Professor He Bingsheng is a faculty member at the Department of Computer Science, School of Computing, National University of Singapore (NUS), where he also serves as Vice-Dean, Research. He holds a Ph.D. in Computer Science from the Hong Kong University of Science & Technology (2008) and dual bachelor’s degrees in Computer Science & Engineering and Business Administration from Shanghai Jiao Tong University (2003). Education: Ph.D. (HKUST, 2008), B.E./B.B.A. (SJTU, 2003) Prior roles: Microsoft Research Asia (2008-2010), Nanyang Technological University (NTU), Singapore His research focuses on Big Data management systems , particularly on cloud computing and emerging hardware architectures (GPU, FPGA, NVM). He has led projects like ThunderGP, a novel FPGA-accelerated graph processing framework achieving 419x speedup for Covid-19 prevalence estimation. His work spans parallel/distributed systems and graph algorithms , with publications in ACM SIGMOD, VLDB, SC, and IEEE Transactions. The selected articles highlight his contributions to GPU/FPGA optimization , LLM applications , and graph analytics . He has received multiple best paper/demo awards, including IEEE/ACM ICCAD (2017), IEEE IC2E (2016), and ACM SIGMOD (2008). As a PC chair and editorial board member for journals like IEEE TPDS and TCC, he actively shapes academic discourse. PhD Students: Chen Xinyu, Tan Hongshi Courses Taught: CS4225/5425 Big Data Systems for Data Science
Sewon Min is an Assistant Professor at UC Berkeley's Electrical Engineering and Computer Sciences (EECS) department and a research scientist at the Allen Institute for AI. Her research focuses on Natural Language Processing (NLP) and Machine Learning, particularly Large Language Models (LLMs), emphasizing data-centric approaches and ethical AI practices. She holds a Ph.D. from the University of Washington (2024) and a B.S. from Seoul National University (2018). Her work includes advancements in retrieval-based models, mixture-of-experts architectures, and data privacy in LLMs. Notable projects include FlexOlmo (flexible data use in LLMs) and OLMoE (open mixture-of-experts models). She has been recognized with the ACM Doctoral Dissertation Award Honorable Mention (2025) and WAGS/ProQuest Innovation in Technology Award. Recent articles highlight her contributions to reasoning models, data tracing (OLMoTrace), and scalable retrieval systems (MassiveDS). She leads the Berkeley NLP Group and collaborates with BAIR, exploring topics like model transparency and ethical data usage.
Dominic Thibault is an Assistant Professor at the Faculty of Music, Université de Montréal . His research-creation explores human-machine interaction in musical contexts, focusing on embodied cognition through electroacoustic compositions, audiovisual performances, and musical software development. Co-director, Laboratoire Formes·Ondes Active member, CIRMMT (Centre for Interdisciplinary Research in Music Media and Technology) Research axis leader, Expanded Musical Practice (CIRMMT) Member, Québecor Millénium entrepreneurship committee Scientific committee member, ACFAS
Dr. Changyou Chen is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, State University of New York. His research focuses on Multi-Modal Learning Foundation Models Deep Generative Models Large-scale Bayesian Sampling with applications in document understanding, music-AI integration, and molecular representation learning. Research Trends revealed through his recent publications include Optimizing Multimodal Large Language Models Developing Novel Retrieval-Augmented Generation Frameworks Creating Benchmark Datasets for Visual Text Understanding Advancing Diffusion Models with Domain-Specific Constraints across domains from music sheets to biomedical documents. Scientific Contributions : UB Young Investigator Award (2020) Architect of LoCAL Framework for Long Document Understanding Co-developer of MusiXQA Benchmark Pioneering Work in Probability Contrastive Learning Academic Leadership includes mentoring 10+ graduate students and serving as Area Chair for major AI conferences (ICML, NeurIPS, AAAI, IJCAI). His Labs develop scalable solutions for multimodal reasoning, with recent work demonstrating practical GPU memory optimization through LoRA adapter sharing.
Prof. Dr. Jeanette Hofmann is Professor of Internet Politics at Freie Universität Berlin since 2017 and Honorary Professor at Universität der Künste Berlin since 2014. She heads the Research Group 'Politics of Digitalization' at WZB Berlin Social Science Center and serves as Principal Investigator for 'Technology, Power and Domination' at the Weizenbaum-Institute. Her work bridges academic research and policy engagement through roles in NETmundial+10, International Observatory on Information and Democracy, and European Commission expert groups. Her research expertise spans Digitalization and Democracy , AI and society , Digital regulation , and Internet governance . Hofmann examines how digital infrastructures reshape political agency, democratic processes, and societal regulation through governance theory and science and technology studies lenses. Recent work analyzes disinformation ecosystems, platform power dynamics, and bureaucratic resistance to digital transformation in public administration. Hofmann's publication trajectory (2019-2024) reveals intensifying focus on AI's democratic implications, with 60% of recent work addressing algorithmic governance, digital sovereignty, and platform regulation. Her scholarship appears in Big Data & Society , Internet Policy Review , and interdisciplinary policy reports for European institutions. Scientific Awards: No formal awards documented in source material Hofmann leads major research initiatives including the Weizenbaum-Institute's 'Technology, Power and Domination' group and European Commission expert panels on platform economy regulation. Her grant portfolio emphasizes policy-relevant research on digital governance, with recent funding supporting comparative studies of digital transformation in Germany, Singapore, and Taiwan. She directs WZB's 'Politics of Digitalization' research group and co-leads the Weizenbaum-Institute's critical technology studies cluster. These teams employ interdisciplinary methods combining discourse analysis, comparative case studies, and policy ethnography to investigate power dynamics in digital ecosystems.
Olli Sotamaa is a Professor of Game Culture Studies at Tampere University's Faculty of Information Technology and Communication Sciences, Department of Communication Sciences. He leads the Tampere University Game Research Lab alongside Professor Frans Mäyrä and serves as team leader in the Centre of Excellence in Game Culture Studies. Specializes in game cultural phenomena: online communities, fandom, modding, data-driven game development Co-edited Game Production Studies (Amsterdam University Press, 2021) His research focuses on game industry practices, data analytics impact, and player production cultures. Recent work examines game data labor, industry ethics, and digital preservation challenges. Key trends in his 15 most recent articles include: Game data work and algorithmic culture (2023-2025) Game modding and user-generated content (2021-2022) Game development practices (2019-2021) Game preservation and heritage (2020) Industry sustainability and ethics (2021-2025) Scientific awards: ERC-Advanced-Grant project 'Making Sense of Games (MSG)' Labs/teams: Tampere University Game Research Lab Centre of Excellence in Game Culture Studies
Dr. Aniket Bera is an Associate Professor in Computer Science at Purdue University and holds an Adjunct Associate Professor role at the University of Maryland at College Park (UMIACS). He directs the IDEAS Lab at Purdue and previously served as a Research Assistant Professor at UNC Chapel Hill. His research focuses on Affective Computing, Computer Graphics (AR/VR), AI & Robotics, Social Robotics, and medical AI applications for mental health diagnostics. Affiliations: Purdue University (Primary), University of Maryland (Adjunct), UMIACS Career: Joined Purdue in 2017, extensive industry collaborations with Disney Research, Intel, and C-DAC Research Interests: Affective Computing: Emotion perception via gait analysis, speech, and facial/body expressions AR/VR: Redirected walking, virtual environments, and human motion modeling Medical AI: AI-driven mental health detection systems (e.g., VidSole dataset) in collaboration with medical schools Key Contributions: Developed Project Dost (mental health initiative) Received 2020 Brain & Behavior Seed Grant ($X) for emotion-gait research Authored 65+ papers (1,800+ citations) with awards at IEEE VR 2021 Funding & Leadership: Serves as Senior Editor for IEEE RA-L (Planning/Simulation) Conference Chair for ACM SIGGRAPH MIG 2022 Labs/Teams: IDEAS Lab (Purdue), UMD GAMMA Group
Dr. Matthew Jones is a Senior Lecturer in Criminology at Swinburne University of Technology’s School of Social Sciences, Media, Film and Education. With a career spanning institutions in the UK and Australia, Matthew’s research bridges interdisciplinary domains including policing, sociology, law, and organizational studies. He is a Senior Fellow of the Higher Education Academy, emphasizing evidence-informed pedagogy and curriculum innovation. Affiliation: Swinburne University of Technology (2022–Present) Previous Roles: The Open University (2017–2022), Northumbria University (2014–2017), Cardiff Metropolitan University (2013–2014). Research Themes: Matthew’s work focuses on three core areas: Policing: Police visibility, digital strategies, occupational culture, diversity, and leadership. LGBTQI+ Criminology: Workplace discrimination, hate crimes, community-police relations, and victimology. Digital Criminology: Technology’s role in policing, crime prevention, and digital victim support systems. Publications: His 15 most recent articles highlight evolving trends in digital policing, police visibility, academic standards in policing education, and LGBTQI+ workplace experiences. These works span qualitative studies, policy analysis, and interdisciplinary collaborations, reflecting his commitment to visual criminology and semiotics. Scientific Awards: Senior Fellow of the Higher Education Academy (2022) Fellow of the Higher Education Academy (2013) Professional Activities: Matthew served as Chair (2019–2022) and Board Member (2013–2019) of the British Society of Criminology’s Policing Network. He led curriculum development for police apprenticeships (2017–2019) and contributed to the first UK Subject Benchmark Statement for Policing (2022). He supervises PhD students on topics like community policing, child maltreatment resilience, and crime drama narratives. Education: He holds an LLB in Law, an MSc in Social Science Research Methods, a PhD in Socio-Legal Studies, a PGCert in Higher Education pedagogy, and an MBA in Leadership Practice.
Kathleen M. Carley is a full professor at Carnegie Mellon University's School of Computer Science with courtesy appointments in Engineering and Public Policy, Heinz School, and Electrical and Computer Engineering. As director of the Center for Computational Analysis of Social and Organizational Systems (CASOS) and the Center for Informed Democracy and Social-Cybersecurity (IDeaS) , she leads interdisciplinary research at the intersection of network science, cognitive modeling, and cybersecurity. Ph.D. in Sociology from Harvard University SB degrees in Economics and Political Science from MIT Her research focuses on Dynamic Network Analysis (DNA) and Social-Cybersecurity (SC) , developing tools like ORA (network analysis), AutoMap (semantic mining), Construct (influence simulation), and BotHunter (bot detection). She has over 400 publications and 15+ active research projects addressing disinformation, cognitive security, and organizational resilience. Recent work examines LLM-powered bots , multi-platform misinformation dynamics , and public health analytics . As an IEEE Fellow, she contributes to standards in computational social science while teaching courses on network analysis and complex socio-technical systems.
Magali (Maggie) Delmas is a Professor of Strategy at the UCLA Anderson School of Management and the UCLA Institute of the Environment & Sustainability. She serves as Faculty Director of the UCLA Anderson Center for Impact, leading the Open for Good Initiative, which aims to make corporate sustainability data more transparent and actionable. Additionally, she directs the UCLA Center for Corporate Environmental Performance and previously served as President of the Alliance for Research in Corporate Sustainability (ARCS). Professor Delmas received her Ph.D. in Strategic Management from HEC Paris and an M.A. in Political Science from the University of Paris. Her academic journey has positioned her at the intersection of business strategy and environmental sustainability, where she has built a distinguished career examining how corporations can effectively integrate sustainability into their core operations. Dr. Delmas's research focuses on corporate sustainability strategy, climate-related disclosure, and the design of effective information strategies to promote conservation behavior and build green markets. She has authored over 100 articles, book chapters, and case studies that explore energy conservation, eco-labeling, climate lobbying, and the detection and prevention of corporate greenwashing. Her work particularly examines how behavioral interventions can effectively motivate sustainable practices, as demonstrated in her large-scale UCLA Engage program that used real-time energy feedback to uncover conservation strategies. Her research spans multiple disciplines, connecting business strategy with environmental science, behavioral economics, and policy analysis. A notable trend in her recent work involves the examination of how transparency in corporate sustainability reporting affects business practices and environmental outcomes. She has made significant contributions to understanding the relationship between eco-certification and product quality, particularly in the wine industry, where her research has shown that organic wines often receive higher quality ratings. Distinguished Scholar Award, Academy of Management/ONE Division Best Book Award, Academy of Management/ONE Division (The Green Bundle) Research Impact on Practice Award, Academy of Management & Network for Business Sustainability (two-time recipient) 2019 Academy of Management/Organization and the Natural Environment Best Book Award 2016 Organization & Environment Journal Best Paper Award Multiple additional awards spanning environmental economics, wine economics, and sustainability research Professor Delmas actively mentors doctoral students interested in strategy, corporate sustainability, environmental policy, and climate-related disclosure. Her students gain hands-on experience with unique datasets from the Open for Good Initiative and engage in interdisciplinary work across UCLA's Institute of the Environment & Sustainability. Her PhD students have pursued successful careers in both academia and policy roles, continuing to advance scholarship and practice in sustainability and strategy. She has secured significant research funding for projects examining energy conservation behavior, corporate sustainability reporting, and the effectiveness of environmental labels. As Faculty Director of the UCLA Anderson Center for Impact, she oversees the Open for Good Initiative, which produces the annual State of Corporate Sustainability Disclosure report. This initiative has become a critical resource for policymakers, investors, and business leaders seeking to understand corporate climate and environmental reporting practices. Her leadership also extends to the UCLA Center for Corporate Environmental Performance, where she coordinates research examining the relationship between environmental management and business performance.
Luís Miguel Mendonça Rato is an Associate Professor at the Universidade de Évora and a Senior Researcher with a PhD at Centro ALGORITMI. He is affiliated with the CST R&D Group and VISTA Lab R&D Lab, focusing on interdisciplinary research at the intersection of Electrical Engineering, Computer Science, and Agricultural/Biomedical applications. Academic Degree: PhD Current Position: Associate Professor Labs: VISTA Lab Researcher IDs: ORCID 0000-0003-4492-7548, ResearcherID A-9152-2013, CiênciaID A914-6344-CD2D His research spans machine learning applications in Agricultural Engineering (Sentinel-2 satellite data for nutrient analysis), Biomedical Imaging (MRI-ADC texture analysis for tumor classification), and Control Systems (predictive control algorithms for water delivery canals and solar fields). With an h-index of 11 and 51 publications, his work emphasizes hybrid systems combining traditional engineering with computational innovation. Recent publications highlight trends in SLAM efficiency (2024), cloud service optimization (2022), and deep learning for medical imaging (2022-2023). He has contributed to Smart Cities initiatives through projects like M-Traffic (2006) and NanoSen-AQM (2020). As a senior researcher, he leads projects in the CST R&D Group and VISTA Lab , with notable work in the Universidade de Évora ecosystem.
Prof. Dr. Michael Amberg is a full-time Professor of Business Informatics, specializing in IT Management, at Friedrich-Alexander University Erlangen-Nuremberg (FAU) . He has held this chair since 2001 and serves as director of the Dr. Theo and Friedl Schöller Research Center for Business and Society since 2010. Formerly, he occupied a professorship at RWTH Aachen University (1999–2001) and served as Vice Dean and Dean of FAU's Faculty of Law and Economics (2007–2012). Education: Computer Science at RWTH Aachen and FAU Erlangen-Nuremberg (1989) Research Focus: Systems development, IT management, and digitalization trends including AI, Industry 4.0, and smart services Leadership Roles: Spokesperson for the Department of Business and Social Sciences, Dean of Faculty (2007–2012), Research Center Director (since 2010) Key Collaborations: Interdisciplinary work with FAU's digitalization and innovation research cluster His recent publications address Explainable AI (XAI) integration into software development (2023) and human-centric work design in SMEs during Industry 4.0 transformations (2018). Current research emphasizes empirical methodologies for IT governance in digital ecosystems.
Dr. Mattia Andreoletti is a Lecturer at the Department of Health Sciences and Technology at ETH Zurich, working within the Professorship for Bioethics. His research spans philosophy of medicine and bioethics, with a focus on the ethical dimensions of AI in healthcare, dementia policy, drug regulation, and clinical reasoning. PhD from the European School of Molecular Medicine (SEMM), affiliated with the European Institute of Oncology (IEO, Milan) ORCID: 0000-0003-1880-0770 His work intersects with clinical ethics, particularly examining replicability in scientific research, evidential pluralism in drug regulation, and the ethical landscape of digital biomarkers. He contributes to courses such as Ethics in Drug Development and Ethics Workshop: The Impact of Digital Life on Society . The 15 most recent articles (2025-2023) highlight his engagement with AI ethics, dementia prevention, regulatory science, and clinical reasoning. Topics include ethical frameworks for digital biomarkers, evidential pluralism in drug approval, and philosophical foundations of rehabilitation sciences.
Joost de Moor is an Assistant Professor in Political Science at Sciences Po’s Centre for European Studies and Comparative Politics (CEE) . His research bridges Environmental Politics , Social Movements , and Political Participation , with a focus on climate activism, lifestyle politics, and post-political strategies. He holds a PhD in Social Sciences: Political Science from the University of Antwerp (2016) and has held postdoctoral positions at Keele University (2016-2018) , Stockholm University (2018-2021) , and Leiden University (2021) . A visiting scholar at the University of Mannheim (2015) , his work spans urban environmentalism, climate summit dynamics, and strategic movement adaptation.
Lynn Wu is an Associate Professor at the Wharton School of the University of Pennsylvania, focusing on the intersection of artificial intelligence, analytics, and innovation. She teaches MBA, undergraduate, and doctoral courses on emerging technologies' transformative impact on business and society. Education: B.S. in Finance and Computer Science, MIT M.S. in Computer Science, MIT Ph.D. in Management Science, MIT Sloan Her research explores how AI and digital platforms reshape productivity, workforce dynamics, and innovation strategies, with applications in antitrust policy and startup ecosystems. Key trends in her publications include AI's role in post-IPO innovation, robotics' impact on managerial roles, and social media's ability to mitigate funding disparities. Scientific Awards: Kauffman Best Paper Award (2019) Sandy Slaughter Early Career Award (2019) AIS Early Career Award (2018) ISR Best Published Paper (2014) Best Paper Awards at ICIS (2009), HICSS (2013), etc. She has collaborated with IBM, Google, Meta, and advised the U.S. Department of Justice and World Bank, with her work cited by The New York Times , The Economist , and Harvard Business Review .
