Catherine H. Hausman is an Associate Professor at the Gerald R. Ford School of Public Policy, University of Michigan, and a Research Associate at the National Bureau of Economic Research (NBER). Her work bridges environmental economics, energy policy, and climate change mitigation. BA in Economics from University of Minnesota PhD in Agricultural and Resource Economics from University of California, Berkeley (2013) Her research explores: Electricity transmission barriers and corporate profit alignment Methane emissions and carbon intensity in fossil fuel production Climate change impacts on grid reliability and pricing Pollution inequality and nuclear power economics Recent publications examine decarbonization strategies, ancillary service market spillovers, and methane leak quantification. She has received a Fulbright grant for pre-graduate work in Peru and contributes policy insights through the Hamilton Project and NBER working papers.
Naresh R. Shanbhag is the Jack Kilby Professor in the Department of Electrical and Computer Engineering and the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. He serves as Director of the Systems on Nanoscale Information fabriCs (SONIC) Center and held the D.J. Gandhi Distinguished Visiting Professorship at IIT Mumbai from 2015-2020. Previously, he was a visiting faculty member at National Taiwan University (2007) and Stanford University (2014). Dr. Shanbhag received his doctorate from the University of Minnesota (1993) in Electrical Engineering. From 1993 to 1995, he worked at AT&T Bell Laboratories as the lead chip architect for AT&T's 51.84 Mb/s transceiver chips over twisted-pair wiring for Asynchronous Transfer Mode (ATM)-LAN and very high-speed digital subscriber line (VDSL) chip-sets. His research focuses on the design of energy-efficient machine learning, communications, and signal processing systems on resource-constrained embedded platforms. He explores fundamental trade-offs between energy efficiency, latency and accuracy of decision-making systems implemented in nanoscale technologies, with applications to computer vision, biomedicine, automatic target recognition, and imaging. His work spans four primary focus areas: Resource-efficient Machine Learning for the Edge, In-memory Computing (IMC), Energy-efficient High Data Rate Communications, and Shannon-inspired Statistical Error Compensation (SEC). Analysis of his recent publications reveals a strong emphasis on in-memory computing architectures (SRAM, MRAM, RRAM) for machine learning acceleration. His work consistently addresses energy-accuracy trade-offs, with increasing attention to security aspects of hardware implementations and applications to MIMO signal processing and edge AI systems. His research demonstrates a progression from theoretical foundations to practical silicon implementations. 2024 Semiconductor Research Corporation Innovation Award 2018 Semiconductor Industry Association/Semiconductor Research Corporation University Researcher Award 2018 IEEE International Symposium on Circuits and Systems Best Paper Award 2006 IEEE Fellow 1996 National Science Foundation CAREER Award Professor Shanbhag has mentored over 50 graduate students who now work at leading technology companies including Qualcomm, Amazon, Nvidia, Intel, and Apple. His research has been generously supported by the National Science Foundation, DARPA, AFRL, Semiconductor Research Corporation, Texas Instruments, Sandia National Laboratories, and industry partners including IBM, GlobalFoundries, and Intel Corporation. He led the Alternative Computational Models research theme (2006-2012) and was the founding Director of the SONIC Center (2013-2017), a 5-year multi-university center funded by DARPA and SRC. Currently, he leads research themes in the SRC and DARPA funded JUMP 2.0 Program's Center for Co-Design of Cognitive Systems and the Center for Ubiquitous Connectivity, and in the NSF IUCRC Center for Advanced Semiconductor Chips with Accelerated Performance (ASAP). As Director of the Systems on Nanoscale Information fabriCs (SONIC) Center, Professor Shanbhag leads a multidisciplinary team exploring novel computing paradigms for the nanoscale era. His group has benchmarked an extensive collection of in-memory computing and digital accelerator IC designs, maintaining a publicly available IMC benchmarking repository of metrics extracted from published IC prototypes. His research philosophy integrates concepts from information theory, statistical signal processing, detection and estimation, VLSI architectures, and digital and analog integrated circuits to develop energy-efficient systems from algorithms to silicon implementations.
Baris Fidan is a Professor in Mechanical & Mechatronics Engineering at the University of Waterloo, with cross appointments in System Design Engineering and Electrical & Computer Engineering. He is a senior member of IEEE and AIAA. His research focuses on cooperative/adaptive control, autonomous systems, multi-agent networks, and vehicular control applications. He leads the Cooperative & Adaptive Mechatronic Systems (CAMS) Lab, which develops control strategies for autonomous vehicles, robotic systems, and intelligent transportation. Education: PhD in Electrical Engineering, University of Southern California (2003) Masters in Electrical & Electronic Engineering, Bilkent University (1998) Bachelor's in Electrical & Electronic Engineering & Mathematics, Middle East Technical University (1996) Research Interests: His work spans adaptive control theory, sensor networks, multi-agent coordination, autonomous vehicle networks, and biomedical systems control. He emphasizes practical applications in intelligent transportation, robotic navigation, and distributed system optimization. Grants & Projects: He has led major grants including NSERC Discovery Programs on cooperative mechatronic systems and 3D autonomous vehicle coordination. Industrial projects include autonomous driving strategies, vehicle control optimization, and high-precision gear manufacturing technologies. Labs/Teams: Directs the CAMS Lab, which collaborates on projects involving distributed motion planning, sensor localization, and autonomous vehicle networks. Current projects address challenges in urban autonomous driving, cooperative robotic systems, and resilient sensor networks.
Prasanna (Sonny) Tambe is a Professor at the Wharton School of the University of Pennsylvania, specializing in the economics of technology and labor markets. His research explores AI’s impact on workforce dynamics, HR algorithms, and the gender wage gap in tech industries. Education: Ph.D. in Managerial Science and Applied Economics (Wharton, UPenn); S.B. and M.Eng. in Electrical Engineering and Computer Science (MIT). His work leverages internet-scale data from job platforms and patent databases to analyze trends in skill acquisition, remote work diversity, and algorithmic bias in hiring. Recent studies examine AI’s role in HR decision-making, the economics of emerging technologies, and labor market responses to IT innovation. Scientific Awards: Best Undergraduate Professors (Poets & Quants, 2020) Best Paper Awards (Management Science, Information Systems Research) ISS Sandra A. Slaughter Early Career Award (2016) Tambe co-directs Wharton Human-AI Research, focusing on ethical AI integration in organizations. His teaching includes award-winning courses on AI’s societal implications and data-driven business strategies.
Robert P. Bartlett is the W. A. Franke Professor of Law and Business at Stanford Law School and a courtesy Professor of Finance at the Stanford Graduate School of Business. He serves as Co-Director of the Arthur and Toni Rembe Rock Center for Corporate Governance. Previously, he held roles at UC Berkeley School of Law and the University of Georgia School of Law, and practiced corporate law at Gunderson Dettmer. He earned his JD (2000) and BA (1996) from Harvard University. His research focuses on law and finance, particularly venture capital, market structure, corporate governance, and capital market regulation. Key areas include fractional shares' impact, odd-lot trading dynamics, and ESG integration in executive compensation. Recent articles address hidden liquidity, venture capital contract standardization, and fintech-driven consumer lending discrimination. Bartlett’s work bridges legal and financial disciplines, influencing policy debates on market transparency, regulatory frameworks, and corporate accountability. He has contributed to prominent journals like the Journal of Financial Economics and Review of Financial Studies , and authored book chapters on venture capital valuation. His affiliations include the Stanford Institute for Economic Policy Research and leadership roles in academic centers fostering corporate governance research.
Professor Daniel Rueckert is a leading academic in Artificial Intelligence and Medical Imaging, holding dual positions at Imperial College London (as Professor of Visual Information Processing) and Technical University of Munich (Alexander von Humboldt Professor for AI in Medicine and Healthcare). He obtained his MSc from Technical University Berlin (1993) and PhD from Imperial College London (1997), followed by postdoctoral work at King’s College London. At Imperial, he led the Department of Computing (2016–2020) and founded the Biomedical Image Analysis group. His research focuses on AI-driven medical image analysis, including algorithms for image reconstruction, registration, and clinical decision support. His research interests span AI applications in healthcare, machine learning for medical imaging, and computational methods for clinical diagnostics. Notable contributions include over 500 publications and 60+ PhD graduates, with key works in federated learning, cardiac motion analysis, and biomarker development. Awards include the Leibniz Prize (2025), Royal Academy of Engineering Fellowship (2015), and multiple ERC grants. He leads the BioMedIA research group and is an editorial board member of Medical Image Analysis . Recent publications highlight advancements in AI-driven medical imaging, such as secure federated learning frameworks and deep learning models for disease prediction. His work bridges academic and industrial sectors through initiatives like IXICO, an Imperial spin-out. Current affiliations include roles at both Imperial and TUM, emphasizing interdisciplinary collaboration in healthcare technology. Advising and grants: Supervised over 60 PhD students and 40 post-docs. Secured grants including ERC Synergy (2013) and ERC Advanced (2020). Active in labs focused on biomedical image computing and AI in healthcare systems. Collaborative efforts include the BioMedIA group and TUM’s AI initiatives. Labs/teams: Leads the Biomedical Image Analysis group at Imperial and the TUM AI in Medicine team. Collaborates extensively on projects like cardiac imaging analysis and federated learning for healthcare.
Roberto Manduchi is a Professor of Computer Science and Engineering at the University of California, Santa Cruz, within the Baskin School of Engineering. His primary affiliation is with the Computer Science and Engineering department where he leads research in assistive technology for visual impairments. He holds a Dottorato di ricerca in Electrical Engineering from the University of Padova, Italy, and previously worked at Apple and NASA JPL before joining UCSC in 2001. His research focuses on mobile computer vision, inertial sensors, and location-aware systems to enhance spatial awareness and information access for blind and low-vision individuals. Key research areas include indoor navigation systems, screen magnification for low-vision readers, obstacle detection using augmented reality, and text accessibility assessment through specialized OCR pipelines. His work bridges computer vision, human-computer interaction, and accessibility design. Analysis of his recent publications (2022-2025) reveals strong emphasis on inertial-based indoor navigation (e.g., PALMS localization system, backtracking algorithms), screen magnification usability studies, and novel approaches to scene text access for blind users. His research consistently targets practical applications for visual impairment, with significant contributions to pedestrian dead reckoning, magnetic signature localization, and gaze-contingent interfaces. Manduchi serves on the scientific advisory board of Aira and is a board member of the Vista Center for the Blind and Visually Impaired. He leads the UCSC Computer Vision Lab where his team develops accessible computing solutions. His work includes both theoretical contributions to computer vision and tangible assistive applications, with recent projects focusing on smartphone-based inertial odometry, multi-scale tactile maps, and real-time obstacle cueing systems.
Luca Peretti is an Associate Professor in Electric Machines and Drives at KTH Royal Institute of Technology, affiliated with the School of Electrical Engineering and Computer Science and the Department of Electrical Engineering, Division of Electric Power and Energy Systems. He works as a researcher in the EMD (Electric Machines and Drives) group and serves as Partner Director for KTH's strategic partnership with ABB. Education: M.Sc. in Electronic Engineering (2005) from University of Udine, Ph.D. from University of Padova (2008) Professional Experience: Postdoc at University of Padova (2009-2010), Principal Scientist at ABB Corporate Research (2010-2018), Associate Professor at KTH (2018-present) His research focuses on: Automatic parameter estimation in electric machines Multiphase drive systems Sensorless control algorithms Loss segregation in drive systems Condition monitoring of industrial and transportation applications Recent publications demonstrate expertise in variable phase-pole machines, harmonic plane decomposition, predictive control algorithms, and advanced modeling of permanent magnet motors. Key application areas include transportation electrification, wind energy systems, and industrial drive technologies. Scientific roles include: Associate Editor, IET Electric Power Applications Journal (2019-present) Theme Co-Leader, Swedish Electromobility Center (2020-present) Member, IEEE (2021-present) and IET (2006-present) He leads the strategic partnership with ABB and contributes to doctoral program committees at University of Padova.
Andrea Bonfiglio is an Associate Professor at the Department of Naval, Electrical, Electronic and Telecommunication Engineering (DITEN) within the School of Engineering at the University of Genoa. His work focuses on power systems, smart grids, and renewable energy integration with a particular emphasis on innovative control strategies and energy storage solutions. Teaching areas: Electrical Systems, Industrial Measurements, Energy Security Key research themes: Smart distribution networks, synthetic inertia, microgrid control, vehicle-to-grid technologies, battery energy storage Recent work explores virtual energy partitioning, load flow optimization, and inertia allocation in transmission networks Contact: a.bonfiglio@unige.it His publications highlight advanced control methodologies using machine learning and sliding mode control for both transmission and distribution networks, with applications to renewable integration and grid stability challenges.
Lam James is a Chair Professor of Control Engineering at the University of Hong Kong (HKU), affiliated with the Faculty of Engineering. He holds a BSc (1st Hons.) in Mechanical Engineering from the University of Manchester, and MPhil/PhD degrees from the University of Cambridge. His academic journey includes roles as a Croucher Fellow, Lecturer at the University of Melbourne, and faculty member at City University of Hong Kong before joining HKU in 1993. Professor Lam serves as Editor-in-Chief for four international journals including IET Control Theory and Applications and Journal of The Franklin Institute . His research focuses on networked control systems, vibration control, control theory, and multi-agent systems. With 600+ peer-reviewed publications, he maintains an H-index of 102 (Web of Science) and 108 (Scopus), recognized as a Highly Cited Researcher in multiple fields. Education: BSc Manchester (Mechanical Engineering), MPhil/PhD Cambridge Editorial Roles: 20+ journals, including leadership roles since 2012 His awards include Foreign Membership of Academia Europaea (2024), National Academy of Artificial Intelligence membership (2025), and two State Natural Science Awards (2015, 2019). He is a Fellow of multiple institutions including IEEE, IMechE, and HKIE.
Leif Eriksson is a Professor at Chalmers University of Technology , specializing in Radar Remote Sensing within the Department of Space, Earth and Environment . His career at Chalmers began in 2004, and he was promoted to Professor in 2022 after serving as Group Leader (2012–2017) and Head of Faculty Assembly (2017–2020). His research focuses on developing advanced methods for environmental monitoring using radar data, particularly synthetic aperture radar (SAR) from satellites and aircraft. Leadership Roles: Group Leader (Radar Remote Sensing), Faculty Assembly Head Key Collaborations: Rymdstyrelsen, EU Horizon, VINNOVA, European Space Agency Research Interests : Dr. Eriksson’s work spans forest biomass estimation , sea ice dynamics , and ocean surface current/wind retrieval . He integrates SAR data with in situ observations and climate models to study: Forest degradation (clear cuts, storm damage) via multi-temporal SAR Sea ice concentration, drift patterns, and thickness in Arctic regions Wind vectors and surface currents using interferometric SAR techniques Applications for maritime navigation safety and polar shipping optimization Article Trends : His recent publications emphasize SAR’s role in transport infrastructure monitoring (e.g., Iron Ore Line degradation), pan-Arctic landfast ice stability , and multi-frequency SAR fusion for enhanced sea ice observations. Collaborative work with teams across Europe and the U.S. highlights interdisciplinary approaches to climate and marine research. Projects & Grants : Dr. Eriksson leads or contributes to projects such as: CAISA (2022–2024): Air-ice-sea data assimilation EONav (2016–2019): Copernicus data for maritime navigation SEDNA (2017–2020): Safe Arctic shipping Forest Biomass Monitoring (2017–2018): Spaceborne SAR applications His work is supported by Rymdstyrelsen, EU Horizon, and industry partners like Trafikverket. Labs & Teams : He is central to the Radar Remote Sensing Group at Chalmers, collaborating with institutions like Lund University and international bodies such as ESA. His research often involves satellite campaigns (e.g., TanDEM-X, Sentinel) and field studies in polar regions.
John Kingston is a Professor of Linguistics and Director of the Phonetics Lab at the University of Massachusetts Amherst, where he has been since 1990. He holds a BA and MA from the University of Chicago (1976–1977) and a PhD from UC Berkeley (1985). His research focuses on the interplay between phonetics and phonology, particularly speech perception and its influence on phonological representations. He co-founded the Laboratory Phonology Conference series in 1987 and has conducted fieldwork on Otomanguean languages. His work emphasizes experimental methods to study phonological questions, including studies on vowel perception, tone systems, and cross-linguistic phonetic patterns. Kingston’s academic journey includes roles at the University of Texas, Austin (1984–1986) and Cornell University (1986–1990). His research explores how auditory processing and linguistic knowledge shape speech perception, with notable contributions to understanding tonogenesis, perceptual contrast effects, and vowel category learning in second languages. He collaborates on grants examining Ganong effects and phonological inventories, advocating for theories that bridge perceptual and structural aspects of language. His lab, the Phonetics Lab, supports experimental work on speech perception and production. Kingston is also the Honors Program Coordinator, mentoring students in linguistics and related fields. Despite no explicit awards listed, his extensive publications and conference leadership reflect his scholarly impact.
Kristofer Pister is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He co-directs the Berkeley Sensor and Actuator Center (BSAC) and the Ubiquitous Swarm Lab. His career spans groundbreaking innovations in Micro/Nano Electro Mechanical Systems (MEMS), Control Systems, and Low-Power Circuits, with a focus on Smart Dust and synthetic insects. Education: Ph.D. and M.S. in EECS from UC Berkeley (1992, 1989); B.A. in Applied Physics from UC San Diego (1986). His research areas include MEMS , Control Systems , Robotics , and Integrated Circuits , with recent work on self-powered micro-sensors, crystal-free radios, and interplanetary swarm networks. Key awards include the ISA Albert F. Sperry Founder Award (2009) , Alexander Schwarzkopf Prize (2006) , and the NSF CAREER Award (1996) . He has authored numerous influential publications in wireless sensor networks and microrobotics. His lab, Ubiquitous Swarm Lab , explores distributed robotics and swarm intelligence. Pister emphasizes open collaboration in research, ethical conduct in academia, and efficient resource utilization for graduate students.
Chendi Zhang is a Professor of Finance at the University of Exeter Business School. He serves as the founding Director of the Exeter Sustainable Finance Centre and Director/Treasurer of the Global Research Alliance for Sustainable Finance and Investment. Previously, he was Associate Dean for Research & Impact (2021-2025) and Director of Research for Finance and Accounting (leading REF2021 submission). He holds affiliations with the Global Systems Institute and Environment and Sustainability Institute, contributing to UN Sustainable Development Goals including Climate Action and Responsible Consumption. Education PhD in Financial Economics from Tilburg University MRes in Finance from Tilburg University MSc in Economics from Tilburg University BSc in International Finance from Shanghai Jiao Tong University Research Focus Professor Zhang's research explores sustainable investing, corporate finance, and behavioral finance with emphasis on ESG integration, climate risk, and stakeholder governance. His work examines how environmental/social factors influence financial markets, corporate decision-making, and asset pricing through empirical and theoretical frameworks. Recent studies analyze biodiversity's financial impact, carbon pricing mechanisms, income inequality disclosures, and ESG resilience during crises (e.g., COVID-19, Ukraine conflict). His research identifies market inefficiencies related to climate sensitivity, gambling sentiment, and dividend policies while exploring corporate governance in state-owned enterprises. Funding and Recognition Research funded by UKRI Natural Environment Research Council, British Academy, BNY Mellon, Royal Bank of Canada, and World Bank. Work featured in The Economist , Wall Street Journal , and Forbes . Articles published in top journals including Management Science and Journal of Financial Economics , cited over 10,000 times. Professional Service Vice Chair of Research Committee for Chartered Association of Business Schools. External examiner for Imperial College London. Previous appointments at University of Cambridge, University of Warwick, University of Sheffield, and Tilburg University.
Brent W. Roberts is a Professor of Psychology at the University of Illinois , affiliated with the Social-Personality-Organizational Division. He serves as Chair of the Social and Behavioral Sciences Research Initiative and holds the Edward William and Jane Marr Gutgsell Professorship. Education: Ph.D. in Personality Psychology (1994), University of California, Berkeley Research focuses on personality development across adulthood, personality assessment (especially conscientiousness ), and personality-health relationships . Methodologically, he emphasizes IRT and contextualized assessments. Scientific contributions include: Over 235 research outputs Highly Cited Researcher (Thomson Reuters 2016-2017) Key publications on BESSI, CONIC model, and longitudinal personality analysis Award-winning scholar: J. S. Tanaka Dissertation Award (1995) Carol & Ed Diener Mid-Career Award Theodore Millon Mid-Career Award Henry Murray Award Honorary Doctorate, University of Basel As academic advisor, he has mentored numerous graduate students and postdoctoral fellows in personality psychology, with lab alumni now at institutions like University of Houston and Carleton University.
