Dr. Qilin Li is a Professor of Civil and Environmental Engineering at Rice University, serving as Co-Director of the NSF Nanosystems Engineering Research Center for Nanotechnology-Enabled Water Treatment (NEWT). She leads research on advanced water treatment technologies, membrane processes, and nanotechnology applications to address global water challenges. Her work focuses on membrane distillation, nanomaterials for disinfection, and sustainable infrastructure solutions. Dr. Li holds a Ph.D. and M.S. from the University of Illinois at Urbana-Champaign and a B.E. from Tsinghua University. Her research group investigates membrane fouling, desalination, and recovery of valuable metals from wastewater. Key projects include nanophotonics-enhanced solar desalination and electrochemical processes for contaminant removal. She has been awarded the CAPEES/Nanova Frontier Research Award and the Roy E. Campbell Faculty Development Award. Dr. Li advises multiple Ph.D. students and postdoctoral researchers, advancing innovative water treatment technologies. Dr. Li’s contributions span academic leadership, industry collaborations (e.g., SolMem LLC), and policy-oriented research to enhance urban water resilience. Her lab develops materials and processes for energy-efficient water reuse, with a focus on sustainable solutions for industrial and municipal systems.
Daniel Lindvall is a Researcher at Uppsala University's Department of Geosciences, affiliated with the Natural Resources and Sustainable Development unit and Climate Leadership initiative. He holds a doctorate in sociology and specializes in democracy-climate policy intersections, with additional expertise in peacebuilding and reconciliation processes in post-conflict regions like Bosnia and Herzegovina. His research focuses on: Democratic governance challenges in climate crisis contexts Public acceptance of renewable energy policies Climate justice and intergenerational equity Political barriers to sustainability transitions Local governance of climate initiatives Lindvall leads multiple research programs including Mistra-Formas funded Fairtrans, Formas' Wicked Problem Governance, and the Swedish EPA's climate-biodiversity policy initiative. His publications consistently examine democratic institutions' capacity to address environmental crises through policy design, public engagement, and institutional innovation.
Roberto Rojas-Cessa is a Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology (NJIT), affiliated with the School of Applied Engineering and Technology. His research focuses on networking, blockchain applications in smart cities, energy systems, wireless communications, and high-performance switching. He has led multiple National Science Foundation (NSF)-funded projects, including initiatives on controlled delivery power grids and next-generation network quality of service. Notably, his work explores blockchain for energy metering, sustainable environmental measures, and smart grid optimization. He is also a Senior Member of the National Academy of Inventors (2024). His research interests span network protocols, distributed systems, and IoT applications. Recent projects include AMI-Chain (a blockchain-based power metering system) and studies on indirect free-space optical communications for vehicular networks. He has contributed to advancements in medium access control for crowded networks and energy packet switches for digital microgrids. Rojas-Cessa’s work integrates machine learning for network management and flood impact analysis. He has developed tools for time-lapse analysis of urban data and agent-based models to evaluate electric vehicle adoption. His publications emphasize scalability, security, and efficiency in both traditional and emerging technologies. Grants: Collaborative Research on Power Grids (NSF, 2016–2018), NeTS-NR: Quality of Service Networks (NSF, 2004–2008) Awards: Senior Member of the National Academy of Inventors (2024) His lab activities include experimental evaluations of digital microgrids and blockchain implementations for carbon footprint tracking. He actively collaborates on projects addressing emergency communications and resilient energy distribution systems.
Dr. Clara Colombatto is an Assistant Professor in the Department of Psychology at the University of Waterloo, where she directs the Vision and Cognition Lab. She holds an honorary lecturer position at University College London and a PhD from Yale University. Her research explores how visual perception extracts social and cognitive states from others, focusing on attentiveness, confidence, and metacognition. She investigates non-biological agents like AI and the perceptual roots of social cognition, including group dynamics and moral judgment. Education: BS in Neuroscience and Philosophy, Duke University PhD in Psychology, Yale University Postdoctoral Research Fellow, University College London Research Interests: Perception of attentiveness and metacognition, social group perception, AI ethics, moral judgment, and visual cognition. Her work bridges cognitive psychology, vision science, and social psychology to understand how humans perceive other minds and interact with non-human agents. Recent Trends in Articles: Recent work emphasizes human-AI collaboration, trust in technology, and perceptual foundations of social interaction. Key themes include gaze dynamics, confidence attribution in AI, and optimal group size perception. Grants & Collaborations: Collaborates with institutions like Princeton University, University of Oxford, and Microsoft Research. Her team includes students working on topics like robot teleoperation and moral narratives. Labs & Teams: Leads the Vision and Cognition Lab at Waterloo, focusing on experimental psychology and computational modeling. Current projects explore metacognition in advice-taking and perceptual grouping in social interactions.
Peter Haas is a Professor at the Manning College of Information and Computer Sciences at the University of Massachusetts Amherst, with an adjunct role in Industrial Engineering. Previously, he spent 30 years as a Principal Research Staff Member at IBM Research and held a consulting professorship in Management Science and Engineering at Stanford University. His research focuses on applying probability and statistics to data management, simulation of complex systems, and machine learning scalability. Education : PhD, Operations Research, Stanford University, 1986 MS, Statistics, Stanford University, 1984 MS, Environmental Engineering, Stanford University, 1979 SB, Engineering and Applied Physics, Harvard University, 1978 Research Interests : Haas’s work spans stochastic systems, probabilistic databases (e.g., MCDB and SimSQL), sampling techniques, and simulation optimization. He pioneered methods for managing uncertain data and scalable machine learning, including compressed linear algebra for declarative systems. His recent focus includes in-database decision support and hybrid simulation metamodeling with neural networks. Key Contributions : He developed the Online Aggregation framework (SIGMOD 1997), which earned a Test-of-Time Award in 2007. His work on matrix factorization and distributed stochastic gradient descent (DSGD) revolutionized large-scale machine learning. He also advanced techniques for estimating distinct-values and correlation discovery in databases. Awards : A six-time recipient of IBM’s Pat Goldberg Memorial Award, he is an ACM and INFORMS Fellow. His honors include the VLDB Best Paper Award (2016), EDBT Best Paper (2018), and recognition in Communications of the ACM. Advising & Grants : He advises four current PhD students and has graduated Matteo Brucato. His IBM career included over 30 patents, including foundational work for DB2’s sampling capabilities and IBM Watson analytics. He leads the DREAM Lab, focusing on data systems for exploration and analytics. Labs/Teams : Directs the Data systems Research for Exploration, Analytics, and Modeling (DREAM) Lab, advancing projects like Splash (health system simulation) and SuDocu (document summarization by example).
Alan A. Stocker is a Professor in the Department of Psychology at the University of Pennsylvania, with affiliations in the Neuroscience Graduate Group, Bioengineering Graduate Group, and Computational Neuroscience Initiative. He leads the Computational Perception and Cognition (CPC) Laboratory, focusing on how prior beliefs and expectations shape sensory perception through Bayesian inference and efficient coding principles.
Saibal Ray is a James McGill Professor of Operations Management and Vice-Dean, Faculty at the Desautels Faculty of Management, McGill University. He holds the Desautels Business Leadership Chair and has served in multiple academic leadership roles, including Vice-Dean, Research and Academic Director of the Bensadoun School of Retail Management. His expertise spans supply chain management, risk management, and retail operations, with a focus on agri-food and natural resources sectors. He has published extensively in top journals like Management Science and Operations Research, and holds editorial roles at journals such as Production and Operations Management. Ray earned a PhD from the University of Waterloo, an MEng from the Asian Institute of Technology, and a BEng from Jadavpur University. His research bridges operations and marketing, addressing challenges like supply chain risk, pricing strategies, and sustainability. He has secured major grants from NSERC, SSHRC, and Quebec agencies, and received awards including the Desautels Faculty Scholar and Quebec Teaching Excellence Award. His teaching focuses on operations and supply chain management at the MBA and graduate levels. Ray’s work integrates academic leadership with practical impact, advising on initiatives like the McGill Center for the Convergence of Health and Economics. His recent research explores behavioral retail tactics, health-conscious bundling, and supply chain resilience in dynamic markets.
Professor Nicholas Hanley holds the Chair in Environmental and One Health Economics at the University of Glasgow's Institute of Biodiversity, Animal Health and Comparative Medicine. He joined in 2017 after previous roles at the Universities of Stirling, Edinburgh, and St Andrews. His research focuses on applying economic methods—including behavioral economics—to biodiversity conservation, One Health challenges, sustainability metrics, and the design of Payment for Ecosystem Services (PES) schemes. He is an Associate Editor of Resource and Energy Economics and Ecological Economics . Current research includes modeling biodiversity net gain policies in the UK, ecological-economic simulations of woodland expansion impacts, and the relationship between natural sounds (e.g., bird song) and mental well-being. He also leads work on coastal resilience, soil carbon markets, and the economic implications of historic pollution. His projects often integrate interdisciplinary approaches, combining ecology, economics, and policy analysis. Key research themes include valuing biodiversity offsets, spatial coordination in conservation auctions, and the economic consequences of land-use changes. His work emphasizes practical policy applications, such as designing effective conservation markets and evaluating trade-offs between environmental and economic objectives. Publications span over 350 articles, with recent work focusing on marine plastic pollution agreements, livestock disease economics in Tanzania, and sediment management in hydropower systems. His research frequently highlights the importance of integrating behavioral insights and spatial analysis into environmental policy design.
Anton Bekkerman is a Professor in the Department of Agriculture, Nutrition, and Food Systems at the University of New Hampshire, serving as Associate Dean for Research and Director of the New Hampshire Agricultural Experiment Station. He holds a Ph.D. and M.S. in Economics from North Carolina State University and a B.B.A. from Loyola University Maryland. His research spans agricultural marketing, price forecasting, policy analysis, and risk management, with specific expertise in: Commodity price dynamics (grain and fertilizer markets) Agricultural insurance and policy design Farm decision-making and risk analysis Spatial economic modeling Recent publications examine quality-based wheat pricing, biofuel policy impacts on fertilizer markets, crop insurance distributions, and economic dimensions of pest management. His work integrates economic theory with empirical analysis of agricultural systems. Dr. Bekkerman leads research initiatives addressing agricultural sustainability and economic resilience in changing climates.
Sara Shafiee is a Senior Researcher at the Department of Civil and Mechanical Engineering , Technical University of Denmark (DTU) . She specializes in product configuration systems, manufacturing engineering, and AI-driven innovation. Her work bridges technical systems with organizational agility, emphasizing sustainability and customer-centric design. External Roles: Founder & CEO of DivERS (Jan 2021–) External Lecturer at Copenhagen Business School (2022–2024) Senior Business Consultant at Haldor Topsoe AS (2017–2019) Research Focus: Her work addresses challenges in product configuration systems, generative AI applications, and sustainable construction. Key themes include: Optimal product design through recommendation systems Agile methodologies in knowledge-intensive development Environmental impact monitoring via configurators Publications Trends (2023–2025): Recent work explores AI-driven manufacturing optimization, consumer-centric innovation strategies, and the integration of environmental monitoring into design systems. High-impact areas include generative AI applications (13K+ downloads) and modular construction configurators. Awards: Agnes & Betzy Award (2025) Nordic Women in Tech Leadership Award (2022) Best Digital Startup (Venture Cup Denmark, 2021) Innovation Fund Denmark Role Model (2018) Advising & Grants: Supervised PhD projects on recommendation systems and configurator design. Lead PI of the RECODE project (DFF Grant DKK 10M+, 2024–2027) focusing on deep learning for engineer-to-order systems. Labs & Teams: Core member of DTU’s Design and Manufacturing Systems group, collaborating with industry partners like Haldor Topsoe and DivERS to develop scalable configurator solutions.
Mondher Feki is an Associate Professor of Management at Université Paris-Saclay, focusing on IS/IT management and digital transformation. His research explores blockchain applications in supply chains, robotic process automation (RPA), robo-advisors, and generative AI. He teaches Management Information Systems and Data Management courses. Currently serving as a reviewer for journals like Business & Information Systems Engineering and conferences like HICSS and ECIS. Active member of the Association Information & Management (AIM). Key research areas include digital transformation strategies, blockchain's operational impact, AI-driven financial advisory systems, and RPA implementation in insurance sectors. His work emphasizes technology adoption challenges and strategic alignment in business contexts. Recent publications analyze blockchain use in French retail logistics, RPA benefits for Allianz France, and IS quality's strategic role in firm performance. Conference contributions address robo-advisors in crowdfunding and pandemic-driven higher education innovation. Maintains active academic service roles in peer review and conference organization.
Xue Han is a Professor of Biomedical Engineering at Boston University (BU), affiliated with the Han Lab. His primary academic appointment is in the Biomedical Engineering department, with additional affiliations in Neuroscience & Neuroengineering, and Photonics & Optical Systems. He holds a PhD in Physiology from the University of Wisconsin-Madison and a B.S. in Biophysics from Beijing University, China. Dr. Han’s research focuses on addressing unmet medical needs in brain disorders by developing novel neuromodulation therapies. His work combines genetic, molecular, pharmacological, optical, and electrical tools to study neural circuit dynamics, with a particular emphasis on optogenetics and optical neural modulation. Key projects include pioneering light-based neuron silencing techniques and pre-clinical testing of neurotechnologies like transcranial ultrasound stimulation. His lab investigates how neural synchrony contributes to cognition and pathology, aiming to link neural activity to behaviors like movement, attention, and decision-making. His recent publications emphasize high-frequency electrical stimulation effects, membrane voltage imaging, and the impact of neuromodulation on brain rhythms. Notable themes include the role of PV neurons in cortical coding, ultrasound-based neuron activation, and the interplay between neural oscillations and disease states. While no formal awards are listed, his prolific output highlights contributions to neurotechnology and systems neuroscience. Dr. Han’s lab develops advanced imaging tools like targeted-illumination confocal microscopy (TICO) and collaborates on projects involving exosome-mediated therapies and brain-computer interfaces. Ongoing work explores translational applications of neurophotonic tools and the mechanistic basis of neuromodulation therapies for disorders like Parkinson’s and epilepsy.
Professor TAN Ah Hwee is a Full-time Faculty member and Lee Kong Chian Professor of Computer Science at the School of Computing and Information Systems (SCIS) at Singapore Management University (SMU). He serves as the Associate Dean (Research) in SCIS and leads research in Artificial Intelligence, Machine Learning, and Health Informatics. His work spans neural networks, multi-agent systems, and healthcare applications such as Mild Cognitive Impairment prediction. He holds a PhD from Boston University (1994). Research Focus: His research integrates adaptive resonance theory, federated learning, and spatial-temporal modeling. Key areas include knowledge graph refinement, episodic memory systems for Activity of Daily Living (ADL) prediction, and explainable AI in multi-agent reinforcement learning. He also develops technologies for aging-in-place support and social media analytics. Recent Contributions: Recent work emphasizes hierarchical multi-agent models (HiSOMA), federated learning frameworks (FedART), and AI-driven health monitoring systems. His publications address challenges in self-organizing neural networks, context-aware reinforcement learning, and medical diagnostics through ambient sensing. Advising & Impact: Advises students like TEH Seng Khoon and Cassandra TAN Hui Ming. His projects include the eHealthPortal for elderly support and Silver Assistants for aging-in-place solutions. Research outputs bridge theoretical advancements in AI with real-world applications in healthcare and smart environments.
Janarthanan Rajendran is an Assistant Professor and the Sexton Chair in Reinforcement Learning at the Faculty of Computer Science, Dalhousie University, in Halifax, Nova Scotia, Canada. He is actively involved in research, teaching, and mentoring, with a focus on deep reinforcement learning and its applications in complex, dynamic environments. Education: Postdoctoral Fellow, Mila Quebec AI Institute and University of Montreal, Canada (2023) PhD in Computer Science and Engineering (AI stream), University of Michigan, Ann Arbor, USA (2021) MTech and BTech in Electrical Engineering, Indian Institute of Technology Madras, India (2016) His research focuses on enabling machines to learn through interaction, with core interests in deep reinforcement learning, model-based RL, multi-agent systems, transfer learning, and applications in materials science and economics. He also explores the integration of large language models and foundation models into reinforcement learning frameworks. His work emphasizes adaptivity, lifelong learning, and societal implications of AI. The most recent publications show a strong trend in advancing cooperative multi-agent systems, developing adaptive and memory-efficient RL methods, and applying RL to real-world challenges such as crystal design and dynamic pricing. His research bridges theoretical innovation with practical application, often in interdisciplinary contexts. Scientific Awards: Sexton Chair in Reinforcement Learning Dr. Rajendran is actively involved in mentoring graduate students and fostering an inclusive research environment. He is currently recruiting PhD and MCS students at Dalhousie University. He has no formal grants listed in the text, but his research chair and active publication record suggest strong funding support. He is also engaged in the broader AI community, having organized and participated in major conferences such as the Atlantic Canada AI Summit and NeurIPS. Labs and Research Groups: He leads a research group focused on deep reinforcement learning at Dalhousie University, working on topics including model-based RL, off-policy learning, and leveraging external knowledge sources. The group emphasizes inclusivity and supports underrepresented groups in computer science research.
Matthias Bernt is Deputy Director and head of the research focus 'Politics and Planning' at the Leibniz Institute for Research on Society and Space (IRS), and an adjunct lecturer at the Institute for Social Sciences, Humboldt University of Berlin. He has held academic and research positions since the early 2000s and has led numerous national and international research projects on urban development, housing, and governance. Studied political science at Freie Universität Berlin Doctorate (2001) on Berlin’s urban renewal policy Habilitation (2021) on gentrification and public policies Research associate at Helmholtz Centre for Environmental Research (2001–2008) Research associate at IRS since 2008 Held teaching positions since 1998 Visiting positions at Columbia University, UCL, European University of St. Petersburg Matthias Bernt's research centers on urban governance, particularly in the context of post-socialist transformation. His work critically examines gentrification, housing financialization, shrinking cities, and migration in urban planning. He has a strong focus on East German large housing estates, exploring their transformation under marketization, state restructuring, and immigration. His concept of the 'commodification gap' offers an institutionalist critique of traditional gentrification theories. His recent work highlights segregation dynamics, the role of institutional investors, and the governance challenges in peripheral urban areas. The 15 most recent publications reflect a consistent focus on urban inequality, governance, and post-socialist urban development. Key themes include gentrification in Berlin, London, and St. Petersburg; financialization of housing; migration and integration in shrinking cities; and comparative analyses of large housing estates. His work increasingly engages with policy implications, as seen in studies on rent control, housing socialization, and urban regeneration. Feodor Lynen Stipendium für erfahrene WissenschaftlerInnen Book Review Editor, International Journal of Urban and Regional Research (2014–2021) Board Member, Research Committee 21 (Urban and Regional Development), International Sociological Association Deputy Speaker, Urban and Regional Sociology Section, German Sociological Association Member, Berlin Tenants’ Association, Fachbeirat Wohnraumversorgung Berlin, and other policy-relevant bodies Matthias Bernt has advised or collaborated on multiple research projects, including StadtumMig, HoPoFin, and Estates After Transition. He has not received major external grants listed in the text, but leads significant publicly funded research. He is actively involved in academic discourse through editorial roles and professional associations. His work bridges academic research and urban policy, particularly in Berlin and East Germany. He is involved in several research teams and projects at IRS, including lead and bridge projects on 'Conflicts in Planning' and 'Disruption and Spatial Development.' He coordinates interdisciplinary teams focusing on governance, migration, and housing. His work is highly collaborative, involving researchers from Germany, the UK, Poland, Russia, and beyond.
