybersecurity transparency. Recent Publications (2022-2025) Provenance-based intrusion detection systems analysis Whole-system provenance for practical security eBPF kernel extension security enhancements LLM-driven provenance summarization Research code quality assessment Scientific Awards Incredible Instructor Awards Amazon Science Research Award He supervises graduate students in systems security research and teaches courses on security & privacy and operating systems. His lab welcomes diverse students for thesis-based research opportunities.
Duncan Wilson is a Professor of Connected Environments at the Bartlett Centre for Advanced Spatial Analysis (CASA) at University College London. His work bridges academia and industry, focusing on IoT, AI, and spatial analysis to enhance understanding of built and natural environments. Current role: Professor of Connected Environments at UCL Education: PhD in Artificial Intelligence and Machine Vision (UCL, 1997), BEng (Hons) in Electrical Engineering (Loughborough University, 1993) Research interests include: Cognitive computing at the network edge Extraordinary sensory systems for data capture Spatial reasoning and digital twins IoT for healthcare and biodiversity Edge AI and TinyML Recent articles span digital twin development , IoT for biodiversity monitoring , and smart healthcare infrastructure . He has received recognition for collaborative R&D approaches during his directorship at Intel's Sustainable Connected Cities institute. Teaching: Leads MSc Connected Environments and modules on IoT ethics, AI on microcontrollers, and sensor network deployment Projects: IoT Living Lab at UCL, Project Hercules for eye clinic analytics, and Shazam for Bats environmental monitoring Professional activities: Former Director of Intel Collaborative Research Institute (2012-2018), ex-member of Smart London Board (2017-2022)
Sudin Bhattacharya is an Associate Professor at the BioMolecular Science Gateway, Michigan State University, with affiliations in the Genetics & Genome Sciences Program and Cell & Molecular Biology Program. His research bridges computational biology and toxicology to understand complex biological systems. Email: sbhattac@msu.edu Research Interests Dr. Bhattacharya specializes in systems toxicology, focusing on computational modeling of gene regulatory networks, single-cell transcriptomics, and molecular dynamics in response to environmental toxicants. His work examines how chemical exposures disrupt cellular pathways and contribute to disease mechanisms. Article Trends His recent publications emphasize: Single-cell and single-nucleus RNA sequencing for toxicological profiling Computational models of circadian rhythms and intercellular communication Dose-dependent responses to environmental chemicals like TCDD and heavy metals Mechanistic studies of adipose tissue remodeling and hypertension Applications of machine learning in chemical risk assessment Integrative approaches to liver metabolism and disease modeling Scientific Contributions Dr. Bhattacharya has pioneered multiscale modeling of biological systems, particularly in hepatic and vascular contexts. His work on the aryl hydrocarbon receptor and PPARα signaling networks has advanced predictive toxicology frameworks.
Bruno Basso serves as the Hannah Distinguished Professor in the Department of Earth & Environmental Sciences at Michigan State University, based in 307A Natural Science Building. He teaches GLG 446: Water and Food and maintains active research in sustainable agricultural systems, with contact via 517-353-9009 or basso@msu.edu. His work bridges academic research with practical farm applications across the US Midwest. His core research interests include: Food Security and Plant Resilience mechanisms Soil Science with emphasis on organic carbon dynamics Precision Agriculture technologies (drones, remote sensing) Climate-Smart Agriculture practices Nitrogen and phosphorus use efficiency Yield stability analysis through spatial-temporal modeling Regenerative agriculture impacts on greenhouse gas emissions Ecosystem services valuation in crop-livestock systems Analysis of his 2023-2025 publications reveals a dominant focus on quantifying climate benefits from regenerative practices using multi-model ensembles. His work consistently addresses scalability for farmer adoption, with strong emphasis on N₂O emissions mapping, soil carbon durability, and yield stability zones. Key methodological innovations include hybrid SAR-remote sensing integration and AI-driven nutrient prescription systems, primarily applied across Midwest corn-soybean systems. No scientific awards were documented in the provided materials. While specific advising details are absent, his leadership in the LTAR cropland common experiment and Soil Inventory Project indicates active mentorship of graduate researchers. His research likely attracts significant USDA and NSF funding given the scale of field experiments and modeling initiatives focused on decarbonizing agriculture. Dr. Basso co-leads the Soil Inventory Project at Kellogg Biological Station, developing integrated sampling, data repository, and modeling frameworks for regenerative agriculture. His team combines ground observations, remote sensing, and biophysical modeling to quantify soil carbon and greenhouse gas fluxes, collaborating with farmers, industry partners, and international researchers to translate science into on-farm practices.
Matteo Brunelli is Associate Professor of “Mathematical Methods of Economics and Actuarial and Financial Sciences” at the University of Trento , Department of Industrial Engineering, and Adjunct Professor (docent) at Lappeenranta University of Technology , Finland. He is nationally habilitated as Full Professor in Italy and has held long-term visiting positions at Berkeley, Turku, Auckland, JAIST and Binghamton. Education: Ph.D. (Doctor of Science) in Information Technologies, Åbo Akademi University, Finland, 2011 – graded Eximia cum laude approbatur M.Sc. in Economics, University of Trento, 2007 – grade 110/110 cum laude B.Sc. in Economics, University of Trento, 2005 Research focus: Brunelli’s work sits at the intersection of multi-criteria decision analysis , operations research and computational optimisation . He develops axiomatic foundations and algorithms for pairwise comparison matrices , consistency indices , the best-worst method and fuzzy preference relations , and applies them to energy planning, sustainable inventory, maintenance scheduling, 3-D printer selection, and blockchain governance. His 2023-2025 articles reveal intensified interest in uncertainty modelling (Dempster-Shafer theory), bi-objective optimisation of inventory and maintenance, and group decision protocols that integrate probabilistic or active-learning components, demonstrating both methodological depth and practical relevance. Scientific awards & grants: Academy of Finland Postdoctoral Researcher grant (€254 670, 2014-2017) Claudio Dematté Research Grant (€19 000, 2008) Teacher of the Year Award, Aalto University (2013 – both Spring & Autumn semesters) Bernard Roy Award 2021 for outstanding contribution to Multiple Criteria Decision Aiding (under-40 category) Supervision & funding: While specific doctoral students are not listed, Brunelli currently supervises graduate theses at Trento and has continuously held competitive national grants. His Academy of Finland project “Consistency of valued preference relations for decision analytics methods” financed three years of full-time research and international collaboration. Editorial & community roles: He serves on the editorial boards of International Journal of General Systems and Mathematical and Computational Applications , and acts as area editor for Journal of Multi-Criteria Decision Analysis , positioning him among the key gatekeepers of the MCDA community.
Boris Jukic is a Professor and Director of Applied Data Science at the Reh School of Business , Clarkson University. With a PhD from the University of Texas at Austin, he teaches courses such as Visual Basic Programming for Business Applications and Development of Business Applications on the Internet. Dr. Jukic's research focuses on: Management and pricing of networks and telecommunication services Application of data management and presentation strategies in e-business and e-commerce IT architecture's impact on organizational success metrics His recent publications highlight trends in data warehousing , IT architecture , and business intelligence . Notable subfields include data modeling , incentive-compatible pricing , and process-data integration . Contact: Email: bjukic@clarkson.edu Phone: 315/268-3884 Office: 227 Bertrand H. Snell Hall, Clarkson University
Professor Barry Porter is a faculty member at Lancaster University in the School of Computing and Communications . His research focuses on emergent software platforms that address software complexity through component models , meta-software platforms , and machine learning . Key areas include distributed systems, cloud integration with sensor nodes, green computing, and real-time visualization. Research Interests : Runtime adaptation in complex systems Self-assembling software architectures Machine learning for code optimization Distributed emergent systems at scale Green computing for multi-core environments Edge-cloud continuum integration Recent Publication Trends : His 2025 work explores genetic improvement for software using speciation algorithms , program geometry projection , and multi-agent decision frameworks . Earlier studies (2022-2024) investigate edge-cloud systems , neural transfer learning , and ecosystem curation in emergent software. Supervision & Projects : He supervises PhD student Ben Craine and leads projects like B-EGI (Bio-Enhanced Genetic Improvement) and BBC Prosperity Partnership for media delivery. Collaborations span environmental IoT, multi-agent learning, and fog computing. Labs & Groups : Affiliated with the Lancaster Intelligent, Robotic and Autonomous Systems Centre , Centre of Excellence in Environmental Data Science , and the Distributed Systems group.
Steven F. Son is the Alfred J. McAllister Professor of Mechanical Engineering at Purdue University, affiliated with the College of Engineering. He holds joint appointments in Aeronautics and Astronautics, Materials Engineering, and Mechanical Engineering. His research focuses on energetic materials, combustion science, and propulsion systems, with emphasis on detonation physics, additive manufacturing of explosives, and novel propellant designs. Key projects include developing throttleable solid propellants, studying material-filled void effects on detonation waves, and optimizing nanomaterials for enhanced reactivity. Dr. Son’s work integrates experimental and computational methods, such as laser absorption spectroscopy and machine learning, to advance understanding of high-energy materials. His contributions span from fundamental material characterization to applied systems like Martian perchlorate-based propellants. He leads research at the Maurice J. Zucrow Laboratories, Purdue’s premier facility for propulsion and energetic materials research. His recent studies explore flexoelectricity in fluoropolymer/aluminum composites, laser ignition systems for solid propellants, and thermal decomposition mechanisms of novel energetic formulations. While no awards are explicitly listed, his prolific publication record and interdisciplinary approach highlight his influence in the field.
James D. Long is a Professor of Political Science at the University of Washington and co-founder of the Political Economy Forum. He holds affiliations with multiple institutions including the Center for Statistics and the Social Sciences (CSSS) and the Technology and Social Change Group (TASCHA). His research focuses on electoral integrity, political violence, and ICT applications in development, particularly in sub-Saharan Africa and South Asia. He has observed elections in over a dozen countries and led field experiments on voter behavior and anti-corruption strategies. Long’s work is funded by USAID, NSF, and others. Education: PhD in Political Science, UC San Diego (2012) MSc in African Politics (Merit), SOAS, University of London (2004) BA in International Relations & History, College of William & Mary (2003) Research Interests: Elections in developing democracies, electoral fraud, technology for governance, insurgency impacts, and poverty reduction. His methods combine field experiments, ethnography, and election forensics. Recent Work: Examines ICT-driven citizen engagement platforms to improve governance and service delivery in developing nations. His 2020 ACM award-winning research addresses wildlife conservancy community relations via technology. Awards: ACM Best Paper Award (2020) Fulbright Scholar (2008-2009) Harvard Academy Fellowship (2012-2016) Advising & Grants: Supervises PhD students in comparative politics and development. Secured grants totaling over $1.5M for projects on electoral integrity and anti-corruption. Hosts the podcast 'Neither Free Nor Fair?' on global election security. Teaching: Courses include Global Crime/Corruption, African Political Economy, and Comparative Politics. Served as Associate Chair of the Department of Political Science.
Onesun Steve Yoo is a Professor of Operations and Marketing Analytics at the UCL School of Management, University College London, and Co-Director of the UCL Centre for Sustainable Business. He holds a PhD from UCLA Anderson School of Management, alongside advanced degrees in Electrical Engineering and Applied Mathematics from UC Berkeley and UCLA. His research focuses on innovation and entrepreneurship, examining operational and marketing strategies for firms launching innovative products/services. Key areas include consumer behavior analysis, pricing policies, sequential product launches, and the impact of technologies like surge pricing and AI-driven data analytics on business operations. Recent work integrates sustainability initiatives with AI to enhance operational transparency in supply chains and regulatory compliance. Yoo’s research has been published in top journals such as Marketing Science , Operations Research , and Manufacturing & Service Operations Management . His findings have been cited by US policymakers and featured in media outlets like the Wall Street Journal . He serves as a senior editor at Production and Operations Management and associate editor at Manufacturing & Service Operations Management . His academic service includes grants from Innovate-UK (UKRI) to collaborate with industry on sustainable business practices. Yoo’s work bridges theoretical research with practical applications, emphasizing data-driven decision-making and interdisciplinary collaboration between operations, marketing, and sustainability domains.
Agnes Horvat is an Associate Professor of Communication (with a courtesy appointment in Computer Science) at Northwestern University. She directs the Technology and Social Behavior (TSB) joint doctoral program between the McCormick School of Engineering and the School of Communication, and leads the Lab on Innovation, Networks, and Knowledge (LINK). Her research focuses on human-centered computing, network science, and AI's impact on information production/sharing in digital platforms. She has received NSF CAREER, CRII, and collaborative awards as PI. Her work examines algorithmic bias in online spaces, AI-assisted creativity (e.g., LLMs in biomedical writing and music), and collective intelligence dynamics. Media coverage includes Nature , Washington Post , and Le Monde . Her advisees have won prestigious fellowships like the Northwestern Presidential Fellowship and best paper awards at top conferences. Research interests include: (1) algorithmic bias in social media and crowdfunding, (2) AI-driven creativity expansion, (3) network structures of scientific attention, and (4) opinion dynamics in online discussions. Current projects explore LLMs' role in scientific writing and music composition, while past work analyzed gender disparities in scholarly self-promotion and retraction paper attention patterns. Grants: NSF CAREER Award (202?), NSF CRII (202?), Collaborative Grant (202?) Labs/Teams: LINK Lab (focusing on innovation networks), TSB Program (interdisciplinary engineering/communication PhD)
Scott L. Stephens is a Professor in the Department of Environmental Science, Policy, and Management (ESPM) at the University of California, Berkeley. He holds a Ph.D. in Wildland Resource Science from UC Berkeley (1995) and a B.S. in Electrical Engineering from Sacramento State University (1985). His research focuses on wildland fire science, fire ecology, and forest management, with an emphasis on how climate change and policy influence fire regimes. He leads the Stephens Lab, which conducts interdisciplinary studies on fire behavior, ecosystem resilience, and policy reform. Key contributions include advocating for prescribed burning and Indigenous stewardship practices to mitigate wildfire risks. Stephens has testified before congressional committees on forest health and has been recognized as a Clarivate Highly Cited Researcher (2024). His work integrates ecological, policy, and management perspectives to address contemporary fire challenges. Education: Ph.D., Wildland Resource Science, UC Berkeley, 1995 B.S., Electrical Engineering, Sacramento State University, 1985 Research Interests: Wildland fire behavior and effects Fire ecology and ecosystem interactions Climate change impacts on fire regimes Policy and management of fire-adapted landscapes Scientific Contributions: Stephens has authored or co-authored over 150 peer-reviewed articles, including seminal works on prescribed fire efficacy, forest restoration, and policy reform. His lab’s research has been featured in BioScience , Ecological Applications , and policy briefs for federal agencies. Lab and Collaborations: The Stephens Lab collaborates with Indigenous communities, federal agencies, and international researchers to advance fire science. Notable projects include the Fire and Fire Surrogate Study (FFS) and the Stewardship Project, which advocate for integrating Indigenous burning practices into federal policies.
Ming Lin is a Distinguished University Professor at the University of Maryland, College Park, holding joint appointments in Computer Science (Department of Computer Science), the Institute for Advanced Computer Studies (UMIACS), Electrical and Computer Engineering (ECE), and the Maryland Robotics Center. She holds the Dr. Barry Mersky and Capital One E-Nnovate Endowed Professorships. Her research focuses on physically-based modeling, virtual environments, haptics, robotics, and AI applications in healthcare and urban computing. Education: Ph.D., M.S., and B.S. in Electrical Engineering & Computer Sciences from UC Berkeley. She previously spent 20 years at UNC Chapel Hill before joining UMD in 2018. Research interests include collision detection algorithms (e.g., Lin-Canny algorithm), real-time physics simulation, virtual/augmented reality systems, and medical imaging applications. Her work has led to over 2 million downloads of her group's software tools and licenses with 60+ companies. Notable contributions include the Oculus Rift-related VR technologies and Amazon's virtual try-on system. Awards: IEEE Fellow (2012), ACM Fellow (2011), NAI Fellow (2022), and Washington Academy of Sciences Distinguished Career Award (2020). Active in professional service, she serves on the CRA Board and chairs the Committee on Widening Participation in Computing Research. Advising: Supervises 12+ PhD/Master's students. Her lab (GAMMA Group) focuses on AI-driven robotics, autonomous systems, and physically-based simulations. Key projects include traffic simulation frameworks, medical VR applications, and 3D garment modeling.
Owen Price is an Associate Professor and Director in Bushfire Risk Management at the School of Earth, Atmospheric and Life Sciences (SEALS), University of Wollongong. His roles include leading research on wildfire impacts on ecosystems, human health, and infrastructure. He holds a PhD from the Australian National University (1998), an MSc from the University of Strathclyde (1986), and a BSc (hons) from the University of York (1985). Director, Centre for Environmental Risk Management of Bushfire (since 2020) Principal Fellow, SEALS (2019–2021) His research integrates fieldwork, GIS/remote sensing, and statistical modeling to address landscape-scale wildfire risks. Key interests include fire severity effects on biodiversity, smoke pollution impacts, and cost-effective fire management strategies. He supervises postgraduate students in topics like coastal wetland vulnerability and fire regime analysis. Recent grants include studies on coastal wetlands' fire resilience (2023–2026), Bayesian fire spread modeling (2023–2026), and evaluating aerial firefighting efficacy (2023). His work bridges ecological, social, and technical dimensions of wildfire risk. Notable awards and recognitions are not explicitly listed in the provided materials. His contributions to fire policy and community adaptation are highlighted through collaborative projects with government and environmental agencies.
