Professor Simon Fraser is a public health physician and academic at the University of Southampton , specializing in kidney disease and multimorbidity. His work integrates epidemiology, health literacy, and inequality analysis to address chronic disease burdens. Educational Background: BM (University of Southampton, 1992) MSc in Public Health DM (Doctor of Medicine, 2014) Research Focus: Fraser's research spans kidney disease , multimorbidity , treatment burden , and health inequalities . Recent projects include the NURTuRE-CKD HRQoL Study and MELD-B , examining determinants of chronic disease progression and intervention design. Academic Contributions: His publications from 2024-2025 emphasize electronic health records for multimorbidity analysis, neonatal risk factors for adult comorbidity, and deprescribing strategies for older adults. Collaborations include NIHR Applied Research Collaboration Wessex and Kidney Research UK. Scientific Recognition: Fellow of the Faculty of Public Health (FFPH) Member of the Royal College of General Practitioners (MRCGP) Fellow of the Higher Education Academy (FHEA) Mentorship: Current PhD students include Emilia Mary Holland and Keegan Guan Ru Lee . He co-leads projects with leading researchers in public health and nephrology.
Santiago Grijalva serves as Georgia Power Distinguished Professor and Director of the Advanced Computational Electricity Systems (ACES) Laboratory at Georgia Institute of Technology's School of Electrical and Computer Engineering. He also holds the position of Associate Director for Electricity Systems at the Strategic Energy Institute (SEI). His educational background includes an Electrical Engineer degree from EPN-Ecuador (1994), M.S. in Information Systems from ESPE-Ecuador (1997), and M.S./Ph.D. in Electrical and Computer Engineering from University of Illinois at Urbana-Champaign (1999/2002). Grijalva pioneers research in decentralized power system architectures, renewable energy integration, and grid cybersecurity. His work spans smart grid technologies, electricity markets design, AI applications for power systems, and ultra-reliable grid architectures. The ACES Laboratory under his direction focuses on real-time power system control, informatics, and economics. His recent publications demonstrate strong trends in photovoltaic integration, multi-agent control systems, voltage stability analysis, and prosumer-based grid architectures, reflecting the industry's shift toward distributed energy resources and decentralized control paradigms. Georgia Tech ECE Outstanding Faculty Award Great Minds in STEM National Achievement Award ARPA-E More Than Smart Grid Disruptor Award IBM Faculty Award As principal investigator for major research projects funded by U.S. Department of Energy, ARPA-E, EPRI, PSERC, NSF, and industry sponsors, Grijalva leads initiatives modernizing electrical infrastructure. His past roles include Senior Software Developer at PowerWorld Corporation and Department Head at Ecuador's National Center for Energy Control (CENACE). He serves as Associate Editor for IEEE Transactions on Industrial Informatics and has published over 250 peer-reviewed papers. The Advanced Computational Electricity Systems (ACES) Laboratory operates at the intersection of power systems engineering and computational science, developing next-generation grid technologies for renewable integration and cyber-physical security.
Aapo Hyvärinen is a Professor of Computer Science at the University of Helsinki , affiliated with the Helsinki Institute for Information Technology and the Helsinki Probabilistic Machine Learning Lab . He previously held the position of Professor of Machine Learning at the Gatsby Computational Neuroscience Unit, University College London (2016-2019). Education : Undergraduate Mathematics at University of Helsinki, Vienna, and Paris; Ph.D. in Information Science from Helsinki University of Technology (1997) His research focuses on machine learning and computational neuroscience , particularly: Independent Component Analysis (ICA) Natural Image Statistics Causal Representation Learning Neural Signal Processing Applications to brain imaging (MEG, CryoEM) Recent publications emphasize causal discovery , identifiable machine learning , and nonlinear ICA . Key projects include: VETURI (AI for health) DIGIMIND (AI in mental health) CIFAR grants (2022-2025) Scientific awards : Highly Cited Researcher (2010) He serves as Action Editor for the Journal of Machine Learning Research and Neural Computation , and has held Area Chair roles at NeurIPS, ICML, ICLR, AISTATS, and UAI conferences. His work bridges theoretical machine learning with neuroscience and philosophical implications of artificial intelligence .
Mohammad Aliannejadi is an Assistant Professor at the IRLab (formerly ILPS) within the Informatics Institute at the University of Amsterdam. His research focuses on Information Retrieval (IR), machine learning, natural language processing (NLP), and conversational systems, particularly in modeling user information needs on mobile devices and conversational search systems. He holds a Ph.D. in Informatics from Università della Svizzera italiana (USI), Lugano, Switzerland, and a M.Sc. in Computer Engineering from Tehran Polytechnic. During his Ph.D., he visited the CIIR Lab at the University of Massachusetts Amherst, USA. His research interests include conversational search systems, recommender systems, unified search frameworks, and user-centric evaluation methodologies. Notable contributions include work on clarifying questions in open-domain dialogues, contextual suggestion systems, and cross-market recommendation. Aliannejadi has organized major shared tasks and workshops, including the IGLU Contest (NeurIPS 2021) and XMRec Workshop (RecSys 2021). He serves on program committees of top IR conferences like SIGIR, CIKM, and ECIR, and has authored over 50 peer-reviewed publications in these areas. His work has received recognition, including top performance in TREC Contextual Suggestion tracks (2015, 2016). He actively contributes to the IR community through teaching, including courses on Information Retrieval and Human-in-the-Loop Machine Learning at the University of Amsterdam.
Dr. Dmytro Matsypura is an Associate Professor in the Discipline of Business Analytics at the University of Sydney Business School. He holds a BA (Hons) from Kyiv Polytechnic Institute (KPI), an MS (Hons) from KPI, and a PhD from the University of Massachusetts Amherst. His research focuses on optimization methodologies, network science, and their applications in finance, transportation, ecology, and graph theory. He is a recipient of multiple teaching awards, including the Wayne Lonergan Outstanding Teaching Award (Early Career) in 2010. Education: PhD in Management Science, University of Massachusetts Amherst (2006) MS (Hons) in Information Systems, Kyiv Polytechnic Institute (2000) BA (Hons) in Business Administration, Kyiv Polytechnic Institute (1998) Research Interests: Dr. Matsypura’s work spans operations research and management science, with a focus on mathematical optimization and network science. His methodological contributions include developing efficient optimization algorithms, while his applied research addresses real-world challenges in finance, engineering, and ecology. Notable applications include wildfire fuel management, portfolio margining, and credit card fraud detection via graph-based models. Awards and Recognition: Teaching Excellence Award (2008, 2013, 2018) Wayne Lonergan Outstanding Teaching Award (Early Career) (2010) Grants and Projects: Current projects include Bushfire Analytics: Optimization of Fuel Reduction (2023, ARC Discovery Project). His research frequently integrates interdisciplinary collaborations, such as applying graph theory to biomedical problems and cybersecurity. Labs/Teams: Active in the Sydney Environment Institute, contributing to projects at the intersection of analytics and sustainability. Collaborates with industry on fraud detection and supply chain optimization.
Furkan Alaca is an Assistant Professor at Queen's University's School of Computing, part of the Faculty of Arts and Science. His research focuses on user authentication systems, addressing security and usability challenges. He holds a Ph.D. (2018) in Computer Science from Carleton University, an M.A.Sc. (2012) in Electrical and Computer Engineering, and a B.Eng. (2010) in Communications Engineering, all from Carleton University. His academic career includes teaching roles at Queen's University and the University of Toronto Mississauga, where he taught courses such as Cryptography, Cybersecurity, and Discrete Mathematics. He is affiliated with Queen's Security Research Group and Computer Security Research Lab. Research interests include computer and internet security, usable security, authentication mechanisms, and systems security. He has contributed to advancements in web authentication frameworks, malware analysis, and privacy-preserving technologies. His work spans conferences like IEEE and ACM, with notable publications in cybersecurity, machine learning, and network efficiency. Current teaching includes CISC 447 (Introduction to Cybersecurity) and CISC 468 (Cryptography). He has advised on courses ranging from undergraduate programming to graduate-level security topics.
Houman Savoji is an Associate Professor in the Department of Pharmacology and Physiology at the Faculty of Medicine, University of Montreal. He is also a full-time researcher at the CHU Sainte-Justine Research Center and principal investigator in regenerative medicine, organs-on-chip, and bioprinting at TransMedTech Institute. Dr. Savoji received his PhD in Biomedical Engineering from the Institute of Biomedical Engineering at Polytechnique Montréal in 2016. He then completed a postdoctoral fellowship at the Institute of Biomaterials and Biomedical Engineering at the University of Toronto. His research expertise combines advanced manufacturing technologies (micro- and nano-fabrication, 3D bioprinting, microfluidics, cell electrospinning) with functional and composite materials for applications in tissue engineering, regenerative medicine, and organs-on-chip. His work focuses on the design, development, optimization, implementation, and characterization of innovative functional biomaterials using emerging engineering technologies, with particular emphasis on cardiac tissue engineering and biomimetic pulmonary heart valves for pediatric patients. Dr. Savoji has published extensively on biomaterials, tissue engineering, 3D bioprinting, and organ-on-chip technologies. His recent publications demonstrate expertise in viscoelastic characterization of soft tissues, engineering immune responses to biomaterials, ceramic engineering for biomedical applications, and advanced 3D bioprinting techniques for cardiac and vascular tissue engineering. 2017-2020, Postdoctoral Research Grant, CIHR 2017-2019, Postdoctoral Research Grant, FRQNT 2017-2018, Human Society of International Grant, Human Toxicity Assessment Project 2016, CR-CHUM Research Center Award 2015, Star Student-Researcher Award, FRQNT 2014-2015, Jane and Frank Warchol Fellowship, Society of Vacuum Coaters Foundation 2013, Institute of Textile Science Award 2012-2015, Excellence Doctoral Scholarship for Foreign Students, FRQNT Dr. Savoji has supervised Master's students including Ines Barrakad (2024) working on 'Advanced manufacturing technologies versus molding of corneal implants: 3D printing vs molding of a Keratoprosthesis' and Zineb Ajji (2023) researching 'Development of perfusable patches by 3D bioprinting for potential application in cardiac tissue regeneration.' He has secured numerous research grants from organizations including CIHR, NSERC, FRQNT, FRQS, MITACS, and others for projects related to 3D bioprinting of cardiac tissues, biomimetic heart valves, and other tissue engineering applications. The Savoji Laboratory, located within the Department of Pharmacology and Physiology and Institute of Biomedical Engineering of the Faculty of Medicine of the University of Montreal, the Research Center of the CHU Sainte-Justine (CHUSJ), and the TransMedTech Institute, focuses on multidisciplinary research involving 3D bioprinting using stem-cell derived human cardiac cells to fabricate functional cardiac tissues for transplantation and drug discovery applications.
Sanghyun Hong is an Assistant Professor at Oregon State University's School of Electrical Engineering and Computer Science , focusing on Trustworthy AI and Cybersecurity . He holds a Ph.D. in Computer Science from the University of Maryland, College Park (2021) and a B.S. in Electrical Engineering and Computer Science from Seoul National University (2015). His research bridges machine learning , security , and privacy-preserving systems . Current research themes: Robustness of AI systems to adversarial attacks Privacy-preserving machine learning Security of pre-trained and large language models Hardware fault vulnerabilities in neural networks Cybersecurity workforce development Publication Trends (15 most recent): Focus on adversarial machine learning (jailbreaking LLMs, membership inference) Advances in physics-informed neural networks and time series forecasting Key contributions to AI security and malware detection Interdisciplinary work in visualization design and tsunami warning systems Scientific Accolades : Google Faculty Research Award (2023) Samsung Global Research Award (2022, 2023, 2024) DARPA Riser (2022) NSF SFS Award (co-PI, 2023) USENIX Enigma Speaker (2021) Academic Leadership : Mentors 5 Ph.D. students and has graduated 8 M.S. and B.S. students. Currently developing next-generation auditing frameworks for AI systems while on medical leave until Winter 2026.
Rachel Cummings is an Associate Professor in the Department of Industrial Engineering and Operations Research (IEOR) at Columbia University, with a courtesy appointment in the Department of Computer Science. She serves as Co-chair of the Cybersecurity Research Center at Columbia’s Data Science Institute. Previously, she was faculty at Georgia Tech’s School of Industrial and Systems Engineering (ISyE), holding a courtesy appointment in Computer Science. She holds a Ph.D. in Computing and Mathematical Sciences from Caltech, with research visits at UPenn, Hebrew University, Microsoft Research, and the Simons Institute. Her research focuses on differential privacy, integrating tools from machine learning, algorithm design, economics, optimization, statistics, HCI, usable security, and public policy. She emphasizes practical applications of theoretical privacy-preserving methods. Key roles include Managing Editor for the Journal of Privacy and Confidentiality , service on the ACM U.S. Technology Policy Council, IEEE Standards Association, and Future of Privacy Forum’s Advisory Board. She has advised on the U.S. Census Bureau’s Scientific Advisory Council and served as a Fellow at the Center for Democracy & Technology. Recent work includes papers on privacy elasticity, synthetic control methods, and differential privacy under class imbalance. Her awards include NSF CAREER, DARPA Young Faculty Award, and Best Paper recognitions at DISC, CCS, and SaTML. She actively chairs conferences (e.g., DEF CON Crypto) and mentors students like Tingting Ou (PhD 2025) and Peihan Liu (PhD 2024–present). Her lab explores privacy-preserving technologies, policy implications, and interdisciplinary collaborations.
Marian Chertow is the Manufacturer’s Association Professor of Industrial Ecology at Yale University and Director of the Center for Industrial Ecology at the Yale School of the Environment. She holds an appointment at the Yale School of Management (SOM) and previously taught at the National University of Singapore (NUS) for 20 years, contributing to the development of their Master’s of Environmental Management program. Her research focuses on industrial ecology, circular economy, and industrial symbiosis—the study of material, energy, and byproduct exchanges among businesses. She pioneered frameworks for understanding industrial ecosystems and their resilience, emphasizing collaboration among firms for environmental and economic benefits. Her work spans global case studies, including China, India, and Singapore, and explores urban metabolism, resource reuse, and policy innovation. Chertow has received prestigious awards, including recognition from the U.S. EPA, the CT Women’s Hall of Fame, and the International Society for Industrial Ecology (ISIE). She advises organizations like Trane Technologies and chairs initiatives like the Industrial Symbiosis Research Symposium. Beyond academia, she founded a theater company staging Greek tragedies and teaches a course linking environmental themes to theater. Her research integrates complex adaptive systems theory, social network analysis, and policy design to address sustainability challenges in emerging economies. Current projects include analyzing waste management in China and urban resource flows in Singapore. Chertow’s interdisciplinary approach bridges environmental science, economics, and management to advance sustainable industrial practices globally.
Dr. Aytaç Kubilay is a Senior Researcher at the Chair of Building Physics, Department of Mechanical and Process Engineering, ETH Zurich. His research focuses on urban microclimate modeling, particularly wind-flow analysis, thermal comfort optimization, and vegetation-based climate mitigation strategies. Institution: ETH Zurich Department: Mechanical and Process Engineering Research Scope: Urban climate, CFD modeling, heat island mitigation Research interests include computational fluid dynamics (CFD) applications for urban environments, with emphasis on heat island effects, wind-driven rain analysis, and porous media heat transfer. His work combines numerical simulations and experimental validations to assess thermal comfort and climate adaptation strategies in cities. Recent publications analyze vegetation impacts on urban microclimates, including tree cooling potential, street-level thermal comfort dynamics, and high-rise building wind mitigation. Studies employ custom solvers like urbanMicroclimateFoam and OpenFOAM for integrated flow-heat-moisture modeling. Key collaborations include researchers from ETH Zurich (Jan Carmeliet, Dominique Derome) and international institutions, focusing on sustainable urban planning and climate resilience frameworks.
Clark Olson is a Professor in the Division of Computing & Software Systems at the University of Washington Bothell, part of the School of Science, Technology, Engineering & Mathematics. He earned his Ph.D. in Computer Science from UC Berkeley (1994), M.S. in Electrical Engineering (1990), and B.S. in Computer Engineering (1989) from the University of Washington, Seattle. Education: Ph.D. in Computer Science (2017) from University of California, Berkeley M.S. in Electrical Engineering (1990) from University of Washington, Seattle B.S. in Computer Engineering (1989) from University of Washington, Seattle His research focuses on computer vision, robot navigation, and clustering algorithms. He has developed techniques for Mars rover terrain mapping, subspace clustering, and geometric feature matching. His work bridges theory and application in autonomous systems and image analysis. Analysis of his publications reveals expertise in computer vision (8 papers), clustering algorithms (4 papers), and robotics (5 papers). Key subtopics include Mars exploration (3 papers), Hough transforms (3 papers), and probabilistic methods (3 papers). Professor Olson teaches courses ranging from introductory programming (CSS 161-162) to advanced topics in computer vision (CSS 487-587) and algorithm design (CSS 549). He also advises on the CSSE Capstone (CSS 497) projects requiring rigorous prerequisites and structured evaluation criteria.
Ahmed Eldawy is an Associate Professor in the Department of Computer Science at the University of California, Riverside. He leads groundbreaking research in databases, big data management, and spatial data processing, with a focus on scalable exploratory analytics through systems like Beast , UCR-Star , Raptor , and Spider . His work spans geospatial data infrastructure, distributed computing, and computational geometry. Research Interests : Databases, big data management, spatial data processing, geospatial analytics, distributed systems, computational geometry. Awards : NSF CAREER award (2021), 10-year Influential Paper Award (ICDE 2025), Best Demo award (SIGSPATIAL 2020). Grants : NSF (IIS-2046236, IIS-1954644, CNS-1924694), USDA (USDA NIFA 2020-69012-31914), UC Office of the President (M21PL3368). Labs & Centers : RAISE@UCR, Data Science Center, Center for Robotics and Intelligent Systems (CRIS), Affiliate of Center for Geospatial Sciences and Winston Chung Global Energy Center. His recent publications focus on LLM-driven geospatial visualization (LASEK), distributed raster analytics (RDPro), learned spatial query optimization, and scalable spatiotemporal systems. He advises numerous PhD and Master’s students, many of whom now work at top tech companies like Amazon, Microsoft, and Meta.
Florian Schäfer is an Assistant Professor at the School of Computational Science and Engineering at Georgia Tech. His research spans numerical computation, statistical inference, and competitive games, with applications in materials science, turbulence modeling, computer graphics, and computational geometry. He will join the Courant Institute at NYU in September 2025. PhD in Applied and Computational Mathematics, Caltech Bachelor’s and Master’s in Mathematics, University of Bonn His work focuses on information geometric mechanics to design structure-preserving numerical methods for continuum mechanics. This includes: State-of-the-art solvers for elliptic PDEs via Gaussian elimination and conditional independence Efficient multi-agent optimization algorithms Information geometric regularization for compressible fluid dynamics Enabling the first compressible fluid simulation exceeding 100 trillion grid cells His recent research trends integrate: Machine learning for materials science (e.g., active learning, Bayesian approaches) Stochastic modeling of microstructures and phase-field problems Neural operators for super-resolution fluid dynamics Generative models for polycrystalline material datasets Optimal transport and diffusion models for conditional density transformations High-performance computing at extreme scales Florian collaborates with researchers including Houman Owhadi, Jessie Liu, Spencer Bryngelson, Tamer Zaki, and Ali Mani. He actively presents at conferences like SIAM and UCLA seminars, and is recruiting PhD students for work at the Courant Institute starting 2025.
Aaron D. Ames is the Bren Professor of Mechanical and Civil Engineering, Control and Dynamical Systems, and Aerospace at the California Institute of Technology (Caltech). He serves as the Booth-Kresa Leadership Chair and Director of the Center for Autonomous Systems and Technologies since 2025. His academic journey includes a BS in Mechanical Engineering and BA in Mathematics from the University of St. Thomas (2001), followed by an MA in Mathematics and a PhD in Electrical Engineering and Computer Sciences from UC Berkeley (2006). Research Interests span theoretical and experimental work in hybrid systems, nonlinear control, and bipedal robotic locomotion. Specific focus areas include: Control Barrier Functions (CBFs) for safety-critical systems Powered prostheses and robotic assistive devices Legged locomotion for bipedal and quadrupedal robots Cyber-physical systems and autonomous control Model predictive control and real-time optimization Humanoid robotics and geometric safety filters Recent publications emphasize risk-aware control, safety verification, and locomotion on constrained environments, with applications to drones, exoskeletons, and quadrupedal robots. His work often integrates theoretical advancements with practical validation through the AMBER Lab. Scientific Awards & Honors : NSF CAREER Award (2010) Donald P. Eckman Award (2015) Leon O. Chua Award (2005) Bernard Friedman Prize (2006) Teaching includes graduate courses on nonlinear control, hybrid systems, and robotics at Caltech, alongside prior roles at Georgia Tech and Texas A&M. He leads the AMBER Lab (Bipedal Robotics) and has secured major grants from the National Science Foundation, NASA, and industry partners like Miso Robotics and SRI International.
