Stephen W. Keckler is an Adjunct Professor at the Department of Computer Science , The University of Texas at Austin , and serves as Vice President of Architecture Research at NVIDIA . He is an ACM Fellow , IEEE Fellow , and Sloan Foundation Research Fellow . Education: BS in Electrical Engineering, Stanford University (1990) SM in Computer Science, Massachusetts Institute of Technology (1992) PhD in Computer Science, MIT (1998) Research Interests focus on computer architecture for deep learning , GPU computing , and energy-efficient systems . His work explores memory compression , network-on-chip designs , and heterogeneous computing . Publication Trends highlight advancements in deep learning accelerators , GPU memory systems , and energy-efficient architectures . Notable themes include sparsity exploitation , multi-chip modules , and fault-tolerant GPU pipelines . Scientific Recognition : ACM Fellow IEEE Fellow Sloan Foundation Research Fellow Best Paper Awards at ASPLOS 2009 and ISPASS 2011 Laboratory Affiliations : Computer Architecture and Technology Laboratory (CART) TRIPS Project (Tera-Op Reliable Intelligently adaptive Processing System) NVIDIA Research
Georges Kaddoum is a Professor at École de technologie supérieure (ÉTS) , specializing in Electrical Engineering. He holds the Canada Research Chair in Unlocking the Power of IoT 6G-Networks and the LACIME – Communications and Microelectronic Integration Laboratory affiliation. His work bridges wireless communications, IoT, and machine learning. Research Interests include wireless communication systems, physical layer security, machine learning for networking, and 6G technologies. He focuses on optimizing network performance in challenging environments (impulsive noise, underwater, non-terrestrial networks) and developing AI-driven solutions for jamming mitigation, resource allocation, and secure IoT frameworks. Recent Publications highlight 6G-enabled vehicular networks, quantum-safe blockchain integration, federated learning for transportation systems, and deep learning-based receivers for chaotic communication systems. His work emphasizes semantic communication, interference management, and digital twin applications. Awards IEEE TCSC Award for Excellence in Scalable Computing (2022) Prix d’excellence de la relève (Université du Québec, 2018) Prix d’excellence en recherche (ÉTS, 2018) Multiple IEEE Exemplary Reviewer and Best Paper Awards (2014–2022) Supervision includes 15+ PhD/Master’s students working on topics like index modulation, physical layer security, UAV communications, and intelligent resource management. Research Units Ultra Research Chair on Intelligent Tactical Wireless Networks LACIME Laboratory Canada Research Chair in IoT 6G-Networks
Robert Likamwa is an Associate Professor at Arizona State University, affiliated with the School of Arts, Media and Engineering and the School of Electrical, Computer and Energy Engineering. His research focuses on the intersection of mobile computing, augmented reality, and sensor design through Meteor Studio. Ph.D., Rice University M.S., Rice University B.S., Rice University His work spans three core research arcs: (i) advanced visual capture systems, (ii) hybrid virtual-physical immersion through sensory augmentation, and (iii) data-driven frameworks for AR/VR storytelling. He explores mobile operating systems, low-power architectures, computational imaging, and holographic computing. Recent publications analyze multi-resolution visual sensing, geospatial cross-virtuality collaboration, planetary data visualization, spatial audio optimization, and multi-sensory virtual environments. His 2013 paper on energy-proportional image sensors received the Best Paper Award at ACM MobiSys. Best Paper Award, ACM MobiSys 2013 LiKamWa advises graduate students through research and thesis courses and leads grants related to mobile vision systems, haptic interfaces, and energy-efficient sensor design. He directs Meteor Studio, a research group focused on immersive technology innovation.
Ottmar Edenhofer serves as Director and Chief Economist of the Potsdam Institute for Climate Impact Research (PIK), Director of the Mercator Research Institute on Global Commons and Climate Change (2012-2024), Professor for The Economics and Politics of Climate Change at Technische Universität Berlin, and Chair of the European Scientific Advisory Board on Climate Change (ESABCC) since 2022. His affiliations span leading European climate research institutions and academic bodies. Edenhofer's research focuses on climate change economics, particularly the impact of technological change on mitigation costs, public finance implications of climate policy, distributional effects of carbon pricing, and governance of global commons. His work bridges theoretical economic modeling with practical policy design, emphasizing equity considerations and institutional frameworks for effective climate action. He pioneered social science research at PIK, establishing rigorous methodologies for translating scientific findings into actionable policy advice. His publication record demonstrates consistent leadership in high-impact climate economics research, with seminal contributions to IPCC assessments (serving as Co-Chair of Working Group III for the Fifth Assessment Report) and influential analyses of carbon pricing mechanisms. Recent work increasingly addresses carbon dioxide removal governance, distributional justice in climate policy, and the integration of climate action with broader sustainable development goals. His research consistently appears in top journals including Nature, Science, and Nature Climate Change. Edenhofer has received numerous scientific honors including the Romano Guardini Prize (2018), Deutsche Umweltpreis (2020), and Arthur Burkhardt-Prize (2021). He belongs to the top 1% of most cited scientists globally (2018-2022) and was ranked among Germany's top 10 economists (2019-2020). His policy influence extends to serving as Vatican consultor for the Dicastery for Promoting Integral Human Development and advising EU institutions through ESABCC. As a science-policy interface leader, Edenhofer has shaped climate negotiations leading to the Paris Agreement and continues to advise European institutions on implementing climate neutrality targets. His work emphasizes the critical role of carbon pricing with equitable revenue recycling and the strategic sequencing of climate policies to maintain political feasibility while achieving deep decarbonization.
Tariq Iqbal is an Assistant Professor at the University of Virginia , with joint appointments in the Department of Systems and Information Engineering and Department of Computer Science . He leads the Collaborative Robotics Lab (CRL) , specializing in human-robot teams and embodied AI . Previously, he was a Postdoctoral Associate at MIT's CSAIL , advised by Prof. Julie Shah , and earned his Ph.D. in Computer Science from University of California San Diego (UCSD) under Prof. Laurel Riek . Ph.D. in Computer Science, University of California San Diego (2017) M.S. in Computer Science, University of Texas at El Paso (2012) B.S. in Computer Science and Engineering, Bangladesh University of Engineering and Technology (2007) His research lies at the intersection of artificial intelligence and robotics , focusing on human-robot collaboration in dynamic environments. Key areas include motion prediction , multimodal fusion , trust modeling , and collaborative learning . His work integrates cognitive science and deep learning to enhance robotic fluency in naturalistic settings. Recent publications (2023–2025) highlight advancements in human-robot team dynamics , multimodal dataset creation , and motion prediction algorithms . Notable works include Energy-Based Transformers for scalable AI, PoseTron for motion prediction, and Accessible Navigation Mapping for assistive robotics. These contributions span trust modeling , cloud robotic infrastructure , and safety in close-proximity collaboration . National Science Foundation (NSF) CAREER Award Air Force Office of Scientific Research (AFOSR) Young Investigator Program (YIP) Award Commonwealth Center for Advanced Manufacturing (CCAM) Innovation Award As faculty, he has secured grants from NSF and AFOSR , mentored research students, and taught courses like Stochastic Modeling I (SYS 6005) and Robots and Humans (SYS 4582/6465, ECE 4502/6465, CS 6465) . His prior industry roles at IBM Watson Lab and Grameenphone Ltd. inform his applied research in telecom infrastructure and cognitive robotics . He leads the Collaborative Robotics Lab (CRL) at UVA, which develops multimodal datasets , real-time coordination algorithms , and adaptive pathfinding systems . Current projects explore human motion prediction , team synchrony , and embodied question-answering , reflecting his commitment to advancing human-robot fluency and contextual AI .
Jinjin Gu is a tenure-track Assistant Professor at Sofia University "St. Kliment Ohridski" 's INSAIT (Institute for Computer Science, Artificial Intelligence, and Technology), leading research on visual cognition and intelligence. Her work spans visual perception, processing, generation, and reasoning. Education: Ph.D. in Electrical and Computer Engineering (2024), University of Sydney B.Sc. in Computer Science and Engineering (2020), Chinese University of Hong Kong, Shenzhen Her research focuses on visual cognition , including agentic systems , diffusion models , GAN architectures , model interpretability , super-resolution , and multimodal vision-language systems . She has developed novel paradigms like HYPIR for diffusion-quality restoration at GAN speeds. Recent publications highlight advancements in image/video restoration , generative modeling , and visual reasoning . Her work addresses critical challenges in model generalization , causal interpretation , and real-world application robustness . Scientific Awards: Stanford University's World's Top 2% Scientists (2024) Yunfan Award at World Artificial Intelligence Conference (WAIC) (2023) She has advised students contributing to TPAMI, CVPR, and ICLR publications, and serves as Area Chair for ICLR 2026, NeurIPS 2025, and ICML 2025.
Dr. Moritz Ziegler is a geomechanics researcher affiliated with the Technical University of Munich (TUM) and the Assistant Professorship of Geothermal Technologies . He previously worked at GFZ Potsdam (2017–2023) and earned his PhD in Geophysics from the University of Potsdam (2014–2017). His research focuses on geomechanical numerical modeling , uncertainty quantification , and 3D stress field analysis , with applications to geothermal energy, seismic hazard, and rock mechanics. Education: Bachelor of Science in Geosciences (2008–2011), Freie Universität Berlin Master of Science in Geophysics (2011–2014), University of Potsdam PhD in Geophysics (2014–2017), University of Potsdam & GFZ Potsdam His work integrates advanced computational methods ( Altair Hypermesh , Dassault Systèmes Abaqus , Python , Matlab ) to address complex geomechanical problems. Recent publications analyze stress gradients in the North Alpine Foreland Basin, fault-stress interactions, and physics-based machine learning in geomechanics. He has contributed to software development (DOuGLAS v1.0) and calibration tools (FAST Calibration v2.4). Scientific awards or honors are not explicitly mentioned in the provided text. However, his research has been published in leading journals such as Geophysical Journal International , Solid Earth , and Pure and Applied Geophysics .
Ahmad Al-Dabbagh is an Assistant Professor in Manufacturing Engineering and holds a Principal's Research Chair in Control Systems (Tier 2) with the School of Engineering at The University of British Columbia. As a Senior Member of IEEE and ISA, he contributes significantly to the field of resilient automation and control systems through research, teaching, and professional service. His academic journey includes postdoctoral fellowships at Imperial College London, the University of Toronto, and the University of Alberta, where he also earned his PhD in Electrical and Computer Engineering. Dr. Al-Dabbagh's research focuses on designing resilient automation and control systems by addressing critical challenges in fault diagnosis, cyber security, and alarm management. His work spans theoretical foundations and practical applications in industrial control systems, with particular emphasis on detection and isolation of faults and cyber attacks, control reconfiguration, event-triggered control, remote state estimation, and alarm systems design. His research interests also extend to causality analysis, prediction methods, and root cause analysis for industrial processes. His extensive publication record demonstrates consistent contributions to control systems security and reliability, with recent work focusing on sophisticated methods for detecting false data injection attacks, analyzing alarm correlations using advanced machine learning techniques, and developing recommender systems for human operators in industrial environments. The trajectory of his research shows an evolution from foundational control theory toward increasingly complex applications in cyber-physical security and human-system interaction in industrial settings. NSERC Postdoctoral Fellowship NSERC Alexander Graham Bell Canada Graduate Scholarship (CGS – D3) Queen Elizabeth II Graduate Scholarship Governor General's Academic Medal (Gold) As a graduate student supervisor, Dr. Al-Dabbagh mentors the next generation of control systems engineers while maintaining an active research program. He serves as an Associate Editor on the IEEE Control Systems Society Conference Editorial Board and is a licensed Professional Engineer in British Columbia and Ontario. His teaching portfolio includes courses such as System Identification, Digital Enterprise, Systems and Control, and Internet of Things, reflecting the breadth of his expertise. Dr. Al-Dabbagh leads the Okanagan Laboratory for Control Systems Research, where his team develops innovative approaches to enhance the security and reliability of industrial automation systems. The laboratory serves as a hub for interdisciplinary research that bridges theoretical control engineering with practical industrial applications, particularly in the energy, manufacturing, and process industries.
Serkut Ayvasik is a Researcher at the Chair of Communication Networks at Technical University Munich (TUM). He joined TUM in March 2019 as a research and teaching associate, following his M.Sc. in Communications Engineering (2019) and B.Sc. in Electrical and Electronics Engineering (2016) from Middle East Technical University. His research focuses on: Wireless Network Resource Management for heterogeneous latency-critical 5G applications Channel State Information Prediction using depth images Network Slicing and Quality of Service optimization Machine Learning for proactive network configuration Telemedicine Applications in cross-border communication Key article trends include 5G/6G technology , IoT sustainability , digital twins , and haptic feedback systems . He contributes to IEEE and ACM journals, with recent work on Digiot (2025) and OCTOPUS (2024). Collaborations include researchers like Wolfgang Kellerer (Chair), Edwin Babaians , Alba Jano , and Fidan Mehmeti . His work spans projects such as 6G Future Lab Bavaria , DFG GGI QCDE , and ERC FlexNets .
Prof. Dr.-Ing. Werner Lang serves as Vice President for Sustainable Transformation and holds the Chair of Energy Efficient and Sustainable Design and Building (ENPB) at the Technical University of Munich (TUM), within the TUM School of Engineering and Design. Previously, he was Professor of Sustainable Building and Director of the Center for Sustainable Development at the University of Texas School of Architecture in Austin (2008-2010). Lang also directs the Oskar von Miller Forum and is a partner at Lang Hugger Rampp GmbH Architekten in Munich. Lang's research focuses on developing strategies for buildings with positive environmental footprints through regenerative energy systems, renewable materials, and closed material cycles. His work emphasizes comprehensive life cycle analysis considering ecological, economic, and social aspects. Current research areas include climate-resilient urban neighborhoods, circular economy in construction, and sustainable building materials. The ENPB institute conducts numerous research projects such as Building Climate-Municipal, CircularFTmehrRAUM, and Urban Green Infrastructure. Lang's publications reveal a strong trend toward life cycle assessment, multi-criteria decision-making, and computational approaches for sustainable building design. His recent work integrates machine learning with building performance analysis and focuses on practical implementation of circular economy principles in urban contexts, with increasing emphasis on quantifying environmental benefits of urban green infrastructure. TUM Sustainability Award 2022 Doce et Delecta (Second Prize for Best Teaching), 2019 Bayerischer Energiepreis 2014 International Building Skin Tech Award (2008) Promotionspreis der TUM (2000) Lang leads the Institute of Energy-Efficient and Sustainable Design and Building with numerous research grants including projects like Building.Lab+, NAWAREUM, and ECO+. His team includes researchers working on topics ranging from urban mining to life cycle assessment tools. The institute maintains several products and startups including MoMeBo, Bilanzlabor, and EnergyML that translate research into practical applications for the building industry.
David Chester Upham is an Assistant Professor in the Department of Chemical & Biological Engineering within the Faculty of Applied Science at the University of British Columbia (UBC). He leads the Upham Lab, which focuses on developing catalysts and processes for sustainable energy production, greenhouse gas mitigation, and CO 2 -free chemical conversion. Dr. Upham received his education from prestigious institutions: Postdoctoral Scholar, Stanford University (2019) Ph.D., University of California Santa Barbara (2017) B.Eng., McGill University (2010) Dr. Upham's research focuses on heterogeneous catalysis for sustainable energy applications. His work centers on developing catalysts and processes that enable CO 2 -free production of chemicals, power, and materials. He specializes in liquid heterogeneous catalysts , particularly molten metal alloys, for methane conversion, CO 2 utilization, and hydrogen production. His lab employs advanced techniques including operando IR spectroscopy, pulsed and transient analysis of reaction mechanisms, isotopic labeling studies, and in-situ X-ray absorption spectroscopy. A key aspect of his research is understanding how liquid heterogeneous catalysts behave under reaction conditions, with applications in methane pyrolysis, dry reforming, and carbon fiber synthesis. Analysis of Dr. Upham's recent publications reveals a strong focus on CO 2 mitigation and clean energy production . His work spans multiple domains including methane conversion technologies, CO 2 -to-fuels processes, and carbon-negative fuel production. A significant portion of his research investigates molten metal catalysts for methane pyrolysis and dry reforming, with applications in hydrogen production and carbon capture. His publications demonstrate an interdisciplinary approach combining chemical engineering, materials science, and environmental engineering to address climate change challenges through innovative catalytic processes. Dr. Upham actively mentors a diverse group of graduate students and researchers. His lab currently includes multiple PhD and MASc students working on various aspects of catalysis and clean energy: PhD Students: Mark Tabbara, Genpei Cai, Natascha Miederhoff MASc Students: Michael Byun, Sawyer d'Entremont, Rami Jubeili, Wyatt Schnare Postdoctoral researcher: Sonit Balyan Multiple undergraduate and visiting students from institutions worldwide The Upham Lab operates within UBC's Catalysis Labs, utilizing advanced experimental techniques to study reaction mechanisms and develop new catalysts. The lab's research has significant implications for decarbonizing the energy and chemical sectors, with potential applications in hydrogen production, carbon fiber manufacturing, and CO 2 -to-fuels technologies.
Hisham Zerriffi is an Associate Professor at the University of British Columbia (UBC) in the Department of Forest Resources Management, Faculty of Forestry. He also serves as Associate Dean for Equity, Diversity, and Inclusion. His research intersects technology, energy, and the environment, focusing on rural areas in the Global South. Affiliation: BioProducts Institute Affiliation: Clean Energy Research Centre Affiliation: Institute for Resources, Environment and Sustainability His research examines institutional factors in technology diffusion, household energy choices, and welfare impacts of energy use. Current projects include analyzing forest density's ecological impact, clean cooking transitions in India, and decentralized energy systems. Recent publications address just transitions, biomass energy economics, and policy misalignments in Indigenous communities. He has authored works on climate change mitigation via forest carbon credits and rural electrification strategies. Scientific Award: Ivan Head South/North Research Chair As a PhD supervisor, he has guided Natalie Payer on urban energy poverty in the U.S. He collaborates on interdisciplinary grants and leads the Energy Resources, Development and Environment Lab (ERDELab).
Antonio De Rosa is an Associate Professor in the Department of Decision Sciences at Bocconi University, Italy. Previously, he held positions at the University of Maryland, College Park (2020–2024), and the Courant Institute of Mathematical Sciences, New York University (2017–2020). He earned his Ph.D. in Mathematics from the University of Zurich in 2017 under Camillo De Lellis and Guido De Philippis. Education: Ph.D. in Mathematics, University of Zurich (2017). His research spans Geometric Analysis , Partial Differential Equations , Calculus of Variations , Geometric Measure Theory , Optimal Transport , and Non-convex Optimization . Recent work focuses on anisotropic geometric variational problems, including existence, regularity, and uniqueness of anisotropic minimal surfaces and CMC (constant mean curvature) surfaces. He has also contributed to interdisciplinary applications in Explainable Risk Assessment and Data Analysis . The 15 most recent articles highlight advancements in anisotropic surfaces , min-max theory , optimal transport , and mathematical programming (e.g., K-means clustering, linear programming). Key trends include the intersection of geometric measure theory with nonlinear PDEs and applications in machine learning and transportation networks . Scientific Awards and Grants: 2023 Maryland Research Excellence Carlo Ciliberto Prize (2019) ERC Starting Grant ANGEVA (101076411, 2023–2028) Air Force Office of Scientific Research (AFOSR) grant (FA9550-23-1-0123) NSF CAREER Award (DMS-2143124) NSF DMS Awards (DMS-1906451, DMS-2112311) AMS Simons Travel Grant Antonio actively supervises research and teaches courses such as Optimization and Introduction to Partial Differential Equations . His work is supported by significant funding totaling approximately €3 million.
Roy Dong is an Assistant Professor at the University of Illinois at Urbana-Champaign, affiliated with the Coordinated Science Laboratory. His research bridges Control Theory Economics Statistics Optimization to address challenges in cyber-physical systems and the Internet of Things, focusing on data manipulation, privacy, and strategic behavior in interconnected systems. His academic journey includes a Ph.D. in Electrical Engineering and Computer Sciences from UC Berkeley (2017) and dual B.S. degrees in Economics and Computer Engineering from Michigan State University (2010). At Illinois, he teaches courses ranging from Control Systems to Convex Optimization , with multiple teaching excellence awards. Roy's research explores Closed-loop effects of machine learning Causality in decision systems Incentive design for strategic agents Privacy-utility tradeoff optimization Human behavior modeling with applications in smart grids, transportation networks, and semi-autonomous vehicles. His work formulates privacy-preserving mechanisms as optimization problems, balancing data utility against user privacy in dynamic systems. Article trends show expertise in Game theory for strategic data sources Energy disaggregation techniques Nonlinear basis pursuit algorithms Privacy-aware control systems with a focus on cyber-physical systems and human-in-the-loop applications. Scientific recognition includes 'Teacher Ranked as Excellent' awards (ECE 120, ECE 486, ECE 515) Contributions to smartSDH building control and CPRL compressive sensing Roy leads the Privacy-aware Control Systems research group, collaborating with institutions like UC Berkeley and Michigan State University , and directs projects funded by grants including the New USDA NIFA grant for agricultural robot autonomy .
Shashi Shekhar is a Professor at the University of Minnesota, holding the distinguished titles of McKnight Distinguished University Professor and Distinguished University Teaching Professor. He serves as the ADC/CSE Chair and Director of the AI-LEAF Institute within the Department of Computer Science at the College of Science and Engineering. His research interests span multiple areas of spatial computing including spatial data science, spatial data mining, spatial databases, Geo-AI, and Geographic Information Systems (GIS). His work has focused on developing scalable algorithms for eco-routing, evacuation route planning, and spatial pattern mining. He has made significant contributions to the field through his Spatial Databases textbook, the Encyclopedia of GIS which has seen over 192,918 downloads in 2017, and a spatial computing book for professionals. His research group has produced numerous PhD graduates dating back to 1993 through 2023. Analysis of his recent publications reveals a strong focus on applying spatial computing to critical societal challenges including climate change mitigation through the AI-LEAF Institute, pandemic response through mobility data analysis, and sustainable transportation through eco-routing algorithms. His work bridges theoretical advances in spatial data science with practical applications in urban planning, emergency management, and environmental sustainability. Distinguished McKnight University Professor Distinguished University Teaching Professor UCGIS Education Award (2015) Graduate Education Award (2015) President of University Consortium for GIS (2017-2018) Computing Research Association Board Member (2016-2019) Professor Shekhar has advised over 30 PhD students since 1993, with his most recent graduate in 2023. He has secured significant research funding including a $20 million AI Institute grant focused on climate-smart agriculture and forestry. His Spatial Computing Research Group maintains active collaborations with government agencies and industry partners. The group has developed practical applications featured in media outlets including FoxTV coverage of evacuation route planning algorithms. Current research directions include applying AI techniques to address climate challenges through the AI-LEAF Institute and advancing spatial data science for polar regions through NSF-funded initiatives.
