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Bradford BellView profile

Professor

Cornell UniversityUnited States

Bradford S. Bell is the William J. Conaty Professor in Strategic Human Resources and Director of the Center for Advanced Human Resource Studies at Cornell University's ILR School. His academic career spans roles as editor of Personnel Psychology and fellowships with the Society for Industrial and Organizational Psychology and American Psychological Association. He holds a Ph.D. in Industrial and Organizational Psychology from Michigan State University. Education: B.A. Psychology, University of Maryland (College Park) M.A. and Ph.D. Industrial and Organizational Psychology, Michigan State University Research Focus: Dr. Bell's work centers on training/development, team dynamics, virtual work, and technology's impact on organizations. He has published widely in journals like Journal of Applied Psychology and Academy of Management Learning & Education , with over 150+ publications. His research emphasizes practical applications in workplace learning systems and team effectiveness. Awards: Early Career Achievement Award (Academy of Management HR Division, 2008) Professional Contributions: Advises organizations globally on HR strategy through the Center for Advanced Human Resource Studies. His consulting spans banking, manufacturing, and public sectors. Active in professional development, he teaches courses on HR management, training, and work teams.

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OU PengfeiView profile

Assistant Professor

National University of SingaporeSingapore

Asst. Prof. OU Pengfei is an Assistant Professor and NUS Presidential Young Professor in the Department of Chemistry at the National University of Singapore, Faculty of Science. He leads the AI for Chemistry (AI4Chem) research group, focusing on computational catalysis, machine learning, and materials science. Previously, he was a Research Associate at Northwestern University and a Postdoctoral Fellow at the University of Toronto under Prof. Edward H. Sargent, and earned his Ph.D. from McGill University. Education: Ph.D., McGill University, 2020 M.Eng., Central South University, 2015 B.Eng., Central South University, 2012 Research interests include catalyst design for electrochemical reactions using ab initio DFT, molecular dynamics simulations, and AI-driven methods. He develops dynamic simulations of chemical processes under reaction conditions and machine learning tools for accelerated catalyst discovery. His work addresses challenges in energy and environmental applications such as CO2 reduction and hydrogen evolution. Notable awards include the NUS Presidential Young Professorship (2024), Climate Positive Energy Postdoctoral Fellowship (2021), and Chinese Government Award for Outstanding Self-Financed Students Abroad (2020). Labs/Teams: The AI4Chem group integrates theory-guided and data-driven approaches to advance computational catalysis, with three core research directions: (1) reaction mechanism exploration and catalyst optimization, (2) dynamic structure-performance relationships under reaction conditions, and (3) machine learning algorithms for high-throughput screening.

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Siyu TangView profile

Assistant Professor

ETH ZurichSwitzerland

Siyu Tang is an Assistant Professor in the Department of Computer Science at ETH Zürich, where she leads the Computer Vision and Learning Group (VLG) at the Institute of Visual Computing. Her research focuses on computational models for human perception and digitalization through computer vision and machine learning. Her educational background includes: PhD in Computer Science, Max Planck Institute for Informatics (2017), supervised by Prof. Bernt Schiele Master of Science in Media Informatics, RWTH Aachen University Bachelor of Science in Computer Science, Zhejiang University, China Dr. Tang specializes in human-centric computer vision, developing statistical models for motion analysis, pose estimation, and digital human creation. Her work integrates machine learning with optimization techniques to enable machines to interpret human activities from visual data, with applications spanning virtual reality, healthcare, and human-computer interaction. Key research thrusts include generative models for content creation, egocentric vision, and human motion synthesis. Her recent publications (2024-2025) demonstrate intense focus on 3D human modeling and neural rendering, with Gaussian splatting emerging as a dominant technique for efficient avatar creation and scene reconstruction. Significant themes include text-driven motion synthesis using diffusion models, relightable avatars, surgical training applications, and egocentric multimodal pretraining. This work bridges computer vision, graphics, and machine learning to advance human digitalization. No scientific awards were mentioned in the provided text. Dr. Tang leads the VLG research group at ETH Zürich, mentoring PhD and Master's students in human-centric AI. She previously secured an early career research grant from the Max Planck Institute for Intelligent Systems to establish her independent research program. Her group actively pursues funding for projects in human motion analysis, 3D reconstruction, and generative modeling, with strong industry and clinical collaborations. The Computer Vision and Learning Group (VLG) operates within ETH's Institute of Visual Computing, maintaining dedicated facilities for motion capture, 3D scanning, and high-performance computing. The team collaborates internationally with institutions like the Max Planck Society and focuses on scalable solutions for real-world human digitalization challenges, including surgical training systems and immersive virtual environments.

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Filipa Melo LopesView profile

Lecturer

University of EdinburghUnited Kingdom

Filipa Melo Lopes is a Lecturer in Social and Political Philosophy at the University of Edinburgh, affiliated with the School of Philosophy, Psychology and Language Sciences. She currently directs the Scottish Feminist Philosophy Network. Her research focuses on feminist philosophy, social theory, sexual ethics, and the work of Simone de Beauvoir, with recent attention to incel extremism, fashion ethics, and gender-based violence. Education: B.A. from Simon Fraser University (Canada), Ph.D. from University of Michigan (USA). Teaching includes undergraduate courses like 'Advanced Topics in Feminist Philosophy: Gender and Beauty' and PhD supervision in feminist ethics and political theory. She has supervised several doctoral students, including Lilith W. Lee (now Assistant Professor at Vrije Universiteit Amsterdam). Publications analyze themes such as misogynistic dehumanization, feminist fashion ethics, and Beauvoirian critiques of incel ideology. Her work bridges academic philosophy with public discourse on topics like sugar dating and incel violence. Active in feminist knowledge networks, she also writes for broader audiences on fashion, misogyny, and cultural criticism.

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Shiva NejatiView profile

Professor

University of OttawaCanada

Shiva Nejati is a Professor at the University of Ottawa 's School of Electrical Engineering and Computer Science . He holds a PhD in Computer Science from the University of Toronto and previously worked as a Senior Scientist (2012-2019) and Scientist (2009-2012) at the SnT Centre (University of Luxembourg) and Simula Research Laboratory. Research focus: Software engineering for cyber-physical systems (autonomous vehicles, IoT), blending formal verification, machine learning, and search-based testing Key tools developed: ARIsTEO, SOCRaTEs, SimCoTest, EPIcuRus Editorial roles: Associate Editor for EMSE Journal (2025–), ASE Journal (2025–), IEEE Transactions on Software Engineering (2020–2024) His work combines formal methods , empirical software engineering , and AI/ML to address verification challenges in complex systems, particularly through evolutionary algorithms and surrogate modeling . Notable collaborations include industry partners in telecommunications, automotive, and aerospace sectors. Recent publications emphasize large language models for requirements analysis, adversarial testing of vision systems, and multi-objective optimization for test generation. His Sedna Research Lab actively trains graduate students in these cutting-edge methodologies.

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Gerben van der VegtView profile

Professor

University of GroningenNetherlands

Gerben van der Vegt is a Professor of Organizational Behavior at the University of Groningen’s Faculty of Economics and Business, Department of HRM & OB. He holds a PhD (cum laude) from the University of Groningen and degrees from Utrecht University. His research focuses on team dynamics, including composition, diversity, membership changes, and performance management. He has served as Director of the Research Institute SOM (2015–2021) and Director of the Master in Human Resource Management program (2005–2007). Currently, he is also a Visiting Professor at Hong Kong Baptist University. Education: PhD (cum laude) in Social and Organizational Psychology, University of Groningen (1998) M.S. in Social and Organizational Psychology, Utrecht University B.S. in Psychology, Utrecht University Research Interests: Effective team functioning and composition Influence of diversity and membership changes on performance Inter- and intra-team collaboration mechanisms Organizational resilience through communication strategies Recent work emphasizes team boundary management, disruption resilience, and newcomer integration. He serves on editorial boards for Academy of Management Journal and Organization Science . His advising includes 10 supervised works, focusing on organizational behavior and team dynamics. His lab explores interdisciplinary approaches to team performance and organizational challenges.

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Roberto WeberView profile

Professor

University of ZurichSwitzerland

Roberto Weber is the UBS Foundation Professor of Economics of Corporate Culture, Business Ethics, and Social Responsibility at the University of Zurich's Department of Economics. He also serves as Director of the Zurich Graduate School of Economics and was previously Vice Chairman of the Department of Economics (2017–2021). His research focuses on behavioral and experimental economics, moral decision-making, and organizational/institutional studies. He holds a Ph.D. from the California Institute of Technology (2000) and has held academic appointments at Carnegie Mellon University and Maastricht University. Education: Ph.D. in Social Science, California Institute of Technology (2000) MS in Social Science, California Institute of Technology (1996) BA in Economics, Texas A&M University (1994) Research Interests: His work explores behavioral and experimental economics, decision-making under moral constraints, and organizational dynamics. He investigates how cultural, institutional, and ethical factors shape economic outcomes, with contributions to leadership studies, social responsibility, and experimental methodologies. Awards and Roles: CESifo Research Network Fellow Department Editor for Behavioral Economics and Decision Analysis at Management Science Board of Trustees, Excellence Foundation Zurich (2012–2022) Leadership and Grants: He oversees the Zurich Graduate School of Economics and has directed various research initiatives. His experimental studies often involve collaborations on topics like trust, leadership effectiveness, and ethical decision-making frameworks. Labs and Teams: Associated with experimental economics labs, including the Pittsburgh Experimental Economics Laboratory (PEEL) and the Economic Science Institute (Chapman University), he contributes to interdisciplinary research in behavioral economics.

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Sohmyung HaView profile

Associate Professor

New York UniversityUnited States

Sohmyung Ha is an Associate Professor of Electrical Engineering and Bioengineering at NYU Abu Dhabi and holds a Global Network position at NYU Tandon School of Engineering. He leads the Integrated BioElectronics Laboratory, focusing on advancing silicon integrated technologies for biomedical applications such as implantable devices and wearable sensors. His expertise spans biomedical circuits, neural interfaces, and wireless power systems. Education: MS (2004, KAIST), PhD (2016, UC San Diego) with a Best Thesis Award. Prior industry experience includes analog circuit design at Samsung Electronics (2006-2010). Academic affiliations include NYU Abu Dhabi, NYU Tandon, and global collaborations. Research interests include high-performance biomedical sensors, neural prosthetics, and energy-efficient bioelectronic systems. Notable achievements include a Best Paper Award (ISCAS 2024) and innovations in impedance spectroscopy and neural interface ICs. Current projects emphasize closed-loop neural interfaces, subcutaneous glucose monitoring, and retinal prostheses. His lab develops miniaturized, power-autonomous systems for healthcare applications.

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Michela BecchiView profile

Associate Professor

North Carolina State UniversityUnited States

Michela Becchi is an Associate Professor in the Department of Electrical and Computer Engineering at North Carolina State University. She specializes in computer architecture, systems software, and applications, with a focus on heterogeneous systems, parallel algorithms, and acceleration techniques for bioinformatics, pattern recognition, and quantum computing. Her work spans multi-core CPUs, GPUs, FPGAs, and distributed clusters, emphasizing the boundary between hardware and software design. Dr. Becchi holds a Ph.D. and Master’s degree in Computer Engineering from Washington University in St. Louis (2009) and a Bachelor’s degree in Computer Engineering from Politecnico di Milano, Italy (2000). Her research has been recognized with prestigious awards, including the NSF CAREER Award (2015) and the University of Missouri System President Award for Early Career Excellence (2016). Her research interests include compiler and runtime techniques for heterogeneous systems, acceleration of bioinformatics algorithms, and high-speed networking applications. She has pioneered frameworks for efficient data transformation, GPU-accelerated compression, and memory-efficient graph algorithms for quantum computing. Her work also explores thread coarsening, mixed-precision auto-tuning, and secure multi-core processor design. Key contributions include the PILOT runtime system for GPU memory management, the GPU-FPtuner auto-tuner for floating-point applications, and innovative approaches to automata processors for genomic analysis. Her publications emphasize reproducible accuracy in scientific simulations and the optimization of irregular applications on many-core platforms.

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Adriana KuglerView profile

Professor

Georgetown UniversityUnited States

Dr. Adriana Kugler is a Full Professor at Georgetown University’s McCourt School of Public Policy and Economics. She currently serves as Governor of the Federal Reserve Board, on leave from Georgetown since 2023. Previously, she was U.S. Executive Director at the World Bank (2022–2023), Chief Economist at the U.S. Department of Labor (2011–2013), and Vice Provost for Faculty at Georgetown (2013–2016). Her research focuses on labor markets, policy evaluation, and development economics, with notable work on unemployment insurance, immigration, and vocational training. She holds a Ph.D. from UC Berkeley (1997) and a BA from McGill University (1991). Education : Ph.D. in Economics, University of California, Berkeley (1997) B.A. in Economics and Political Science (First Class Honors), McGill University (1991) Research Interests : Dr. Kugler examines the impact of public policies on labor markets, including payroll taxes, employment protections, and unemployment insurance. Her work bridges academia and policy, addressing issues like occupational licensing, immigration, and global development. She has published in top journals such as the American Economic Review and the Journal of Labor Economics. Awards : Chase Award (U.S. Treasury, 2023) 100 Most Influential Women in U.S. Finance (Barrons, 2024–2025) John T. Dunlop Outstanding Scholar Award (2007) Global Development Network First Prize (2010) Grants and Service : She secured NSF grants supporting women in STEM and advised Congress on economic policies. She chairs committees at the National Academies of Science and served on the Bureau of Labor Statistics’ Technical Advisory Committee. Labs/Teams : Founder of the International Summer Institute on Policy Evaluation (2010–2013) and affiliated with multiple research institutes, including NBER and CEPR.

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Cathryn MitchellView profile

Professor

University of BathUnited Kingdom

Cathryn Mitchell is a Professor of Radio Science and Royal Society Industry Fellow at the University of Bath, specializing in ionospheric physics, position, navigation, and timing (PNT). She leads research in the Space & Telecoms Research Group (STAR), focusing on radio propagation, data assimilation, and space weather impacts on communication systems. Her work bridges theoretical, computational, and experimental approaches, with applications in satellite navigation, climate monitoring, and defense sectors. Her research interests include ionospheric tomography, HF communications, and the development of robust PNT systems. Mitchell collaborates extensively with industry partners like Spirent Communications on future navigation technologies and space weather resilience. She has held roles such as Academic Director of the Doctoral College and contributes to interdisciplinary projects like the DRIIVE initiative exploring ionospheric variability with EISCAT-3D radar. Recent work emphasizes ionospheric effects during geomagnetic storms (e.g., the 2024 Gannon Storm) and cooperative autonomous systems under communication constraints. Her projects are funded by the Royal Society, Natural Environment Research Council (NERC), and ESA, addressing challenges in space weather forecasting and PNT system reliability. Awards: Royal Society Industry Fellow (2022–present) Key Projects: Royal Society Industry Fellowship on Future PNT Technologies DRIVERS (DRIIVE): Ionospheric Variability Studies EISCAT-3D FINESSE: Ionospheric Structuring Analysis Mitchell’s lab, STAR, integrates academic and industrial partnerships to advance space weather applications and sustainable navigation systems, contributing to UN Sustainable Development Goals related to climate action and innovation.

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Raquel CamposView profile

Assistant Professor

London School of Economics and Political Science (LSE)United Kingdom

Dr Raquel Campos is an Assistant Professor (Education) of Management at the Department of Management, London School of Economics and Political Science (LSE). Her work focuses on the impact of information technologies on institutional performance across firms and universities. She holds dual expertise in economics (PhD, MSc from Universidad Rey Juan Carlos) and engineering (BSc in Electrical Engineering and Computer Science). Prior to academia, she worked in IT project management and consulting in Spain and the US. Key qualifications include a PhD in Economics (2013) and MSc in Economics (2009), both from Universidad Rey Juan Carlos. She also completed the University of London’s BSc in Economics and Management via its external program. Her multidisciplinary background spans electrical engineering, computer science, and law. Research interests center on organizational economics, personnel economics, and ICT applications in labor markets. Notable works include studies on hurricane impacts on academic collaborations, internet recruitment strategies in Spain, and gender disparities in engineering careers. She has presented at major labor economics workshops and serves as a referee for Economics of Innovation and New Technology . Teaching responsibilities include leading the Strategy module (MG301) at LSE, where she received top teaching awards including the 2019 Excellence in Education Award. Her professional experience includes roles as Visiting Researcher at University of Kent (2015-2017), and prior IT project management roles in sectors like banking and real estate. Awards highlight her educational contributions: Top 10% performer in LSE Management Department teaching evaluations (2018-19) and Excellence in Education recognition. Current research explores missing skills for EU entrepreneurs/managers using PIAAC data in collaboration with M. Arrazola and J. de Hevia.

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Dino PedreschiView profile

Professor

National Research Council of Italy (CNR)Italy

Dino Pedreschi is a Full Professor of Computer Science at the University of Pisa, affiliated with the Department of Computer Science (DI-UNIPI). He co-leads the Pisa KDD Lab, a joint research initiative between the University of Pisa and the Italian National Research Council’s Institute of Information Science and Technology, one of the earliest labs focused on data mining and knowledge discovery. His research spans Big Data Analytics , Social Network Analysis , Human Mobility Analysis , Privacy-by-Design , Explainable AI (XAI) , and ethical data mining . He is a pioneer in privacy-preserving data mining and has contributed significantly to understanding societal impacts of AI and big data. Recent publications highlight trends in explainable AI , fairness-aware data mining , urban mobility modeling , and socio-economic nowcasting , reflecting a strong interdisciplinary focus combining computer science, social science, and policy. Notable scientific awards include: Google Research Award on Privacy (2009) University of Pisa Ordine del Cherubino (2017) Pedreschi has played leadership roles in major conferences such as ECML/PKDD (Co-Chair 2004), ICDM (Vice-Chair 2005), and ICDE (Vice-Chair 2014). He founded the Business Informatics MSc program at the University of Pisa to train interdisciplinary data scientists. He has been a visiting scientist at the University of Texas at Austin, CWI Amsterdam, UCLA, and the Barabási Lab at Northeastern University. He actively contributes to European research initiatives including SoBigData++, FAIR, and TAILOR, and has advised on AI policy, including testimony before the Italian Parliament on AI and labor markets. He is a key member of the Pisa KDD Lab, a leading research group in data science and AI ethics, fostering collaboration between academia and public institutions.

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David DotyView profile

Professor

University of California, DavisUnited States

David Doty is a Professor in the Department of Computer Science at the University of California, Davis . His research focuses on the intersection of molecular systems and computation , exploring how natural processes like chemical reactions , DNA nanotechnology , and self-assembly can perform computation. He also investigates connections to theoretical computer science, including distributed computing and algorithmic information theory . Doty's work bridges physics , chemistry , and biology through rigorous computational models like the Tile Assembly Model and Population Protocols . His research program includes software development ( scadnano , ppsim ), theoretical analysis, and collaborations with experimentalists. He teaches courses on theory of computation and molecular computing , and has advised numerous students in his research group. His publications cover topics such as algorithmic self-assembly , chemical reaction networks , and thermodynamic binding networks , with a focus on understanding fundamental computational and physical limits. Key software tools developed by his group include scadnano for DNA design and ppsim for population protocol simulations. Doty's recent research trends explore rate-independent chemical computing , error correction , and stochastic modeling in molecular systems. Current academic activity includes teaching ECS 120 (Undergraduate Theory of Computation), ECS 220 (Graduate Theory of Computation), and ECS 232 (Theory of Molecular Computation). He maintains a research lab in 2306 Academic Surge and continues to publish in leading conferences like DNA Computing and CMSB .

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Steve WhittakerView profile

Professor

University of California, Santa CruzUnited States

Steve Whittaker is Professor of Human-Computer Interaction at the University of California at Santa Cruz. He conducts interdisciplinary research at the intersection of social science and computer science, focusing on how technology affects human memory, communication, and personal information management. His current research explores human-centric AI systems, mental health technologies, and digital identity. His research interests center on designing interactive systems that support human needs in digital environments. He investigates how people manage digital information, remember personal experiences through lifelogging, and interact with conversational agents and social robots. His work emphasizes computational well-being, affective computing, and the social implications of technology use. He has made foundational contributions to the fields of personal information management (PIM), computer-mediated communication (CMC), and human-robot interaction. The recent publications reflect a strong trend toward mental health technology, human-AI interaction, and digital well-being. His work spans from theoretical models of emotion and memory to practical systems for mental health apps, chatbots, and immersive visualization. He frequently publishes in top-tier venues such as CHI, CSCW, and IUI, often in collaboration with researchers across disciplines. Lifetime Research Achievement Award from SIGCHI Fellow of the Association for Computational Machinery (ACM) Member of the CHI Academy Lasting Impact Award from ACM CSCW Best Paper Award at CSCW10 Best Paper Award at CHI07 Honourable Mention at ACM CHI 2020 Multiple best paper nominations at CHI, CSCW, and IUI MIT Siegel Prize Steve Whittaker has supervised numerous PhD and Master’s students, though specific names are not listed in the provided text. His research has been funded by major grants from NSF, NIH, and industry partners, enabling long-term studies on digital behavior and system development. He is Editor of the journal Human Computer Interaction and has authored over 200 peer-reviewed publications. His most recent book, The Science of Managing Our Digital Stuff (MIT Press), co-authored with Ofer Bergman, synthesizes decades of research on personal information management. He leads a vibrant research lab at UC Santa Cruz that focuses on human-centered computing, where students and collaborators work on projects involving AI, mental health, digital memory, and social interaction. The lab has produced influential work on lifelogging, email management, telepresence robots, and algorithmic transparency. The team employs mixed methods, combining qualitative studies with system design and evaluation.

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