Fei Ding is a Senior Researcher at National Renewable Energy Laboratory (NREL) specializing in Power Systems Engineering within the Grid Modernization Research Topic. Her work focuses on integrating renewable energy into electrical grids, optimizing distributed energy resources, and enhancing grid resilience. Education: PhD in Electrical Engineering from Case Western Reserve University Her research spans: Distribution grid modeling and control strategies Grid-edge resource optimization for reliability and cybersecurity Photovoltaic hosting capacity analysis Recent publications emphasize: AI-driven voltage regulation with neural networks Microgrid formation for grid restoration Data fusion techniques for outage detection Award highlights: NREL Chairman’s Award (2018) NREL President's Award (2020) NREL Distinguished Member of Research Staff (2021) She actively contributes to IEEE as a Senior Member and leads projects developing advanced distribution management systems.
Dr. Yildiz Bayazitoglu is the Harry S. Cameron Professor of Mechanical Engineering and Professor of Materials Science and NanoEngineering at Rice University since 1996. She joined Rice in 1977 and has held prior roles as an assistant professor at Middle East Technical University (1973–74) and a visiting assistant professor at the University of Houston (1975–76). Her education includes a B.S. from Middle East Technical University (1967), and M.S. and Ph.D. from the University of Michigan (1969 and 1974). Her research focuses on convective heat transfer with phase change , micro/nano-scale heat transfer , and radiation heat transfer . Key areas include thermal modeling of biomedical systems, containerless materials processing, and fuel cell design. She has pioneered work on nanofluids, interfacial thermal resistance, and radiation shielding for aerospace applications. Dr. Bayazitoglu has published over 200 technical papers and holds patents in thermal engineering. She authored two heat transfer textbooks and serves as Editor-in-Chief of the International Journal of Thermal Sciences . Her honors include ASME’s Heat Transfer Memorial Award, AAAS and AIAA Fellowships, and membership in the Turkish Academy of Sciences. Education: B.S., Middle East Technical University (1967) M.S., University of Michigan (1969) Ph.D., University of Michigan (1974) Leadership Roles: Former Vice-President of the International Center for Heat and Mass Transfer (2019–2021) Member of Turkish Academy of Sciences Energy Sources Committee (2017–2018) Her work bridges thermal engineering with biomedical, aerospace, and materials science applications, emphasizing practical solutions to complex thermal challenges.
Daniel Gottesman is the Brin Family Endowed Professor in Theoretical Computer Science at the University of Maryland, affiliated with the Department of Computer Science, Institute for Advanced Computer Studies (UMIACS), and the Joint Center for Quantum Information and Computer Science (QuICS). He holds a Ph.D. in Physics from Caltech (1997) and has held positions at institutions like the Perimeter Institute and Quantum Benchmark. His research focuses on quantum computing, quantum error correction, and fault-tolerant systems, with contributions to stabilizer codes and quantum teleportation-based gates. Education: Bachelor's in Physics, Harvard University (1992) Ph.D. in Physics, California Institute of Technology (1997) Research Interests: Quantum error correction and fault-tolerant architectures Quantum cryptography and secure communication protocols Quantum complexity theory and algorithm design Applications of stabilizer codes and topological quantum computing Scientific Awards: Fellow of the American Physical Society CIFAR Senior Fellow in Quantum Information Science Three U.S. Patents (e.g., quantum key distribution systems) Advising & Grants: Supervised over 30 students/postdocs and served on numerous thesis committees. Active in securing funding for quantum research through endowed professorships and industry partnerships (e.g., Quantum Benchmark). Labs/Teams: Member of QuICS and UMIACS, collaborating on quantum hardware-software integration and error correction challenges.
Massimiliano Esposito is a Full Professor of Theoretical Physics at the University of Luxembourg, affiliated with the Faculty of Science, Technology and Medicine (FSTM) and the Department of Physics and Materials Science. His research focuses on statistical physics, complex systems, thermodynamics, chemical networks, and quantitative biology. He holds positions such as ERC Fellow (2016-2021) and Attract Fellow (2012-2017). Education includes a Ph.D. in Sciences (2004) and a degree in Chemistry (2000) from the Free University of Brussels (Belgium), alongside a European Baccalaureate (1996) from Luxembourg. His work bridges stochastic thermodynamics, quantum thermodynamics, and chemical reaction networks, with contributions to fluctuation theorems, energy transduction, and non-equilibrium systems. Key achievements include seminal papers on nonequilibrium fluctuation-response relations, quantum thermodynamics, and chemical reaction network theory. He has been a guest editor for journals like Physica A and Physical Review X, and serves on editorial boards such as Physical Review Letters. His lab explores emergent phenomena in complex systems, with applications in biology and nanotechnology.
Constantinos Daskalakis is the Armen Avanessians (1982) Professor in the MIT Schwarzman College of Computing and the Department of Electrical Engineering and Computer Science (EECS). He joined MIT in 2009 and is a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL), affiliated with the Laboratory for Information and Decision Systems (LIDS) and the Operations Research Center (ORC). His research focuses on theoretical computer science, with emphasis on game theory, machine learning, and high-dimensional statistics. Education: Ph.D. in Computer Science (not explicitly stated, but implied by tenure and awards). Research interests include computational complexity of Nash equilibria, multi-item auctions, machine learning algorithms, and causal inference. His work bridges game theory, economics, probability, and statistics, with applications in AI and healthcare. Key contributions include resolving long-standing problems in computational game theory and developing efficient methods for statistical hypothesis testing. He has been recognized with the 2018 Nevanlinna Prize, ACM Grace Murray Hopper Award, and the Kalai Game Theory Prize. Affiliations: CSAIL, LIDS, ORC, and the Foundations of Data Science Institute. Active in multi-agent learning, bias mitigation in data, and generative models.
Noah J. Cowan is a Professor of Mechanical Engineering at Johns Hopkins University's Whiting School of Engineering, with secondary appointments in Computer Science, Electrical & Computer Engineering, and Neuroscience. He is the founder and director of the Locomotion in Mechanical and Biological Systems (LIMBS) Laboratory, part of the Laboratory for Computational Sensing and Robotics. His research focuses on neuromechanics, robotics, and control theory, bridging neuroscience, biomechanics, and engineering. Cowan's work investigates how organisms achieve precise locomotion and applies these insights to advance robotics, neuroprosthetics, and rehabilitation technologies. Education: B.S. Electrical Engineering (Ohio State, 1995), M.S. and Ph.D. Electrical Engineering & Computer Science (University of Michigan, 1997/2001). Postdoctoral fellowship at UC Berkeley (2001–2003) before joining Johns Hopkins. Research Interests: Neuromechanics of motion, bio-inspired robotics, multisensory integration in animals (e.g., electric fish, Drosophila), and sensorimotor control in clinical contexts like cerebellar ataxia. His lab studies how neural circuits interact with biomechanics to produce movement, with applications to robotic design and neurological disorder treatments. Awards & Recognition: Presidential Early Career Award for Scientists and Engineers (2010), IEEE Fellow, NSF CAREER Award (2009), and multiple teaching and research excellence awards at Johns Hopkins. His work has been published in top journals like Nature , Proceedings of the National Academy of Sciences , and IEEE Transactions on Robotics . Outreach & Mentorship: Longtime mentor for high school and undergraduate students in STEM, leading programs like the Baltimore Ingenuity Project and WISE. Served as team leader for the STEM Achievement in Baltimore Elementary Schools (SABES) initiative. Key Projects: Development of the LIMBS Lab’s VR systems for animal studies, bioelectric navigation technologies for medical devices, and collaborations with clinicians on upper limb movement disorders. His team’s research on electric fish and fruit flies has revealed principles of adaptive control applicable to robotics and AI.
Shu Yang is an Associate Professor of Statistics at North Carolina State University (NC State), specializing in causal inference, missing data analysis, and biostatistics. She holds a Ph.D. in Applied Mathematics and Statistics from Iowa State University and has held roles including Postdoctoral Fellow at Harvard University and Assistant Professor at NC State. Her research focuses on developing statistical methods for observational and clinical studies, particularly in healthcare and environmental applications. Education: Ph.D. in Applied Mathematics and Statistics from Iowa State University (2014) B.Sc. in Mathematics and Applied Mathematics from Beijing Normal University (2009) Research Interests: Dr. Yang’s work addresses challenges in causal inference, including longitudinal data analysis, missing data imputation, and high-dimensional statistics. She applies these methods to environmental health, cardiovascular diseases, HIV infection, and cancer research. Her team also explores spatial statistics and data integration techniques. Awards: 2025: Think, Collaborate & Do Ideation Award 2024: COPSS Emerging Leader Award, Cavell Brownie Mentoring Award 2022: University Faculty Scholar 2018: Ralph E. Powe Junior Faculty Enhancement Award Grants & Advising: She leads funded projects on causal inference methods in environmental health, sepsis detection, and marine protected areas. She advises over 20 Ph.D. students and postdocs, focusing on causal methods, data integration, and healthcare analytics.
Prof. Dr. Mirko Hornung is a Professor of Aircraft Design at the TUM School of Engineering and Design, Technische Universität München. His research focuses on conceptual aircraft design, integration of propulsion systems, and evaluation of aviation technologies in operational contexts. Education and Career: PhD in Aeronautical Engineering from the University of the Bundeswehr (2003), awarded a research prize for work on reusable space transport systems. 2003–2009: Worked at Airbus Group (EADS) on military air systems, propulsion integration, and program management. Executive Director of Research & Technology at Bauhaus Luftfahrt, a think tank for long-term aviation developments. Research Interests: Aircraft design optimization, including hybrid energy systems, electric propulsion, and UAV technologies. Environmental sustainability in aviation, such as hydrogen-powered aircraft and lifecycle assessment. Aerodynamic and structural analysis, including flutter suppression and composite materials. Key Publications Highlight Trends: Focus on hybrid-electric and hydrogen propulsion for reducing environmental impact. Advancements in UAV design, including morphing wings and autonomous systems. Integration of AI-driven tools for propulsion optimization and lifecycle analysis. Scientific Awards: EADS Promotion Award (1995) Research Prize for Thesis on Reusable Space Transport Systems (2003) Advising & Grants: Directs research at Bauhaus Luftfahrt, collaborating on future aviation concepts. Engaged in interdisciplinary projects like FLEXOP UAV demonstrator and Ce-Liner eMobility studies. Labs/Teams: Active in the Aircraft Design Professorship at TUM and leadership roles at Bauhaus Luftfahrt, focusing on next-generation aviation technologies.
Witold J. Henisz serves as Vice Dean and Faculty Director of the Impact, Value, and Sustainable Business Initiative at The Wharton School, University of Pennsylvania, holding the Deloitte & Touche Professorship in Management. His research centers on political and social risk identification, ESG impact materiality, and corporate diplomacy frameworks that transform stakeholder relationships into strategic assets. His educational background includes a Ph.D. in Business and Public Policy from UC Berkeley's Haas School and an M.A. in International Relations from Johns Hopkins SAIS. Henisz has served as Departmental Editor at Journal of International Business Studies and Associate Editor at Strategic Management Journal , reflecting his scholarly influence. Research interests converge on geopolitical risk quantification, stakeholder engagement optimization, and sustainable business model innovation. His work demonstrates how political hazards materially impact firm valuation and how corporate diplomacy can mitigate conflict through strategic stakeholder alignment. Recent publications leverage massive media datasets (4+ billion articles) to model populism dynamics, indigenous land conflicts, and ESG-credit risk linkages. Award highlights include the Aspen Institute Ideas Worth Teaching Award (2020), Iron Prof recognition (2019), and Academy of International Business Fellowship. His geostrategy framework Geostrategy by Design (2024) provides executives with actionable methods for navigating geopolitical volatility. Aspen Institute Ideas Worth Teaching Award (2020) Iron Prof recognition (2019) Academy of International Business Fellow (2014-present) Multiple Wharton Excellence in Teaching Awards (2006-2021) Industry Studies Association Best Paper Award (2019) Henisz consults through PRIMA LLC for multinational firms (Rio Tinto, Shell), financial institutions (Eaton Vance, World Bank), and NGOs. His executive education programs train leaders in ESG integration and geopolitical risk management, while his KEROVKA crisis simulation develops real-time strategic response capabilities. Media frequently cites his expertise on ESG controversies, with 50+ major publications featuring his analysis since 2022 including Financial Times , Bloomberg , and Wall Street Journal .
Arash Arami is an Associate Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo, cross-appointed in Systems Design Engineering. He directs the Neuromechanics and Assistive Robotics Laboratory and maintains affiliations with Waterloo Robohub, the Centre for Bioengineering and Biotechnology, Waterloo AI institute, and KITE institute at Toronto Rehab Institute. He earned his Doctorate in Electrical Engineering from EPFL (2014), Master of Science from University of Tehran (2009), and Bachelor of Science from University of Tabriz (2006), all in Control Engineering. His research in Assistive Robotics and Rehabilitation Engineering integrates Machine Learning with Neuromechanics to develop intelligent systems for human movement analysis. Key focus areas include exoskeleton control algorithms, wearable sensor systems, and neural control modeling for rehabilitation applications. Recent publications demonstrate interdisciplinary work spanning robotics, biomedical engineering, and materials science, with emphasis on real-time human locomotion prediction, exoskeleton-human interaction, and data-driven health monitoring solutions. Dr. Arami serves as Chair of the NSERC Scholarship Committee (2021-2023) and mentors graduate students through the Mechatronics Exchange Study program. His teaching includes core courses in control systems, robot manipulators, and biomechanical engineering. The Neuromechanics and Assistive Robotics Laboratory fosters collaborations with clinical partners at Toronto Rehab Institute, focusing on translating robotic innovations into practical rehabilitation tools through interdisciplinary teamwork.
Harri Lähdesmäki is an Associate Professor (tenured) at the Department of Computer Science, Aalto University, where he leads the Computational Systems Biology research group. His work focuses on probabilistic machine learning and deep generative models with applications in biomedicine and molecular biology. Key Research Interests: Probabilistic machine learning, deep generative models, computational biology, bioinformatics, longitudinal data modeling Contact: harri.lahdesmaki@aalto.fi | Konemiehentie 2, 02150 Espoo, Finland His recent publications highlight advancements in: Gaussian process priors for scalable deep generative models Single-cell analysis of immune repertoires in leukemia and diabetes Probabilistic deconvolution methods for RNA-seq data Epigenetic analysis using hidden Markov and mixed models Transformer-based survival prediction and missing data handling Harri’s work integrates mechanistic modeling with Bayesian inference, particularly applied to immunology, cancer biology, and early disease prediction.
Howard Elman is a Professor in the Department of Computer Science at the University of Maryland, with affiliations to the Institute for Advanced Computer Studies (UMIACS) and as an Affiliate Professor in the Department of Mathematics. His research spans numerical analysis, computational fluid dynamics, and uncertainty quantification, focusing on iterative solvers for partial differential equations. Education: PhD in Computer Science, Yale University (1982); BA in Mathematics, Columbia University (1975); Stuyvesant High School (1971) Elman's research integrates Scientific Computing with Numerical Linear Algebra , Computational Fluid Dynamics , and Uncertainty Quantification . His work addresses Stochastic Galerkin Methods , Reduced-Order Modeling , and Low-Rank Approximations for PDEs with random data. Recent publications emphasize Surrogate Models and Deep Learning in Bayesian inverse problems. His scientific awards include SIAM Fellowship (2009) and roles as Associate Editor for journals like Mathematics of Computation and SIAM Journal on Scientific Computing . He served as SIAM Editor-in-Chief (1998-2004) and Vice President for Publications. Contact: helman@umd.edu | Office: 4210 Iribe Center | Courses: AMSC/CMSC 460 Computational Methods
Assia Mahboubi is a tenured researcher ( directrice de recherche ) at INRIA in the Gallinette team, Nantes, France, and an endowed professor in the Algebra and Number Theory section of the Vrije Universiteit Amsterdam, Netherlands. Her work bridges theoretical computer science and formal mathematics, with significant contributions to proof assistants and formal verification. Her research focuses on the foundations and formalization of mathematics in type theory, particularly on the automated verification of mathematical proofs. She explores the interplay between computer algebra and formal proofs, and is a key contributor to the Rocq prover (formerly Coq) and the Mathematical Components libraries. Her work often examines how familiar mathematical objects can be optimally represented for computer-aided proof checking. Recent publications show a strong trend toward categorical reasoning, diagram chasing, and continuity properties in constructive type theory, with increasing focus on practical applications of formal methods in computational mathematics. Her work demonstrates the maturation of formal verification techniques from theoretical foundations to practical tools for mathematical research. ERC Consolidator grant for the FRESCO (Fast and Reliable Symbolic Computation) project Mahboubi actively supervises doctoral students including Vojtěch Štěpančík, Tomás Vallejos Parada, and Alain Chavarri Villarello. She has received significant research funding through her ERC Consolidator grant for the FRESCO project, which aims to develop fast and reliable symbolic computation techniques. She is deeply involved in the international research community, serving on program committees for major conferences including POPL, CPP, and ICFP. She leads research in the Gallinette team at INRIA, which focuses on the intersection of proof assistants, programming languages, and formal mathematics. Her work has helped establish formal verification as a practical tool for mathematical research, moving beyond theoretical foundations to real applications in computational mathematics.
Abbas Milani is a tenured Professor of Mechanical Engineering at the University of British Columbia's Okanagan campus, where he holds the Tier 1 Principal's Research Chair in Sustainable & Smart Manufacturing and serves as Director of the Materials and Manufacturing Research Institute (MMRI). He also serves as Technical Director of the Composites Research Network (CRN), Lead of the Canadian-International Biocomposites Research Network, and leads multiple major initiatives including the UBC-Pacific Economic Development Canada-Advancing Circular Economy (ACE) program and the UBC-NRC IRAP National Circular Economy CtO Program. Dr. Milani's primary research focuses on advanced modeling, simulation, and multi-criteria design optimization of composite and biocomposite materials, structures, and manufacturing processes. His expertise spans Textile Composites/Biocomposites, Materials Constitutive Relations, Finite Element Modeling, Robust Inverse Methods, Material Selection for End-of-Life Design Strategies, Multiple Criteria Decision Making, and Industry 5.0 applications. His interdisciplinary research bridges mechanical engineering, sustainable materials science, and smart manufacturing technologies. Analysis of his recent publication record reveals a strong emphasis on sustainable materials development, with particular focus on biocomposites, life cycle assessment methodologies, and optimization of manufacturing processes. His work integrates computational modeling with experimental validation across diverse application areas including medical devices, sustainable packaging, and circular economy strategies. The publications demonstrate increasing integration of artificial intelligence and machine learning approaches with traditional engineering methods. 2015 UBC Okanagan Researcher of the Year Award Killam Faculty Research Award (2016) Inducted into Royal Society of Canada - College of New Scholars (2020) Gold Medal Service Contribution Award by Academics World Reviewer Contribution Award by ASM International Multiple teaching excellence awards from UBC Dr. Milani has successfully mentored over 100 students and postdoctoral fellows who have secured positions in both industry and academia. His research program has been supported by more than $15 million in funding from government and industrial organizations. He leads the NSERC CREATE in Immersive Technologies (CITech) program and co-leads the Advanced Materials and Fabrication Core Competency within the Survive and Thrive Applied Research (STAR) program, demonstrating his commitment to training the next generation of engineers and advancing applied research.
Professor Paweł Chmura is a Full Professor at Wrocław University of Health and Sport Sciences, specializing in Sports Sciences with a focus on football performance analysis. He serves in the Department of Individual and Team Sports, where he conducts research on exercise physiology, training load monitoring, and physical activity analysis in soccer players. With over 130 publications, Professor Chmura is a recognized expert in sports science and also holds a UEFA A coaching license. Professor Chmura's research interests center on exercise physiology, particularly in the context of team sports. His work extensively examines repeated maximum effort capabilities, physical activity analysis in soccer players, and monitoring training loads. He has developed innovative concepts such as the Psychomotor Fatigue Threshold and investigates how environmental factors like temperature and air quality affect athletic performance. His research bridges the gap between theoretical sports science and practical coaching applications, making significant contributions to football performance optimization. Professor Chmura's extensive publication record demonstrates a consistent focus on soccer performance analysis, with recent work expanding into multidisciplinary approaches including physiological, psychological, and tactical aspects of the game. His research shows increasing sophistication in methodology, incorporating advanced monitoring technologies and comprehensive analysis frameworks that consider multiple performance indicators simultaneously. This evolution reflects broader trends in sports science toward integrated, holistic approaches to athlete performance. Professor Chmura actively supervises the Motosoccer Student Research Club and invites master's and doctoral students to collaborate on research projects related to football, exercise physiology, game analysis, and motor preparation. His mentorship extends beyond formal academic supervision to practical coaching guidance, leveraging his UEFA A coaching certification to provide students with both theoretical knowledge and practical field experience. As a UEFA A-licensed football coach and tennis instructor, Professor Chmura maintains strong connections between academic research and practical sports applications. He leads the Motosoccer Student Research Club, which provides hands-on research opportunities for students interested in sports science. His dual expertise in academic research and practical coaching creates a unique environment for applied sports science research that directly impacts coaching methodologies and athlete development.
