Romain Fleury is an Associate Professor at the Laboratory of Wave Engineering (LWE) , part of the École Polytechnique Fédérale de Lausanne (EPFL) School of Engineering and Institute of Electrical and Micro Engineering (IEL) . He earned a Ph.D. in Electrical and Computer Engineering from the University of Texas at Austin in 2015 under Andrea Alù, followed by a Marie-Curie Postdoctoral Fellowship at ESPCI Paris-Tech and CNRS Langevin Institute (2016). His research explores wave physics and engineering , focusing on topological insulators , nonreciprocal wave propagation , and time-modulated metamaterials . He has co-authored over 70 peer-reviewed articles in journals like Science , Nature , and Physical Review series, with recent work on topological acoustics , active metamaterials , and wave-based analog computing . Dr. Fleury received the Eccellenza Grant (2021) from the Swiss National Science Foundation and an ERC Starting Grant (2022) . He co-founded Minwave , a startup selling miniaturized microwave devices patented by his lab, which has garnered awards such as ESA-BIC CH , FIT , and Venture Kick . He has served as Technical Program Committee Chair for Eucap 2019 and on the Editorial Board of the New Journal of Physics . Recognized for teaching excellence with the STI Polysphere Award (2019) and IEL Best Teacher Award , he teaches courses including Electromagnetics , Antennas , and Advanced Photonics . His work bridges fundamental wave physics with applied technologies , emphasizing topological effects , nonlinear systems , and metamaterials . Collaborations span institutions such as ESPCI Paris , University of Texas at Austin , and University of Vienna , with applications in acoustic imaging , 5G antennas , and optical signal processing . His recent publications highlight ultrafast anti-lasing , reconfigurable metasurfaces , and disorder-assisted photonic crystals , reflecting a career dedicated to advancing wave engineering through topological and nonreciprocal designs .
Michael Smith is the McCosh Professor of Philosophy at Princeton University. He holds a DPhil from Oxford University (1989) and has been a faculty member since 2004, previously at the Australian National University. His research focuses on ethics, moral psychology, philosophy of mind, political philosophy, and philosophy of law. Smith’s work integrates constitutivist theories of practical reason with analyses of moral agency. He has contributed to debates on moral rationalism, the nature of reasons for action, and the relationship between rationality and normativity. Education: MA, Monash University (1980); BPhil (1983), DPhil (1989), University of Oxford Smith’s scholarship emphasizes the interplay between ethical theory and psychological explanations of agency. Recent publications explore topics like carbon capture technologies, cultural clashes in moral reasoning, and probabilistic forecasting in oceanography. His philosophical contributions address foundational questions in meta-ethics, including the ‘moral problem’ and the implications of constitutivism for normative frameworks. He advises on interdisciplinary projects at the intersection of philosophy and emerging technologies. Notable research trends include applying philosophical analysis to environmental ethics and developing frameworks for resolving moral dilemmas through rational agency models. His work often bridges analytic philosophy with empirical inquiries in psychology and social science.
Liangming Pan is an Assistant Professor at the University of Arizona's College of Information Science. His research focuses on building trustworthy large language models (LLMs) with an emphasis on logical reasoning, truthfulness, and safety. He holds a PhD in Computer Science from the National University of Singapore (2022), a Master's from Tsinghua University, and a Bachelor's from Beihang University. Education : PhD in Computer Science, National University of Singapore (2022) Master of Engineering in Computer Science, Tsinghua University (2017) Bachelor of Engineering in Computer Science, Beihang University (2014) Research Interests : Dr. Pan's work centers on enhancing LLMs' reliability through: Logical reasoning mechanisms to ensure faithful deductions Truthfulness verification to combat misinformation Safety protocols to mitigate societal harm Key Contributions : Developed TART, an open-source framework for explainable table-based reasoning Created benchmarks like SCITAB and FactCheck-Bench for evaluating LLMs Advanced techniques for knowledge editing and causal reasoning Awards : Best Paper Runner-Up at NeurIPS Table Representation Workshop (2024) Area Chair Award for Question Answering (IJCNLP-AACL 2023) Service & Outreach : He serves as an Area Chair for EMNLP (2024), COLING (2025), and ACL (2024). He has delivered invited talks at Tsinghua University, Peking University, and other institutions.
Jiang Hu is a Professor in the Department of Electrical and Computer Engineering at Texas A&M University, holding the Eric D. Rubin '06 Endowed Professorship. He also serves as Co-Director of Graduate Programs and is affiliated with the Computer Science & Engineering department. His research focuses on VLSI design automation, machine learning applications, and hardware security. He has held roles as editor for IEEE Transactions on CAD and ACM Transactions on Design Automation, and chaired the 2012 ACM International Symposium on Physical Design. Education: B.S. in Optical Engineering (Zhejiang University, 1990), M.S. in Physics (1997), and Ph.D. in Electrical Engineering (University of Minnesota, 2001). He worked at IBM Microelectronics before joining Texas A&M in 2002. Research interests include energy-efficient VLSI circuits, on-chip communication fabrics, analog layout automation, and AI-driven EDA. Recent work emphasizes machine learning for design closure, privacy-preserving frameworks, and systolic array-based architectures. Awards: IEEE Fellow (2016) Humboldt Research Fellowship (2012) Multiple best paper awards at DAC, ICCAD, and ASPDAC Advising and grants: Leads initiatives like the SLICE project, NSF workshops on ML-EDA infrastructure, and serves as Editor-in-Chief of ACM TODAES since 2024. His work bridges academic research and industry applications in EDA and semiconductor design. Labs/Teams: Active contributor to open-source tools like ALIGN for analog layout generation and collaborations on machine learning for EDA commons.
Paul Taele is an Instructional Assistant Professor and Deputy Lab Director in the Sketch Recognition Lab at Texas A&M University's Department of Computer Science & Engineering. He holds a Ph.D. (2019), M.S. (2010), and dual B.S. degrees in Computer Science and Mathematics from the University of Texas at Austin (2006). His research focuses on sketch recognition, haptics, and intelligent interfaces for education and accessibility, with notable work in mid-air gesture recognition, educational sketching tools, and assistive technologies for disabilities. He has contributed to projects like Kanji Workbook , Hashigo , and HaptiMoto , and has published over 50 peer-reviewed articles across venues like CHI, IUI, and AAAI. Taele has received awards including the NSF Student Travel Grant (2014) and Ford Foundation Honorable Mention (2015). He teaches courses in capstone design, programming, and sketch recognition, and mentors students across all academic levels through strict eligibility criteria for research collaborations. Education : Ph.D. Computer Science, Texas A&M University (2019) M.S. Computer Science, Texas A&M University (2010) B.S. Computer Science & Mathematics, University of Texas at Austin (2006) Concentration in Mandarin Chinese, National Chengchi University (2007) Research Interests : Taele's work bridges HCI and AI to create accessible educational interfaces. His projects emphasize: Sketch Recognition : Developing algorithms for mid-air gestures, children's developmental assessments, and language learning Accessibility : Haptic systems for visually impaired learners and algebra education Educational Tech : Intelligent tutoring systems for music, math, and East Asian languages Awards & Grants : EAAI-20 Travel Grant (2020) Ford Foundation Dissertation Honorable Mention (2015) NSF East Asia-Pacific Summer Institutes (2013, 2012) Royce E. Wisenbaker Fellowship (2009) Lab & Teams : Director of the Sketch Recognition Lab (SRL) and collaborator with global institutions like Singapore Management University and National Taiwan University. Active in organizing workshops like SketchRec at IUI conferences.
Dr. Jing Li is an Associate Professor and Eduardo D. Glandt Faculty Fellow at the University of Pennsylvania , holding dual appointments in the Electrical and Systems Engineering and Computer and Information Science departments. As co-director of the CyberSavvy nationwide security research center and director of the Penn Computational Intelligence Lab (PennCIL) , she pioneers innovations in non-von Neumann computing paradigms. Her research spans post-CMOS technologies, in-memory computing, and hardware-software co-design for security and AI applications. PhD in Computer Engineering, Purdue University (2009) BSc in Electrical Engineering, Shanghai Jiaotong University (2004) Research Focus: Dr. Li's work addresses fundamental challenges in computer systems across the stack. Key areas include: In-Memory Computing: Liquid Silicon architecture combining RRAM with silicon CMOS through monolithic 3D integration Security Engineering: Transforming computer security from "Art" to formal "Engineering" discipline within CyberSavvy Virtualization: Cloud FPGA abstraction layers decoupling compilation from runtime resource management Graph Analytics: Degree-aware optimization techniques for massive-scale graph processing Deep Learning Systems: Roofline model extensions for FPGA-based CNN acceleration Scientific Impact: Awarded DARPA Young Faculty Award , NSF CAREER Award , and IBM CEO Milestone Award , her team has achieved world records in energy-efficient computing (ENIAD supercomputer). With 46 U.S. patents and over 80 publications, she leads ecosystem development for emerging computing architectures through initiatives like the open-source MEG simulation platform . Community Leadership: Dr. Li serves on program committees for flagship conferences ( ISCA , FPGA Symposium ), chairs the International Memory Workshop , and contributes to the MLsys conference's inaugural committee. She actively mentors through multiple PhD openings and industry collaborations.
Dr Anandadeep Mandal is an Associate Professor in Finance and the Scotcoin Distinguished Chair of Digital Finance at the University of Birmingham , within the Birmingham Business School and the Department of Finance . He is the founding director of the MSc Financial Technology programme and the Programme Director for the MBA (Distance Learning), demonstrating significant leadership in academic program development. Education: PhD in Probability Distribution Fitting, Cranfield University (2016) MRes in Management Science, Cranfield University (2012) MSc in Finance and Investments, Durham University (2008) Bachelor’s in Electronics Engineering Research Interests: Dr Mandal’s interdisciplinary research lies at the intersection of mathematical modelling, artificial intelligence, finance, and digital innovation . His work focuses on AI-enabled investment strategies , blockchain for financial transparency , ESG performance measurement , and the development of the Sustainable Efficiency Index (SEI) . He also pioneers AI applications in digital education , including a patent-pending platform for automated grading of multi-modal student submissions using ensemble AI methods. Publication Trends: His recent scholarly output spans high-impact journals and conferences, reflecting a strong focus on digital finance , climate and social media analytics , cryptocurrency regulation , and AI in financial forecasting . His work combines advanced data science techniques with real-world policy and financial applications, particularly in sustainability and public health. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: Dr Mandal has secured over £2 million in research funding from sources including UKRI, UoB QR Funding, and industry partners. While specific students are not listed, his role as programme director and research leader suggests active mentorship. His research has direct policy impact through collaborations with the NHS Trusts , NIHR , and the UK Government . Labs, Teams, and Impact: Dr Mandal leads a research agenda that bridges academia and public policy. His work extends beyond the university through public engagement at science festivals, outreach for young learners, and expert contributions to UK Parliamentary consultations on AI, sustainability, and financial innovation. He is a key figure in advancing digital finance education and research at the University of Birmingham.
Shuran Song is an Assistant Professor of Electrical Engineering at Stanford University, with a courtesy appointment in Computer Science. Previously, she was faculty at Columbia University. She holds a Ph.D. in Computer Science from Princeton University and a BEng from HKUST. Her research focuses on the intersection of computer vision and robotics, particularly in embodied AI, robot manipulation, and sensorimotor learning. Song's work emphasizes learning from physical interactions to enable robots to perform complex tasks autonomously. She leads the Robotics and Embodied AI Lab (REAL@Stanford) and has received prestigious awards, including the NSF Career Award, Sloan Fellowship, and Microsoft Faculty Fellowship. Education: Ph.D., Computer Science, Princeton University; BEng, HKUST Affiliations: Stanford School of Engineering, Department of Electrical Engineering Research interests include deformable object manipulation, visuomotor policy learning, and generalizable robot skills. Her lab develops algorithms for robots to learn through interaction, with applications in household assistance (e.g., TidyBot) and industrial automation. Notable contributions include the TossingBot and Diffusion Policy frameworks. Publications span robotics, computer vision, and AI conferences (RSS, ICRA, CVPR), focusing on policy learning, deformable object handling, and embodied intelligence. Awards highlight her impact in advancing robot learning and perception. Advises doctoral and master's students in robotics and AI, and collaborates on grants from NSF, DoD, and industry partners. Teaches courses on robot perception and embodied AI at Stanford.
Viswanath Nagarajan is an Associate Professor of Industrial & Operations Engineering and Computer Science Engineering (courtesy) at the University of Michigan. His research focuses on combinatorial optimization, approximation algorithms, and stochastic models for routing, scheduling, and location problems. He previously served as an Assistant Professor at the University of Michigan (2014–2020) and a Research Staff Member at IBM T.J. Watson Research Center (2009–2014). He holds a Ph.D. in Algorithms, Combinatorics, and Optimization from Carnegie Mellon University (2004–2009) and a B.Tech. in Computer Science from IIT Bombay (1999–2003). His research explores uncertainty management in optimization, including stochastic models and approximation algorithms for decision-making under uncertainty. He has contributed to adaptive algorithms, submodular optimization, and applications in logistics, network design, and scheduling. Education: Ph.D., Algorithms, Combinatorics, and Optimization (Carnegie Mellon University, 2009) B.Tech., Computer Science and Engineering (IIT Bombay, 2003) Prof. Nagarajan has organized major conferences like IPCO 2019 and served on editorial boards for journals including Operations Research , ACM Computing Surveys , and ACM Transactions on Algorithms . His service includes program committees for SODA, APPROX, and IPCO. He advises Ph.D. students focusing on optimization theory and applications, with advisees securing positions at Yahoo! Research, the University of Chicago, Ford Motor Company, and Georgia Tech.
Edward H. Kaplan is the William N. and Marie A. Beach Professor of Management Sciences at the Yale School of Management, Professor of Public Health at the Yale School of Medicine, and Professor of Engineering at the Yale School of Engineering and Applied Sciences. He holds secondary appointments in Chemical and Environmental Engineering, Health Policy & Management, the Institution for Social and Policy Studies, and Statistics. Education: PhD in Urban Studies, Massachusetts Institute of Technology (1984) SM in Mathematics, Massachusetts Institute of Technology (1982) SM in Operations Research and City Planning, Massachusetts Institute of Technology (1979) BA in Urban/Economic Geography, McGill University (1977) Kaplan is an expert in operations research, mathematical modeling, and statistics, focusing on public policy and management. His research spans counterterrorism, HIV prevention, bioterrorism, and public health modeling. He has developed models for suicide bomber detection, smallpox response logistics, needle exchange program effectiveness, and wastewater-based disease surveillance. His work has been recognized with numerous awards, including the Koopman Prize (2003, 2005), INFORMS President’s Award (2002), Charles C. Shepard Science Award (2009), and INFORMS Fellow (2005). He has also served as President of INFORMS (2016) and co-directs the Daniel Rose Technion-Yale Initiative in Homeland Security.
Dr. Alain Bonneville is a Lab Fellow and Geophysicist at Pacific Northwest National Laboratory (PNNL) and holds a Courtesy Professor appointment at Oregon State University's College of Earth, Ocean, and Atmospheric Sciences. With extensive experience in geological storage of CO2, geothermal energy, and geophysical monitoring techniques, Dr. Bonneville leads diverse research projects that bridge fundamental science and practical applications for energy and environmental challenges. Dr. Bonneville's educational background includes: PhD in Geophysics from the University of Montpellier, France MS in Petroleum Geophysics from IFP-School, Paris, France BS in Geology from the University of Lyon, France Dr. Bonneville's research spans several critical areas in Earth sciences and energy systems. His work on geothermal energy focuses on super-hot enhanced geothermal systems (EGS), site characterization, monitoring, and stimulation fluids. In geological CO2 storage, he investigates project management, site characterization, numerical modeling, and monitoring methods using potential fields and remote sensing. His expertise in geophysical methods includes heat flow measurements, gravity surveys, muon tomography development for borehole deployment, and remote sensing applications. Additional research areas encompass marine heat flow instrumentation development, thermal monitoring of active volcanoes, and intraplate volcanism studies in the Indian and Pacific Oceans. Dr. Bonneville has received significant recognition for his contributions to science, including: Membership in the Washington State Academy of Sciences Lab Fellow position at Pacific Northwest National Laboratory Executive Committee membership on the U.S. National Risk Assessment Partnership Scientific Committee membership at IFP-Energies Nouvelles, France He also holds two U.S. patents related to electrophilic acid gas-reactive fluids for enhanced fracturing and recovery of energy producing materials. Throughout his career, Dr. Bonneville has led significant research initiatives, including the PNNL Carbon Sequestration Initiative (2009-2013) and the European Marie Curie Research Training Network on Greenhouse Gas Removal (GRASP), which involved 14 academic and industrial institutions across 7 countries and supported 35 PhD students and post-docs. His work on the FutureGen 2.0 project demonstrates his leadership in large-scale carbon storage site characterization and monitoring program design. Dr. Bonneville maintains active collaborations with research teams at PNNL's Environmental Molecular Sciences Laboratory and works closely with Oregon State University's geoscience researchers. His laboratory work focuses on developing novel instrumentation for geophysical monitoring, particularly in the areas of muon tomography for subsurface characterization and thermal monitoring systems for geothermal and carbon storage applications.
Dr. Matthew Brookhouse is a Senior Lecturer at the Fenner School of Environment & Society, part of the Australian National University's Institute for Climate, Energy & Disaster Solutions. With a PhD in Dendroclimatology from ANU, he specializes in using forest structural complexity and tree-ring analysis to understand climate interactions and ecological responses in Australian subalpine environments. Research Focus: Sub-alpine ecology, Dendrochronology, CO2 responsiveness in eucalypt species Teaching: First-year research methods with emphasis on statistical application, advanced modeling and field botany Projects: Leading collaborative snow-gum dieback research and dendrochronological monitoring initiatives His publications span 2006-2025 with recent emphasis on machine learning applications for forest monitoring, tropical tree-ring chronologies for climate change, and climate sensitivity in Australian alpine ecosystems. Key collaborations include institutions like Australian Nuclear Science and Technology Organisation and University of Canberra researchers. Current projects focus on snow-gum woodland dieback mechanisms, high-resolution dendrometric monitoring, and integrating dendrochronology with environmental policy frameworks. He maintains active supervision of research students and contributes to both undergraduate and postgraduate curriculum development.
Thatchaphol Saranurak is an Assistant Professor at the University of Michigan , specifically in the Computer Science and Engineering Division . Prior to this, he earned his PhD in Computer Science from KTH Royal Institute of Technology in 2018 under Danupon Nanongkai , followed by a postdoctoral research assistant professorship at Toyota Technological Institute at Chicago (2018-2020). Research Focus : His work bridges fundamental problems in graph theory, including Dynamic graph algorithms for max-flow and min-cut Expander graph decompositions and their applications Robust algorithms against adaptive adversaries Continuous optimization for combinatorial problems Scientific Contributions : He has made breakthroughs in deterministic graph algorithms, notably improving vertex connectivity bounds, developing near-linear time Gomory-Hu trees, and advancing dynamic matching algorithms. His research has been recognized by Sloan Research Fellowship NSF CAREER Award Presburger Award 2023 Teaching : He teaches courses like Expander and Graph Algorithms and Introduction to Algorithms (Winter 23, Winter 25). His lecture videos and notes are publicly available. Collaborations : He works with leading researchers including Sayan Bhattacharya , Joakim Blikstad , and Jason Li , with affiliations to institutions like TTIC , KTH , and SODA conferences.
Pedro M. Reis serves as Full Professor and Director of the Institute of Mechanical Engineering (IGM) at École Polytechnique Fédérale de Lausanne (EPFL), leading the Flexible Structures Laboratory (FLEXLAB) within the School of Engineering (STI). He holds additional appointments as Full Professor in STI-SGM Teaching, Member of the STI Academic Evaluation Committee, and PhD Program Committee Member for Mechanics. His academic journey includes: B.Sc. in Physics, University of Manchester (1999) Certificate of Advanced Studies in Mathematics, University of Cambridge (2000) Ph.D. in Physics, University of Manchester (2004) Postdoctoral research at City College of New York (2004-2005) and CNRS/ESPCI Paris (2005-2007) Faculty positions at MIT (2007-2013) as Esther and Harold E. Edgerton Assistant Professor and Gilbert W. Winslow Associate Professor Reis's research pioneers the exploitation of mechanical instabilities in flexible structures, spanning experimental mechanics, fluid-structure interactions, and buckling phenomena. His work bridges theoretical modeling with physical experimentation to develop novel functional materials and devices, emphasizing practical applications in engineering design and soft matter systems. His accolades include: 2013 Brilliant 10 recognition by Popular Science 2014 NSF CAREER Award 2016 Thomas J.R. Hughes Young Investigator Award (ASME) 2016 GSOFT Early Career Award (APS) APS Fellowship and 2021 Presidency of the Society of Engineering Science (SES) Reis actively mentors nine PhD students across current and graduated cohorts while directing FLEXLAB's experimental research on structural instabilities. His leadership extends to institutional roles including Director of IGM and committee memberships shaping EPFL's academic framework and doctoral programs in mechanics.
Dr. Stephanie Spahr is a Research Group Leader at the Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB) in Berlin, Germany, where she leads the Organic Contaminants research group within the Department of Ecohydrology and Biogeochemistry. Previously, she served as a Junior Research Group Leader at the University of Tübingen's Center for Applied Geoscience (2019-2021) and as a Postdoctoral Researcher at Stanford University's Department of Civil and Environmental Engineering (2016-2019). Dr. Spahr earned her PhD in Environmental Chemistry from the Swiss Federal Institute of Technology Lausanne (EPFL) and the Swiss Federal Institute of Aquatic Science and Technology (Eawag) in 2016. Her doctoral research focused on the formation of N-nitrosodimethylamine during water disinfection with chloramine. She completed her MSc in Geoecology at the University of Tübingen in 2012, with thesis work on carbon and nitrogen isotope analysis of benzotriazoles conducted at Eawag, and her BSc in Geoecology/Ecosystem Management at the same institution in 2010. Dr. Spahr's research focuses on trace organic contaminants in aquatic systems, with particular expertise in transformation processes of contaminants in natural and engineered systems, advanced oxidation processes for water treatment, urban blue-green infrastructure, and compound-specific isotope analysis. Her work bridges environmental chemistry, engineering, and ecology to address water quality challenges in urban and natural water systems. She employs advanced analytical techniques to track contaminant sources and transformation pathways, with a strong emphasis on practical applications for water treatment and environmental protection. Her recent publications demonstrate a strong focus on biochar-based water treatment technologies, particularly for stormwater management. She investigates how biochar amendments can remove trace organic contaminants from urban runoff, with recent work examining persulfate activation mechanisms, the role of chloride in reactive species formation, and the performance of engineered media filters under dynamic conditions. Her research also extends to understanding contaminant transport in rivers, the ecological impacts of pollutants, and developing analytical methods for environmental monitoring. The interdisciplinary nature of her work connects chemical processes with ecological outcomes. Outstanding Review Paper Award 2023 in Environmental Science: Water Research & Technology Selected for the Falling Walls Female Science Talents Intensive Track 2023 Selected mentee in the Leibniz Mentoring Programme 2022-2023 Best poster award (1st prize) at the Wasser 2022 of the Water Chemistry Society Selected fellow in the Postdoc Academy for Transformational Leadership 2020-2022 (Robert Bosch Stiftung) Selected fellow in the Athene Program for early female career researchers at the University of Tübingen, 2020-2021 As a Research Group Leader, Dr. Spahr supervises multiple research projects including 'POllution in UrbaN ponds, eco-evolutionary Dynamics, and Ecosystem Resilience (POUNDER)', 'Dynamic hyporheic zone', 'NYMPHE', and the 'Incident-related special investigation programme for the environmental disaster in the Oder River'. She serves on the Executive Board of the German Water Chemistry Society and heads its Expert Committee on 'Oxidative Processes'. Her collaborative work spans numerous institutions across Germany and internationally, addressing critical water quality challenges through interdisciplinary approaches. Dr. Spahr leads the Organic Contaminants research group at IGB Berlin, which focuses on understanding the fate and treatment of organic pollutants in water systems. Her team employs advanced analytical techniques including compound-specific isotope analysis to track contaminant sources and transformation pathways. The group collaborates extensively with other departments at IGB and with international partners on projects addressing urban water challenges and ecological impacts of pollution. Current research emphasizes innovative water treatment technologies, particularly biochar-based systems for stormwater management, and investigating the complex interactions between contaminants, aquatic ecosystems, and human activities.
