Mohammadtaghi Hajiaghayi is the Jack and Rita G. Minker Professor of Computer Science at the University of Maryland, College Park. He is affiliated with the Robert H. Smith School of Business and holds Research Affiliate positions at MIT CSAIL and the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS). His research focuses on algorithms, game theory, and network design, supported by NSF, ONR, and industry grants. He has received prestigious awards including ACM Fellow (2018) and EATCS Nerode Prize (2015) for his work on bidimensionality theory. Education: PhD from MIT (2005), postdocs at CMU and MIT, MSc from University of Waterloo, and BSc from Sharif University. He teaches courses like Data Science and Algorithms at UMD. Industry experience includes roles at Amazon, Google, and AT&T Labs. Over 20 students have graduated under his advisement, many in academia and industry. His work spans approximation algorithms, game theory, and big data. Projects include BigDND with Erik Demaine. He serves on editorial boards of Algorithmica, SODA, and others. Awards also include IEEE Fellow (2020) and Blavatnik Honoree (2020).
Dr. Mao Shan is a Senior Research Fellow at the Australian Centre for Robotics, part of The University of Sydney. He holds a PhD from The University of Sydney (2014) and has held research positions at Nanyang Technological University (2016-2017) and the Australian Centre for Robotics (2014-2016). His research focuses on autonomous systems, V2X communication, cooperative perception, and sensor fusion. Current students include Yaoqi HUANG, Henry LYU, Zhenxing MING, Nguyen TRAN, Tzu-yun TSENG, and Yupeng WANG. His work spans robotics, intelligent transportation systems, and control systems. Recent publications emphasize 3D object detection, cooperative perception frameworks, and autonomous navigation. He has contributed to the development of the University of Sydney Campus Dataset for robust autonomy testing and led cooperative perception projects funded by iMOVE CRC (2018). His research bridges theoretical advancements with practical applications in autonomous vehicles and multi-robot systems. Labs and affiliations include the Australian Centre for Robotics and the Intelligent Transport Systems Group. His interdisciplinary approach integrates probabilistic modeling, sensor fusion, and machine learning to address challenges in autonomous systems.
Professor Dan Goodley is a leading academic in Critical Disability Studies at the University of Sheffield , affiliated with the School of Education and co-director of the iHuman research center. His work bridges critical psychology , medical sociology , and posthuman theory to challenge ableist norms in education, healthcare, and society. He has secured major grants, including a £2.9m Wellcome Trust Discretionary Award and multiple ESRC-funded projects, focusing on themes like disablism , social justice , and inclusive research methodologies . Research Themes : Critical Disability Theory, Posthumanism, Dis/ability and Technology, Decolonizing Disability, Austerity and Dis/ability, Co-Production with Marginalized Communities. Grants : Wellcome Trust, ESRC, EPSRC, Research England, European Social Fund. Professional Roles : Visiting Professor at University of Ghent, Editorial Board Member for multiple journals, ESRC Peer Review College. His recent publications interrogate the intersections of disability , pandemic ethics , and autonomous technologies , often employing co-produced and participatory frameworks. He advocates for disabled voices in research and policy, emphasizing resilience and decolonizing praxis in global contexts.
Dr. Tan Viet Tuyen Nguyen is a New Frontiers Fellow (Lecturer) in AI at the University of Southampton, specializing in Human-Centered Artificial Intelligence and Social Human-Robot Interaction. His research focuses on multimodal learning for robots to adapt their behavior to human social needs, with applications in healthcare, education, and service environments. Prior to this role, he was a Research Associate at King’s College London and a Research Assistant on the EU-funded CARESSES project, developing culturally-aware assistive robots for elderly support. Education: PhD in Information Science (Robotics) from Japan Advanced Institute of Science and Technology. He has organized conferences such as the IEEE RO-MAN 2022 special session on nonverbal communication and served as a reviewer for top-tier robotics and AI conferences. Research Interests include: Human-Robot Collaboration, Multimodal Perception, Generative AI for Social Interaction, and Context-Aware Robot Behavior Generation. His work has been recognized with awards including the Best Paper Award at ROMAN 2022 and the Prospective Research Award at ICServ 2023. Teaching Responsibilities include courses on Biologically Inspired Robotics, High-Level Programming, and MSc/Undergraduate project supervision. He currently oversees two PhD students and collaborates on projects like 'Exploring the impact of AI-driven writing of engagement in climate change' and 'Bridging Generations and Cultures through Generative AI.' Labs/Teams: Member of the Agents, Interaction and Complexity Centre and the Centre for Robotics Research at Southampton.
Associate Professor Sam Kirshner is a faculty member at the University of New South Wales within the School of Information Systems and Technology Management . His research focuses on behavioral decision making , algorithmic impact on operations , and artificial intelligence applications in business contexts. PhD in Management Science from Queen’s University, Canada Teaching expertise in data visualization, predictive analytics, and AI ethics Co-author of Business Analytics: A Management Approach Member of the Ethical AI Advisory His research explores how psychological distance and construal level theory influence decisions in supply chains, technology management, and consumer behavior. Recent work examines ChatGPT's decision biases , algorithm aversion , and sustainable operations under financial constraints. Key publication trends show focus areas: AI ethics and human-AI collaboration Behavioral supply chain analysis Temporal/spatial psychological distance effects CO2 forecasting with sparse data Consumer behavior in digital platforms Virtual reality and cognitive processing Supervision roles include mentoring 2 PhD students and 6 honors students, contributing to the next generation of scholars in business analytics and technology management.
Feng Fu is an Associate Professor of Mathematics at Dartmouth College, with an adjunct appointment in Biomedical Data Science. He leads the Fu Lab, focusing on interdisciplinary research at the intersection of evolutionary game theory, computational social science, and biomedical data science. His academic roles include teaching courses such as Evolutionary Game Theory, Stochastic Processes, and Game Theory and Artificial Intelligence. Education: Senior Postdoc, ETH Zurich (2012-2015); Postdoc, Harvard University (2010-2012); PhD, Peking University (2010); B.S., Fudan University (2004). Research interests span evolutionary dynamics of cooperation, computational models of human behavior and social networks, cancer evolution, and behavioral epidemiology. Notable work includes studies on vaccine hesitancy, misinformation dynamics, and the hysteresis effect in vaccination uptake. His lab has received prestigious funding, including a Bill & Melinda Gates Foundation Grant (2019). Teaching and mentoring: Advised numerous graduate and undergraduate researchers, many of whom have received awards and advanced to academic or industry roles. Courses taught include QSS/MATH 30.04 (Evolutionary Game Theory) and MATH 146 (Game Theory and AI). Labs/Teams: Fu Lab at Dartmouth collaborates across disciplines, with projects in cancer immunotherapy modeling, network-based interventions, and computational social science. Recent lab highlights include advancements in understanding polarization and the development of targeted public health strategies.
Simon Dobson is a Professor of Computer Science and Deputy Head of the School of Computer Science at the University of St Andrews. His research focuses on complex systems, sensor analytics, computational tools for simulation, and data analytics. He leads grants exceeding EUR30M, including a £5M EPSRC-funded programme in Sensor Systems Software. He is a Fellow of the Royal Society of Edinburgh (2020) and advises the Scottish government. Education: BSc (University of Newcastle), DPhil (University of York), both in Computer Science. Professional: Chartered Engineer, Fellow of the British Computer Society. Research Interests: Complex systems, network science, higher-order networks, epidemiological modeling, and sensor data integration. Teaching: CS4203 (Computer Security), CS5728 (Complex Systems Modelling). Supervises PhD/MSc projects. Awards: Includes RSE Fellowship, BCS Fellowship, and multiple leadership roles in conferences and committees.
Reiko Heckel is a Professor of Software Engineering at the University of Leicester, serving as Director of Postgraduate Teaching for Computing degrees and Data Analytics Lead at the Leicester Innovation Hub. She previously held academic roles at the Technical Universities of Dresden and Berlin before joining Leicester in 2004. Her research focuses on graph transformation systems, model-based development, stochastic modeling, and formal methods in software engineering. She earned her PhD (Dr.-Ing.) in Computer Science from TU Berlin in 1998. Her research interests span software engineering pedagogy, formal specification techniques, and applications of graph grammars in system modeling. Recent work explores stochastic graph transformations for social networks, transparency engineering in AI systems, and blockchain-based smart contract frameworks. Her contributions bridge theoretical foundations with practical applications in cybersecurity, data integration, and human-centric systems design. Key contributions include advancements in automated test case generation via graph transformations, visual contracts for software reverse engineering, and formal methods for complex system analysis. Her work frequently intersects with industry through collaborations via the Leicester Innovation Hub, emphasizing data analytics and technology transfer. Education: MSc Computer Science, Technical University of Dresden PhD (Dr.-Ing.), Computer Science, TU Berlin (1998) Leadership Roles: Head of Department (2014-2018) Director of Postgraduate Teaching (Ongoing) Research Themes: Model-Based Development Stochastic Systems Analysis Graph Neural Networks Trustworthy AI Her publications reflect a focus on formal methods, with recent trends in applying graph transformation techniques to social network modeling, blockchain smart contracts, and educational pedagogy.
Brooke Erin Duffy is an Associate Professor in the Department of Communication at Cornell University, with affiliations in the College of Agriculture and Life Sciences (CALS), the Graduate Field of Feminist, Gender, and Sexuality Studies, and Media Studies. Her research investigates digital and social media industries, gender and identity dynamics, the gig economy’s impact on creative labor, and algorithmic governance in cultural production. She is a prominent voice in feminist media studies, blending academic rigor with public engagement through outlets like The Atlantic , Vox , and The New York Times . Education : Ph.D. in Communication (University of Pennsylvania, 2011), M.A. (University of Pennsylvania, 2008), B.A. in Communications (Penn State University, 2002) Her work highlights the gendered politics of digital labor , focusing on social media influencers, platform precarity, and the tension between authenticity and visibility. Recent research examines algorithmic systems, platform paternalism, and the visibility bind in creator economies. Duffy’s academic contributions include leadership in organizations like the American Influencer Council and Content Creator Scholar Network. She received multiple honors, including the 2021 Top Student-Led Paper award and the 2014 Lillian Lodge Kopenhaver Outstanding Woman Junior Scholar Award. Teaching : Courses on New Media & Society , Gender and Media , and Platform Labor and Precarity Public Impact : Regular commentary in global media and a 2024 contributor role at Forbes
Martin Volk is a Full Professor of Computational Linguistics at the University of Zurich, with a dual affiliation to the Department of Informatics since 2019. He holds a PhD from the University of Koblenz and has held academic positions at institutions including Stockholm University (part-time from 2008-2011), Zurich University of Applied Sciences, and the University of Georgia. His research focuses on grammar engineering, machine translation evaluation, multilingual text analysis, and cross-language information retrieval. Education : Born in Cochem, Germany Studied Computer Science and Computational Linguistics at EWH University, Koblenz Master's in Artificial Intelligence at the University of Georgia (Fulbright Scholar) PhD in Computational Linguistics from the University of Koblenz Research Interests : His work emphasizes data-driven NLP methods, including corpus-based approaches, parsing technologies, and the application of machine learning to historical and multilingual texts. Key focuses include: Machine translation systems and evaluation frameworks Grammar testing environments (e.g., GTU) OCR and digitization of historical documents (e.g., Gothic script) Development of parallel corpora for linguistic research Projects : SMULTRON: Multilingual parallel treebank project Bullinger Digital: Historical document digitization initiative Text+Berg: Digital Humanities project for alpine textual heritage EU-funded MuchMore (cross-language medical IR) Grants & Collaborations : Recipient of grants from the Swiss National Science Foundation, EU projects, and industry partnerships (e.g., Siemens, Xerox). His work integrates academic and industrial perspectives in NLP tool development. Labs & Teams : Leads research teams in the Institute of Computational Linguistics at UZH, focusing on projects like the Zurich Parallel Corpus Collection and MODERN (modeling discourse for MT).
Angela Crow is an Associate Professor at James Madison University (JMU) in the School of Writing, Rhetoric and Technical Communication, where she has served since 2012. Her research bridges literacy studies, design, and urban mobility, focusing on how communities advocate for car-free infrastructure and equitable public spaces. She explores the role of digital communication in fostering feminist interventions, particularly around cycling advocacy and street design. Her work intersects with gender studies, urban studies, and rhetorical theory. Educated at the University of Kansas (Ph.D., 1997) and Point Loma College (B.A., 1987), she has authored books on writing programs and composition studies, including Aging Literacies (2006) and Field of Dreams (2002). Recent publications analyze surveillance, privacy in digital contexts, and transportation equity. Her research often highlights marginalized voices in shaping public discourse. Research Interests: Her current projects examine embodied literacies in mobility advocacy, social media practices of grassroots movements, and the rhetoric of urban infrastructure. She critiques car-centric planning through feminist and critical frameworks, emphasizing accessibility and safety for non-car users. Her work also addresses aging populations’ digital literacies and the intersection of technology with social inequality. Publications: Her articles span rhetorical analysis of social movements, educational assessment frameworks, and the sociotechnical dimensions of writing. Recent trends include collaborations on privacy in big data and participatory design for community mobility.
Prof. Sanne Kruikemeier is a Professor of Digital Media and Society at Wageningen University & Research (WUR). She leads the ERC Starting Grant (HUNTING) and a NORFACE consortium grant, coordinating research across four European universities (2020–2024). As director of the Digital Data and Democracy Lab and member of the AlgoSoc Gravitation Program, she explores digitalization's societal and democratic impacts. Her research focuses on data-driven political targeting, social media's role in polarization, privacy behavior, and digital journalism. She holds roles on the editorial boards of journals like Human Communication Research , International Journal of Press/Politics , and Digital Journalism . Awards include the KNAW Early Career Award and ICA Herbert S. Dordick Dissertation Award. Her work bridges digital media, political communication, and societal change, addressing challenges like misinformation and democratic engagement. Kruikemeier advises PhD candidates on projects like data-driven campaigning's impact on democracy and polarization strategies. She engages in public discourse through media commentary on social media's role in politics and news consumption trends. Her interdisciplinary approach integrates communication science with computational methods to analyze modern political and social dynamics.
Professor Luke Prendergast is the Deputy Dean of the School of Computing, Engineering & Mathematical Sciences (SCEMS) at La Trobe University (LTU) and holds a Professorship in the Department of Mathematics and Statistics. He previously served as Head of Department (2014–2020) and led LTU's Statistics Consulting Platform. His research focuses on robust statistics, meta-analysis, dimension reduction, and applied statistics, leading the DRAMA research group. Collaborations span fields like endocrinology, disability studies, and respiratory health. He actively contributes to research grants, including projects on Prader-Willi syndrome and exercise for disability populations. Professor Prendergast's recent work emphasizes statistical software development (e.g., the rquest package) and applications in biostatistics, such as metabolomics analysis and health intervention fidelity. His articles address topics like quantile-based hypothesis testing, geospatial accessibility for disability care, and motivational interviewing efficacy. Professional roles include NHMRC grant review panels, editorial boards for Nutrients and Respirology , and leadership in the Statistical Society of Australia (SSA Vic). His teaching includes courses in meta-analysis, linear models, and data-based critical thinking. Grants funded projects on exercise programs for cerebral palsy populations and community-university partnerships for disability inclusion. Luke's work bridges statistical theory with real-world health challenges, emphasizing robust methodologies and interdisciplinary collaboration.
Filip Biljecki is an Assistant Professor jointly appointed at the Department of Architecture within the College of Design and Engineering and the Department of Real Estate at the NUS Business School, National University of Singapore. He is the founder and principal investigator of the NUS Urban Analytics Lab and was awarded the prestigious NUS Presidential Young Professorship in 2020. With over 150 peer-reviewed publications, his research bridges geomatic engineering, geospatial technologies, and urban data science to advance digital twins and data-driven urban planning. Dr. Biljecki's educational background includes: PhD in 3D GIS (cum laude), Delft University of Technology, Netherlands (2017) MSc in Geomatics, Delft University of Technology, Netherlands (2010) BSc in Geodesy and Geoinformatics, University of Zagreb, Croatia (2008) His research interests focus on emerging urban data sources, particularly urban imagery, and their application in 3D city modeling, digital twins, and GeoAI. He explores how crowdsourcing and open science can inform cutting-edge techniques for urban sensing and analytics at city-scale. His work significantly contributes to establishing smart cities through innovative methods that integrate recent advancements in computer science, geomatics, and urban data science. Analysis of his recent publications reveals a strong focus on street view imagery applications for urban analytics, digital twin development, and geospatial AI. His research spans multiple domains including urban morphology, environmental assessment, public health applications, and urban comfort analysis. The interdisciplinary nature of his work is evident in collaborations with researchers from diverse fields, producing impactful studies that address complex urban challenges through innovative methodological approaches. His notable scientific achievements include: Annual Teaching Excellence Award (ATEA), 2025 College Educator Award AY2023/2024, 2025 Urban Informatics Paper of the Year Award, 2023 Top 2% scientists worldwide (Stanford University), 2021 Presidential Young Professorship (NUS), 2020 As an educator, Dr. Biljecki has supervised dozens of students leading to publications in leading journals and placements at top universities and organizations. He has delivered talks at over 120 universities and organizations worldwide including MIT, Stanford, Harvard, and ETH Zurich. His research is supported through various grants and affiliations including his role as Principal Investigator at the Future Cities Lab Global at the Singapore-ETH Centre. The NUS Urban Analytics Lab, which he established, brings together scholars from diverse disciplines to drive research on making cities smarter and more data-driven. The lab has developed innovative tools like ZenSVI for street view imagery analysis and has produced influential research on urban digital twins, urban morphology, and GeoAI applications. Through his leadership, the lab continues to pioneer methods that advance data-driven urban planning and smart city development.
Aaron Roth is the Henry Salvatori Professor of Computer and Cognitive Science at the University of Pennsylvania, affiliated with the Department of Computer and Information Science in the School of Engineering and Applied Science. He holds a secondary appointment in the Department of Statistics and Data Science at the Wharton School and is associated with several research centers including PRiML, the Warren Center for Network and Data Sciences, and the AMCS program. He received his PhD from Carnegie Mellon University under Avrim Blum and was a postdoc at Microsoft Research New England. His research focuses on algorithms and machine learning, particularly in private data analysis, fairness in machine learning, game theory, mechanism design, and learning theory. His work bridges theoretical computer science with societal concerns, advocating for ethically aware algorithm design. He co-authored the book The Ethical Algorithm with Michael Kearns, which explores how to embed social values like privacy and fairness into algorithmic systems. His recent publications show a strong trend toward uncertainty quantification, multicalibration, conformal prediction, and fairness in reinforcement learning and high-dimensional settings. He frequently publishes in top-tier venues such as STOC, FOCS, ICML, NeurIPS, and COLT, often with a focus on rigorous theoretical foundations with practical implications. Hans Sigrist Prize Presidential Early Career Award for Scientists and Engineers (PECASE) Alfred P. Sloan Research Fellowship NSF CAREER award Google Faculty Research Award Amazon Research Award Yahoo Academic Career Enhancement award Roth has advised numerous PhD students and postdocs, many of whom now hold academic or industry research positions. He is also an Amazon Scholar at AWS and has served in advisory roles for companies like Apple, Facebook, Leapyear, and Spectrum Labs. He has been active in organizing workshops and tutorials on differential privacy, fairness, and adaptive data analysis, and has given keynotes at major conferences and institutions worldwide. He leads research groups and collaborates widely across Penn, focusing on responsible AI, privacy, and algorithmic fairness. His lab produces foundational work on calibration, unlearning, privacy-preserving learning, and equitable decision-making systems.
