Jee Eun (Jamie) Kang is an Associate Professor in the Department of Industrial and Systems Engineering at the University at Buffalo's School of Engineering and Applied Sciences. Research focuses on transportation modeling and applied operations research, with applications in urban mobility, shared autonomous vehicles, and sustainable transportation systems. Education includes a PhD from UC Irvine. Research emphasizes data-driven approaches to travel behavior, electric vehicle adoption, and humanitarian logistics. Publications consistently address mobility innovation, including pricing strategies for emerging services, predictive analytics for transit, and optimization of shared transportation systems.
Prof. Dr. Helen Engemann is a Junior Professor at the Department of English, School of Humanities, University of Mannheim. Her research focuses on multilingualism, language acquisition, and cognitive aspects of bilingualism. She is affiliated with the Research Team JP Multilingualism and is a member of the Deutsche Gesellschaft für Sprachwissenschaft (DGfS), European Second Language Association (EUROSLA), and International Association for the Study of Child Language (IASCL). Her work investigates how language structures influence cognitive processes, particularly in bilingual children and heritage speakers. Key topics include motion event constructions, crosslinguistic influence, and syntactic packaging in multilingual environments. Recent studies explore language change mechanisms in Italian heritage speakers and the impact of typological factors on memory and event encoding. Publications span prestigious journals like Linguistic Approaches to Bilingualism , Journal of Child Language , and Bilingualism: Language and Cognition . Her research bridges linguistics, psychology, and education, addressing both theoretical and applied questions in multilingual development.
Gita Reese Sukthankar is a Professor in the Department of Computer Science at the University of Central Florida (UCF) , where she directs the Intelligent Agents Lab . Her research focuses on activity and plan recognition , with applications in multi-agent systems, robotics, and human-robot interaction. She earned her Ph.D. from the Robotics Institute at Carnegie Mellon University and joined UCF in fall 2007. Research Interests: Her work spans activity recognition , intent inference , multi-agent coordination , and human-robot teams . She has applied these techniques to domains such as adversarial games (e.g., military simulations, Unreal Tournament), assistive technologies, and cooperative robotics. Her research integrates AI, machine learning, and probabilistic models to understand and predict complex team behaviors. Publication Trends: Her publications emphasize spatio-temporal modeling , probabilistic graphical models (e.g., HMMs, CRFs) , and multi-agent plan recognition . She frequently publishes in top venues like AAMAS, AAAI, and ICRA, with a focus on robust recognition of team behaviors, transfer learning, and real-world AI applications. Scientific Awards: NSF CAREER Award (2009) AFOSR Young Investigator (2009) ONR Summer Faculty Fellow (2008) UCF Faculty Excellence for Doctoral Mentoring (2012) CECS Dean's Research Professorship (2013) AAAI Senior Member (2021) ACM and IEEE Senior Member Advising and Grants: She mentors graduate students in AI and robotics and has led research funded by DARPA, AFOSR, and ONR. Her lab develops systems for intelligent agents that can understand and collaborate with humans. She has served on numerous program committees and editorial boards, including ACM Transactions on Autonomous and Adaptive Systems . She teaches courses such as Intelligent Systems , Robotics , and Machine Learning , and has been recognized for both research and teaching excellence. Labs and Teams: She leads the Intelligent Agents Lab at UCF, which focuses on data-driven social informatics and AI for human-agent teams. Her group collaborates with researchers in robotics, computer vision, and cognitive science to build adaptive, intelligent systems.
Dr. Frank Meyer is a researcher at the Leibniz Institute for Regional Geography (IfL) since April 2024, focusing on Geographies of Belonging and Difference within the Theory, Methodology, and History of Geography department. His career includes roles as a research associate at TU Dresden (2019–2024) and the Leibniz Institute for Regional Geography (2010–2019), alongside teaching at Leipzig University and Humboldt University Berlin. He holds a PhD from the University of Leipzig (2019) on subjective perceptions of territorial regulatory withdrawal in rural regions. Meyer specializes in qualitative social geography, global health geographies, and migration studies. Key research areas include transnational organ transplantation systems, regionalist movements, and socio-spatial stigmatization. He co-leads the 'Umbrüche und Transformationen' Leibniz Lab and contributes to the EEGA Science Campus. His work emphasizes innovative methods like improvisational theater for regional identity studies and qualitative visualization techniques. Recent projects include analyzing fiscal demands of regionalist parties and geopolitical impacts on healthcare systems in post-Dayton Bosnia. Meyer's publications span peer-reviewed journals (Geographische Zeitschrift, Erdkunde), edited volumes, and methodological guides for qualitative research. He co-edited 'Ins Feld und zurück' (2018) and organized the IMAJINE research project. His research bridges theoretical contributions (e.g., postsecularism) with applied studies on rural depopulation and transnational medical practices.
Noel Cressie is a Distinguished Professor of Statistics at the University of Wollongong (UOW), Australia, affiliated with the School of Mathematics and Applied Statistics and the National Institute for Applied Statistics Research Australia (NIASRA). He is also the Director of the Centre for Environmental Informatics (CEI). His academic journey includes a PhD from Princeton University (1975) and a B.Sc. with First Class Honours from the University of Western Australia (1972). His research focuses on spatial and spatio-temporal statistics, Bayesian methods, environmental informatics, and applications in climate science. Notable projects include work on atmospheric CO2 flux inversion (WOMBAT framework), Antarctic environmental research (SAEF initiative), and statistical remote sensing for NASA. He has secured over $20 million in research funding and authored four influential books, including Statistics for Spatial Data . Cressie has received prestigious awards such as the COPSS R.A. Fisher Award (2009), Pitman Medal (2014), and Fellowship of the Australian Academy of Science (2018). He leads interdisciplinary teams addressing global challenges like carbon cycle dynamics and biodiversity modeling. His contributions to statistical methodology and environmental science have been recognized through international collaborations and advisory roles.
Renaud Lambiotte is Professor of Networks and Nonlinear Systems at the Mathematical Institute, University of Oxford. He holds a PhD in Physics from Université libre de Bruxelles and has held research and faculty positions at ENS Lyon, Université de Liège, UCLouvain, Imperial College London, and the University of Namur. He is currently an active academic in applied mathematics and network science. His research focuses on complex systems, particularly dynamics on networks, temporal networks, and stochastic processes. He applies these to social and brain networks, data mining, and urban systems. His work bridges theoretical modeling and real-world data, emphasizing the structure and evolution of complex systems. His recent publications demonstrate strong trends in network theory, including hypergraphs, community detection, multidimensional dynamics, and data quality in network interventions. He also explores applications in urban air quality and gentrification, showing a commitment to socially relevant complex systems research. Scientific Awards: Prix Wernaers 2013 Prix Wernaers 2016 Prix Wernaers 2020 Verdickt-Rijdams 2016 de l'Académie royale de langue et de littérature françaises He is the co-founder of L’Arbre de Diane, a publishing initiative at the science-literature interface, which received multiple awards. He teaches advanced courses such as Differential Equations II and Networks. He is affiliated with the Machine Learning and Data Science and the Oxford Centre for Industrial and Applied Mathematics research groups. He has authored or co-edited key texts in the field, including A Guide to Temporal Networks and Modularity and Dynamics on Complex Networks , and has published around 130 peer-reviewed articles. His research is supported by ongoing collaborations and active publication output, indicating sustained academic leadership.
Erika Cudworth is an Associate Professor in Education at De Montfort University, affiliated with the School of Applied Social Sciences . Her academic journey began with a PhD in Sociology from the University of Leeds, followed by an MSc in Political Sociology from LSE and a BSoc.Sc. in Political Science from the University of Birmingham. She previously served as a Professor at the University of East London. Research Expertise : Human/Animal Studies, Posthumanism, Gender, Intersectionality, Critical Animal Studies, Environmental Sociology Erika’s research explores the intersection of posthumanism , gender , and environmental justice , focusing on domestic violence and animal abuse , multispecies ethnography , and critical pedagogy . Her recent publications analyze companion animals , zoonotic politics , and eco-pedagogy , integrating feminist , new materialist , and complex systems frameworks. Her 15 most recent publications span sociology , international relations , and critical animal studies , with a focus on domestic violence , companion species , and posthumanist theory . She actively collaborates with institutions in Canada, Sweden, and the UK on projects like Animalizing Sociology and Home Schooling in multispecies contexts. Erika supervises PhD students Jana Canavan , Tasnina Karim , and Meera Naran at DMU, and external students at the University of Guelph and Lund. She serves on the Academic Consultative Committee of the Vegan Society and reviews for journals like Animals , Security Dialogue , and The Sociological Review .
Anders Rønn-Nielsen is an Associate Professor at the Department of Finance and Center Coordinator at the Center for Statistics at Copenhagen Business School (CBS). He holds a M.Sc. in Statistics from University of Copenhagen and a PhD in Statistics and Probability Theory from Aarhus University. His research focuses on applied probability theory, particularly Lévy-based spatial models, and statistical efficiency analysis. His academic credentials include: M.Sc. in Statistics, University of Copenhagen PhD in Statistics and Probability Theory, Aarhus University Research interests span: Lévy processes and spatial stochastic modeling Extreme value theory applications in finance and natural sciences Nonparametric production frontier analysis Efficiency measurement methodologies His publications (18+ articles) emphasize theoretical probability and statistical applications in efficiency analysis. He has served as external examiner at Aarhus University and Copenhagen University for master’s and PhD examinations (2017–2019). His teaching responsibilities include advanced probability theory courses and statistical methods training for economics students.
Professor Andy Tolmie is Chair of Psychology and Human Development at University College London's Institute of Education (IOE). He leads the Centre for Educational Neuroscience, a tri-institutional partnership with Birkbeck and UCL's Institute of Cognitive Neuroscience. His roles include Deputy Director of this Centre and Programme Leader for the Educational Neuroscience MSc. He also oversees the Bloomsbury and UCL ESRC Doctoral Training Centres, instrumental in social science doctoral training across multiple universities. His research focuses on cognitive development, particularly in science learning, executive function, and child pedestrian safety. Key projects include the EEF/Wellcome Trust initiative on executive function in STEM education and interventions to improve group work efficacy in primary classrooms. He has developed behavioral training programs for child pedestrians adopted nationwide. Dr. Tolmie's academic leadership spans editorship of the British Journal of Educational Psychology and roles in the British Psychological Society. His work bridges developmental psychology with educational practice, emphasizing evidence-based strategies for teaching science and fostering critical thinking skills.
Jure Leskovec is a Professor of Computer Science at Stanford University, affiliated with the Stanford AI Lab, Machine Learning Group, and the Center for Research on Foundation Models. He holds academic appointments in the Department of Computer Science and is a member of Bio-X, the Institute for Human-Centered Artificial Intelligence (HAI), and the Wu Tsai Neurosciences Institute. Leskovec earned his BSc from the University of Ljubljana (2004), PhD from Carnegie Mellon University (2008), and postdoctoral training at Cornell University. His research focuses on social networks, data mining, machine learning, and computational biomedicine, with contributions to graph neural networks, drug discovery, and AI applications in healthcare. His work has been applied to combat the COVID-19 pandemic and integrated into products at major tech companies. Leskovec’s publications reflect his expertise in network analysis, medical AI, and biological systems. His recent work includes foundational contributions to graph neural networks (e.g., PyG) and medical AI frameworks. His research has garnered numerous awards, including the Microsoft Research Faculty Fellowship and ICDM Research Contributions Award. Leskovec advises numerous doctoral and postdoctoral researchers, contributing to over 200 publications. His interdisciplinary collaborations span computational biology, healthcare analytics, and social systems, with a focus on leveraging AI to address real-world challenges.
Ewa Szczurek is a Professor at the University of Warsaw's Faculty of Mathematics, Informatics and Mechanics and Co-director of the Institute for AI for Health, leading joint labs at Helmholtz Munich and the University of Warsaw. Education: Master degree in Computer Science from Uppsala University, Sweden (2005) Master degree in Computer Science from University of Warsaw, Poland (2006) Doctoral degree from Max Planck Institute for Molecular Genetics, Berlin (2011) Postdoctoral fellowship at ETH Zurich, Switzerland (2011) Habilitation at University of Warsaw, Poland (2020) Visiting associate professor at Northwestern University, USA (2023) Research Focus: Her work centers on probabilistic graphical models and deep generative models applied to computational medicine, with emphasis on oncology (tumor microenvironment modeling and evolution), pulmonology, and AI-driven antimicrobial peptide design to combat antibiotic resistance. She develops specialized deep learning frameworks for spatial transcriptomics analysis, tumor evolution reconstruction, and synthetic antimicrobial compound generation. Publication Trends: Recent publications (2022-2023) demonstrate consistent innovation in AI-driven biomedical solutions, bridging machine learning with oncology and infectious disease research. Her work shows increasing focus on generative models for drug design and spatial data analysis, with strong industry-academia collaborations (e.g., Merck, IMMUcan consortium). Awards: ERC Consolidator Grant (2023) for DOG-AMP project Scientific and didactic award from Rector of University of Warsaw ETH Zurich and IMPRS fellowship awards Grants & Leadership: Leads the ERC Consolidator Grant project DOG-AMP for antimicrobial peptide design. Serves as Associate Editor for Genome Biology and participates in program committees for ISMB and RECOMB-CCB conferences. Collaborates with international consortia including IMMUcan and Merck's Oncology Bioinformatics department. Labs & Networks: Co-directs AI for Health Institute with joint labs at Helmholtz Munich and University of Warsaw. Active in ELLIS (pan-European AI network) and Polish Bioinformatics Society, driving interdisciplinary research at the AI-medicine interface.
Tobias Ofner-Graff is a researcher at the Institute of Forest Growth within the Department of Ecosystem Management, Climate and Biodiversity at the University of Natural Resources and Life Sciences, Vienna (BOKU). Based at Peter-Jordan-Straße 82, 1190 Wien, his work focuses on advanced forest monitoring technologies. His research interests include: LiDAR and remote sensing applications in forestry Automated forest inventory systems Forest regeneration quantification Airborne Laser Scanning (ALS) data analysis Sustainable forest harvesting planning Recent project contributions include: Leading lidar-based forest monitoring systems development Developing spatial forest growth models Implementing digital inventory workflows His publications demonstrate expertise in: Quantifying forest resources through 3D point clouds Advanced timber stack measurement techniques ALS data integration for forest modeling Mobile laser scanning applications Forest climate adaptation strategies
Dr. Tharindu P. De Alwis is an Assistant Professor in the Department of Mathematics and Statistics at the University of West Florida, part of the Hal Marcus College of Science and Engineering. He is actively engaged in teaching and research, with a focus on high-dimensional data analysis and machine learning applications. Ph.D. in Mathematics (Statistics), Southern Illinois University Carbondale M.S. in Mathematics, Southern Illinois University Carbondale B.Sc. in Statistics and Operations Research, University of Peradeniya, Sri Lanka His research centers on dimension reduction techniques, particularly Sufficient Dimension Reduction (SDR), envelope methods, and their applications in multivariate time series and spatial-temporal data. He integrates deep learning and neural networks into statistical modeling, with recent work on stacking-based deep neural networks and Fourier-based SDR methods. His work bridges statistical theory with practical machine learning applications in complex datasets. His recent publications (2021–2024) demonstrate a strong focus on developing innovative statistical and machine learning methods for time series and high-dimensional regression. Key themes include nonlinear modeling, dimension reduction, R package development, and AI-augmented reliability analysis. These works reflect interdisciplinary applications in engineering, data science, and systems safety. Dr. De Alwis has presented his research at national academic conferences in the USA and has publications in peer-reviewed journals such as Statistical Methods & Applications and Reliability Engineering & System Safety , as well as preprints on arXiv and software on CRAN. He teaches a variety of courses including Precalculus with Trigonometry, Linear Algebra, Applied Statistics, and Data Science. While no formal advisees or grants are mentioned, his active publication record suggests ongoing research mentorship and scholarly engagement. He previously served as a post-doctoral scholar at Worcester Polytechnic Institute before joining UWF.
Dr Ana Cristina Vasconcelos is a Senior Lecturer in Corporate Information Management at the School of Information, Journalism and Communication, University of Sheffield. She holds a PhD from Sheffield Hallam University and has held academic roles at multiple institutions, including Leeds Metropolitan University and Sheffield Hallam University. Her research focuses on the intersection of knowledge management, information systems, and organizational adaptation. Education: BA in History, PGDip in Information Science (University of Lisbon), PhD in Information Systems (Sheffield Hallam University) Her research explores organizational learning, absorptive capacity, knowledge sharing, and boundary spanning practices, often applying theoretical frameworks like Arenas/Social Worlds Theory and Practice Theory. Funded by the European Community and AHRC, her work addresses challenges in information systems implementation and knowledge integration across sectors. Recent publications highlight trends in smart city datafication, interdisciplinary knowledge management, and virtual community dynamics. She supervises PhD students in areas spanning economic resilience to knowledge transfer in FinTech ecosystems. Teaching interests include qualitative research methods, organizational culture, and knowledge management systems. She has external examiner roles at multiple universities and serves on editorial boards for journals like Libri and the International Journal of Knowledge-Based Organizations.
Alexander Damm is a Professor and head of the Remote Sensing of Water Systems (RSWS) group, holding a joint appointment between the Department of Geography at the University of Zurich (UZH) and the Swiss Federal Institute of Aquatic Science and Technology (Eawag). His research integrates advanced Earth observation technologies with environmental science to study water systems under changing climatic and anthropogenic pressures. University: University of Zurich Institutional Affiliation: Swiss Federal Institute of Aquatic Science and Technology (Eawag) Department: Department of Geography Alexander Damm obtained his MSc and PhD in remote sensing from Humboldt-University Berlin. Since 2008, he has been contributing to UZH’s leadership in imaging spectroscopy and Earth observation science. MSc, Remote Sensing, Humboldt-University Berlin PhD, Remote Sensing, Humboldt-University Berlin His research focuses on the fundamentals of remote sensing as applied to terrestrial and aquatic ecosystems, particularly in studying water dynamics and environmental change impacts. He specializes in sun-induced chlorophyll fluorescence (SIF), imaging spectroscopy, and the development of methods to monitor ecosystem productivity, drought responses, and biogeochemical cycles. His work bridges physics, ecology, and environmental engineering to improve understanding of plant-water relations and ecosystem resilience. The recent publications highlight a strong trend in using airborne and satellite-based spectroscopy to assess vegetation health, water stress, forest dynamics, and atmospheric constituents. Key themes include SIF retrieval, drought monitoring, canopy structure modeling, and air quality estimation. These works span applications from croplands and forests to tundra and inland waters, reflecting a broad interdisciplinary approach grounded in quantitative remote sensing. Alexander Damm is involved in several high-profile research initiatives, including: ESA’s FLuorescence EXplorer (FLEX) mission SNSF projects: FLUO4ECO, Spatial-sustainable-finance, DeltAs MeteoSwiss: UrbanNature EU Horizon: NextGenCarbon He leads the RSWS group, which develops and applies cutting-edge remote sensing methodologies for water system monitoring. The team collaborates across disciplines and institutions, focusing on integrating field measurements, airborne campaigns, and satellite data for environmental assessment. Damm’s leadership in projects like FLEX and HyPlant underscores his role in advancing spectroscopic remote sensing for global ecosystem monitoring.
