Dr. Heesung Woo is an Assistant Professor of Advanced Forestry at the College of Forestry, Oregon State University , specializing in robotics, sensor integration, and precision forestry. His work focuses on autonomous forestry machinery, AI-driven forest management, and sustainable practices. He advises two graduate students and collaborates internationally through research projects. Research Interests: Autonomous Forest Machinery Development Sensor Integration & ICT Solutions Precision Forestry via Remote Sensing/LiDAR/GIS Machine Learning for Forest Inventory Advanced Forestry Practices for Sustainability Publications emphasize innovative applications of technology in forestry, including LIDAR integration, harvester data analytics, and carbon offset project modeling. His work bridges engineering, environmental science, and policy. Dr. Woo leads the Advanced Forestry Lab at Oregon State, focusing on real-world deployment of cutting-edge technologies to address challenges in forest operations, sustainability, and resource optimization.
Kenneth M. Roberts is the Richard J. Schwartz Professor of Government at Cornell University, affiliated with the College of Arts and Sciences. He specializes in comparative democracy, Latin American political economy, and the intersection of populism, social movements, and inequality. Roberts holds leadership roles including former Senior Associate Dean for the Social Sciences and directorships in Cornell’s Latin American and Caribbean Studies program and the Institute for the Social Sciences. Roberts earned his Ph.D. in comparative and Latin American politics from Stanford University. His research focuses on democratic resilience, polarization, and crises of democracy globally, with a regional emphasis on Latin America. Notable works include Democratic Resilience: Can the United States Withstand Rising Polarization? (Cambridge 2021) and Changing Course in Latin America: Party Systems in the Neoliberal Era (Cambridge 2014). His academic engagements include visiting fellowships at institutions like the Institute for Advanced Study (Princeton) and the Scuola Normale Superiore (Florence). Roberts contributes actively to global democracy initiatives through the American Democracy Collaborative, analyzing threats to democratic institutions in the U.S. and beyond.
Luigi Acerbi is an Associate Professor in the Department of Computer Science at the University of Helsinki, where he leads the Machine and Human Intelligence research group. He is also an active member of the Finnish Center for Artificial Intelligence (FCAI) and ELLIS (European Laboratory for Learning and Intelligent Systems). His research focuses on probabilistic machine learning and computational neuroscience, particularly on developing efficient methods for statistical inference, Bayesian models of perception, and resource-constrained rationality. His work bridges machine learning and cognitive science, with applications in Bayesian optimization, simulation-based inference, and image completion. The recent publications highlight a strong trend toward unifying probabilistic conditioning across diverse tasks using transformer-based meta-learning frameworks like the Amortized Conditioning Engine (ACE). These works emphasize amortized inference, flexible latent variable modeling, and the integration of prior knowledge at runtime, enabling efficient and scalable Bayesian methods for complex problems. Scientific Affiliations: University of Helsinki, Department of Computer Science Finnish Center for Artificial Intelligence (FCAI) ELLIS (European Laboratory for Learning and Intelligent Systems) Education: PhD in Computational Neuroscience, Doctoral Training Centre, Edinburgh, UK Advisor: Sethu Vijayakumar and Daniel Wolpert Visiting work at Computational and Biological Learning Lab, Cambridge Postdoctoral Experience: Alex Pouget’s lab, University of Geneva, Switzerland Wei Ji Ma, New York University, USA Collaboration with the International Brain Laboratory Luigi Acerbi mentors PhD students including Daolang Huang and Nasrulloh Loka, and collaborates widely with researchers such as Samuel Kaski. He has contributed to open-source tools like PyVBMC and is involved in community initiatives such as the EurIPS conference. His work is supported by grants from the Research Council of Finland, Business Finland, and the UKRI Turing AI World-Leading Researcher Fellowship. He leads a research lab focused on amortized probabilistic inference, with ongoing projects including PriorGuide and Stacked VBMC, aiming to make Bayesian methods more practical and accessible for real-world scientific and engineering applications.
Professor Tavis Potts is a Personal Chair in Sustainable Development and Environmental Governance at the University of Aberdeen, affiliated with the Department of Geography and Environment within the School of Geosciences. He is actively engaged in research on just transitions, environmental justice, marine governance, and participatory planning. His research focuses on: Understanding just transitions and the social dimensions of climate and energy Marine resource governance and planning Participatory and community-based approaches to managing natural capital The political economy of environmental policy The blue economy and net zero transitions His recent publications highlight a strong trend toward policy-relevant research on just transitions, stakeholder engagement, and environmental governance. Articles and reports examine climate assemblies, community participation in net zero planning, nuclear decommissioning, and measuring equitable outcomes in transition processes. His work integrates social science perspectives with environmental policy, emphasizing democratic participation and equity. Key scientific contributions include commissioned reports for the Just Transition Commission and the Nuclear Decommissioning Authority, as well as peer-reviewed articles in journals such as Environmental Science & Policy and Marine Policy . He has led and contributed to projects funded by Interreg EU, NERC, British Council, and the World Bank. Professor Potts advises research students and leads the Just Transition Lab at Aberdeen. He holds external advisory roles with Aberdeen City Council’s Net Zero Delivery Unit and Aberdeenshire Council’s Climate Ready Aberdeenshire Board, demonstrating active engagement with policy and practice. He is affiliated with key research centers including the Centre for Marine and Coastal Zone Management and the Just Transition Lab, where he advances interdisciplinary work on sustainable futures and equitable environmental governance.
Sanjeev Dewan is a Professor of Information Systems and Associate Dean of Masters Programs at the Paul Merage School of Business, University of California, Irvine. He also serves as Faculty Director of the Master of Science in Business Analytics program. Prior to joining UCI in 2001, he held faculty positions at the University of Washington and George Mason University. PhD, University of Rochester MS, University of Rochester Bachelor of Technology, Indian Institute of Technology, Delhi His research focuses on the economics of digital platforms , social and mobile analytics , and the valuation of technology investments . He investigates how information technology creates business value, impacts consumer behavior, and influences firm performance. His work spans electronic markets, Web 2.0 technologies, IT productivity, and the digital divide. The most recent publications reveal a strong emphasis on empirical analysis of digital platforms , including studies on gender bias in open source communities, quality certification in the sharing economy (e.g., Airbnb), personalized ranking in app stores, and mobile health applications. His research frequently uses large-scale datasets to examine behavioral patterns, market dynamics, and the economic implications of IT innovations. Faculty Service Award for 2023-24, UCI Paul Merage School of Business Best Paper Award, INFORMS 2019 e-Business Cluster Faculty Service Award for 2016-17, UCI Paul Merage School of Business Best Paper Award, INFORMS Conference on Information Systems and Technology (2009) INFORMS Service Award (2009) INFORMS Certificate of Appreciation (2008) Beta Gamma Sigma Honor Society (1991) University of Rochester Fellowship (1985–1990) Sanjeev Dewan has advised numerous PhD students who have secured faculty positions at leading institutions such as the University of Wisconsin-Madison, HKUST, Penn State, and the University of Hong Kong. His editorial service includes senior editor roles at Information Systems Research and associate editor at Management Science . He has also chaired tracks at ICIS and served as program co-chair for PACIS. There is no indication of external grant funding in the provided text, but his sustained publication record and leadership roles suggest significant research activity and institutional support. He is actively involved in academic leadership and research dissemination, contributing to major conferences and editorial boards. His work bridges theory and practice, particularly in digital platform ecosystems and analytics-driven decision-making.
Dr. Emily Cuming is a Senior Lecturer in the Humanities and Social Science school at Liverpool John Moores University , specializing in British literature, culture, and social history from the 19th century to the present. Her research focuses on maritime relations, working-class girlhood, life writing, and representations of domestic spaces including council estates, slums, and bedsits. PhD, MA, BA in English & Russian from University of Manchester (2006, 2002, 2001) Editor of Key Words: A Journal of Cultural Materialism Co-leader of the Home and Domestic Cultures research network Committee member of the Research Institute for Literature and Cultural History Board member of the Centre for Port and Maritime History Her research combines literary analysis with historical and cultural studies, emphasizing material culture, port cities, and marginalized voices. Recent publications include Maritime Relations: Life, Labour and Literature at the Water’s Edge, 1830-1914 (Cambridge University Press, forthcoming 2025) and Housing, Class and Gender in Modern British Writing, 1880-2012 (CUP, 2016). She has received multiple research grants including AHRC Connected Communities funding and Liverpool John Moores University QR awards. Dr. Cuming teaches undergraduate modules on Life Stories , Representing Domestic Space , and Waterscapes , as well as MA courses on Place: Imagining Place in Modern Times . She supervises three PhD projects and welcomes new supervisees in her research areas. 2025: Enhancing Research Cultures funding for 'The Sinking of the Lancastria' 2024: Editorial board member of Journal of Victorian Culture 2023: NCCPE Engage Prize for 'Around the Toilet' project 2022: Caird Short-term Research Fellowship 2016: NCCPE Engage Prize winner
Keming Yu is a Professor and Chair in Statistics at the Department of Mathematics, Brunel University London, within the College of Engineering, Design and Physical Sciences. He is also the Impact Champion for REF in Mathematical Sciences. He joined Brunel in 2005 after holding positions at the University of Plymouth, Lancaster University, and The Open University. He earned his PhD from The Open University and earlier degrees in Mathematics and Statistics from Chinese institutions. PhD in Statistics – The Open University, UK MSc in Statistics – China BSc in Mathematics – China His research centers on quantile regression, Bayesian modeling, survival analysis, and statistical methods for big data . His work spans applications in health, finance, environment, and social sciences. He has made significant contributions to robust and flexible regression methods, including expectile, mode, and censored quantile regression. His recent publications (2023–2025) show a strong focus on streaming data, spatiotemporal modeling, high-dimensional data, and Bayesian methods . He frequently publishes in top-tier journals such as the Journal of the Royal Statistical Society Series A, B, and C , Statistica Sinica , and Computational Statistics and Data Analysis . His work often involves collaboration with international researchers, especially in China and Europe. He has contributed to methodological discussions in leading statistical journals, demonstrating active engagement with the academic community. His work on financial risk, environmental statistics, and health data analysis reflects interdisciplinary impact. Reviewed and contributed to discussions on safe testing, confidence sequences, and betting-based inference. Active in developing methods for nonignorable missing data, censored models, and functional covariates. He supervises PhD students and is involved in teaching and curriculum development, including as Course Director for the MSc Statistics with Data Analytics. His research is supported by extensive publication output and academic service. He leads or contributes to research on Bayesian models, robust regression, and scalable methods for big data , often involving collaborations in interdisciplinary teams. His lab or research group focuses on statistical methodology development with real-world applications.
Amir Rahmati is an Assistant Professor in the Department of Computer Science at Stony Brook University , where he directs the Ethos Security and Privacy Lab and contributes to the Stony Brook National Security Institute . His research focuses on system security , with specific emphasis on the security and privacy challenges of emerging technologies such as IoT , AR , and ML systems . Teaching: Instructor of SBU102: Computer Security (Spring 2025) Collaborations: Frequent collaborations with institutions like University of Michigan, University of Toronto, and IEEE/USENIX conferences. Rahmati’s research addresses security vulnerabilities in resource-constrained devices and real-world ML applications. His work includes adversarial robustness in neural networks, attack synthesis on medical devices, and privacy-preserving frameworks for IoT ecosystems. Trends in his publications reveal a focus on practical system design to mitigate security threats in cyber-physical systems , augmented reality , and blockchain technologies . Prospective students: Rahmati seeks researchers with expertise in hardware/software, machine learning, network protocols, and security to tackle system-stack challenges in his lab.
Dr. Antal Jarai is a Senior Lecturer in the Department of Mathematical Sciences at the University of Bath, where he also contributes to the EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa) and the Probability Laboratory at Bath. His work bridges probability theory and statistical physics, focusing on random processes with spatial and/or temporal structure. PhD in Mathematics from Cornell University (2000) BSc from Eötvös Loránd University (1996) Dr. Jarai's research explores problems motivated by statistical physics, including percolation, random walks, branching random walks, uniform spanning trees, and Abelian sandpiles. His recent publications address interlacement limits, asymptotics of optimal policies, resistance scaling, and wireless network proximity. He actively collaborates on interdisciplinary projects in network mathematics and wireless technology. Key trends in his publications include asymptotic analysis (5/5 papers), random walk theory (4/5), and probabilistic methods in statistical physics (4/5). Subfields span interlacement theory, self-organized criticality, stochastic geometry, and disordered systems. Royal Society Grant for 'Zero Dissipation Limit in Abelian Sandpiles' London Mathematical Society Grant for 'Critical Exponents in Sandpiles via Exact Sampling' EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa) Dr. Jarai serves as Principal Investigator on multiple research grants and supervises students in probability and applied mathematics. He has contributed datasets on sandpile simulations and collaborates internationally on network mathematics projects.
Seth Blumsack is a Professor at the Pennsylvania State University in the Department of Energy and Mineral Engineering and serves as Director of the Center for Energy Law and Policy . He holds an Adjunct Research Professor position at the Carnegie Mellon Electricity Industry Center and is affiliated with the Santa Fe Institute as an External Faculty member. His research spans energy economics , power grid reliability , and complex infrastructure networks . Key projects include: Interdependent natural gas and electricity systems analysis Governance of regional transmission organizations Smart grid consumer behavior studies Power grid reliability tools development He has secured funding from the U.S. National Science Foundation , Department of Energy , Environmental Protection Agency , and private industry. His Best paper award at Hawai’i International Conference on System Sciences (2011) and John T. Ryan, Jr. Fellowship (2011-17) highlight his scientific recognition. Publications emphasize electricity market deregulation , energy infrastructure resilience , and consumer response to smart grid technologies . His work has been cited in major media outlets like The New York Times and The Los Angeles Times , and he has consulted for National Renewable Energy Laboratory , U.S. Department of Energy , and other industry stakeholders.
Eduardo Velloso is a Professor of Computer Science at the University of Sydney , focusing on interaction design for emerging technologies . His work explores novel user experiences through input modalities, interaction devices, and AI/ML integration in systems. Education: PhD in Computer Science (Lancaster University, UK), Bachelor in Computer Engineering (Pontifical Catholic University of Rio de Janeiro, Brazil) Research Interests: Interdisciplinary work combining Human-Computer Interaction , Augmented/Virtual Reality , Eye Tracking , Wearable Computing , and Machine Learning . Publication Trends: Recent work addresses methodology in HCI , AR/VR applications , AI integration , and sensor-based interaction . Scientific Awards: Best Paper Award at CHI Best Paper Award at UIST Best Paper Award at TOCHI Best Paper Award at TEI Supervision: Actively supervises PhD students and collaborates with companies/government on projects like VR training systems and AI mediation tools . Labs/Teams: Affiliated with institutions in Australia (University of Sydney) and Brazil (PUC-Rio), with global co-authors in projects involving mixed reality , wearables , and AI ethics .
Daniel B. Neill is a Professor of Computer Science, Public Service, and Urban Analytics at New York University (NYU), jointly appointed across the Courant Institute of Mathematical Sciences, Robert F. Wagner Graduate School of Public Service, and the Center for Urban Science and Progress (Tandon School of Engineering). He also serves as the Director of the Machine Learning for Good Laboratory (ML4G) and is affiliated with NYU's Center for Data Science and Tandon Department of Computer Science and Engineering. Education: Ph.D. in Computer Science, Carnegie Mellon University M.S. in Computer Science, Carnegie Mellon University M.Phil. in Computer Speech, Cambridge University Research Interests: Dr. Neill's research focuses on developing novel machine learning methods for social good, with applications in disease surveillance (e.g., early outbreak detection), healthcare (e.g., anomalous care patterns), and urban analytics (e.g., predicting citizen needs). He also explores algorithmic fairness , causal inference , and pre-syndromic surveillance using unstructured data. His work bridges theoretical machine learning with real-world policy challenges, collaborating with health departments, hospitals, and city governments to deploy data-driven tools that enhance public health, safety, and security. Scientific Awards & Honors: NSF CAREER Award NSF Graduate Research Fellowship IEEE Intelligent Systems' "Top Ten AI Researchers to Watch" Yelp Dataset Challenge Winner Hidden Signals Challenge Runner-Up (DHS) Grants & Funding: He has received significant funding from the National Science Foundation (NSF), including grants on fairness in AI (IIS-2040898), bias in urban analytics (IIS-1926470), and others. He also acknowledges support from UPMC, MacArthur Foundation, and Richard King Mellon Foundation. Laboratory & Leadership: He directs the Machine Learning for Good Laboratory (ML4G) at NYU, focusing on AI for social impact. He previously co-directed NYU's Urban Initiative (2019-2022) and led the Event and Pattern Detection Laboratory at Carnegie Mellon University.
Sharryn M. Kasmir serves as Professor of Anthropology at Hofstra University, where she conducts critical research on labor, capitalism, and working-class communities through ethnographic fieldwork in Spain's Basque region and the U.S. South. Her institutional affiliation centers within the Department of Anthropology, though the specific school/college structure isn't explicitly stated in available materials. Her academic credentials include: PhD from CUNY Graduate School and University Center MPhil from CUNY Hunter College BA from University of Massachusetts Amherst Professor Kasmir's research program critically interrogates Global Capitalism's impact on working-class lives, with specialized focus on Labor and Working Classes, Nationalist Movements and Identity, and Popular Culture across Western Europe and North America. Her fieldwork at Mondragon's worker cooperatives challenged idealized narratives through working-class perspectives, while her Saturn factory research exposed how auto workers navigate perpetual plant closure threats and economic insecurity. As co-editor of the seminal volume Blood and Fire: Toward a Global Anthropology of Labor , she established foundational frameworks for contemporary labor anthropology that bridge ethnographic detail with macro-political economic analysis. Her publication trajectory since the 1990s reveals persistent engagement with labor anthropology's core questions: analyzing worker cooperatives as contested sites within global capitalism (1996-2016), documenting working-class dispossession amid industrial restructuring (2008-2016), and developing theoretical tools like 'unevenness' for cross-cultural labor studies (2016). This body of work consistently synthesizes cultural anthropology, political economy, and critical theory to center workers' lived experiences within broader capitalist transformations. Available documentation contains no references to scientific awards, research grants, student advising activities, laboratory facilities, or collaborative research teams.
Mark Crowley is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo , with a cross-appointment in the Cheriton School of Computer Science . He is actively involved in the Waterloo Artificial Intelligence Institute (WAII) , the Waterloo Institute for Complexity and Innovation (WICI) , and serves as National Secretary for the Canadian Artificial Intelligence Association (CAIAC) , coordinating the Canadian Conference on AI . Research interests span the theoretical and applied aspects of Reinforcement Learning , Deep Learning , Manifold Learning , and Ensemble Methods . His work addresses challenges in domains with spatial dynamics, multi-agent systems, and uncertainty, particularly in Computational Sustainability (forest fire management, sustainable forestry), Autonomous Driving , Medical Imaging , and Material Design . Recent research focuses on integrating causal modeling with generative representation learning to improve out-of-distribution robustness in motion forecasting applications. Key publications include foundational work on ChemGymRL environments for safe chemical process reinforcement learning, Generative Causal Representation Learning for robust forecasting, and collaborative work on multi-advisor reinforcement learning in multi-agent settings. He co-authored a textbook Elements of Dimensionality Reduction and Manifold Learning (Springer, 2023) with Prof. Ali Ghodsi and Prof. Fakhri Karray. Teaching includes graduate and undergraduate courses in Algorithm Design , Computational Intelligence , Reinforcement Learning , and Data Modeling at the University of Waterloo since 2018. His research group has produced several notable graduates including Benyamin Ghojogh (2021), who continued as a postdoc until 2022.
Toni Rantanen is a Doctoral Researcher at Aalto University in the College of Built Environment. His work focuses on integrating geospatial data with game engine technologies for advanced 3D visualization and analysis of urban environments. Specializes in digital twin applications Active in urban sustainability research Collaborates with the MeMo research group Research Interests Geospatial Data Integration : Developing frameworks for open data standards in urban digital twins 3D Visualization : Creating immersive virtual environments for watershed analysis and lighting simulations Environmental Analysis : Using game engines for change detection and urban park evaluation Interactive Mapping : Designing user-friendly geospatial tools Reality Modeling : Capturing built environment changes through multitemporal data Recent publications demonstrate expertise in urban digital twin development , 3D geovisualization , and game engine applications for environmental research. Collaborative work spans multiple disciplines including urban planning , GIS technology , and virtual reality evaluation .
