Vikrant Vaze is the Stata Family Career Development Associate Professor and Executive Director of the Master of Engineering Management Program at Dartmouth's Thayer School of Engineering. He leads research in transportation systems, aviation optimization, and healthcare analytics, developing data-driven solutions for complex logistics challenges. His work integrates game theory, statistical modeling, and large-scale optimization. Research spans sustainable urban mobility, airline disruption recovery, multimodal pricing alliances, and healthcare operations. Articles consistently focus on optimization algorithms for real-world transportation and healthcare systems, with recent emphasis on electric aerial mobility and pandemic-responsive logistics. Major Awards: INFORMS Aviation Applications Best Paper (2024, 2023) AGIFORS Best Innovation Award (2024) NSF CAREER Award (2018) President of India Gold Medal As founding co-director of the Operations Research Group, he collaborates with industry partners like Multivariate Systems to translate academic research into deployable solutions.
Hao Chen, Ph.D. is an Associate Professor in the Department of Statistics at the University of California, Davis. His research focuses on statistical methodology for high-dimensional and non-Euclidean data, including anomaly detection, graph-based methods, and change-point analysis. He also explores AI security, multimodal models, and geospatial applications. His work bridges statistical theory and practical machine learning challenges. Education: Ph.D., Graduate Group in Biostatistics, Stanford University Research Interests: Dr. Chen’s expertise spans statistical methods for streaming data, categorical data analysis, and allele-specific copy number variation. He has pioneered work in detecting signals in complex datasets and developing robust AI systems. His recent focus includes mitigating modality interference in LLMs, enhancing model safety via guardrails, and advancing geospatial AI through projects like GeoLM. Publications: His recent work addresses cutting-edge topics such as multimodal model vulnerabilities, unlearning algorithms, and clinical radiology applications. Key themes include improving model robustness, ethical AI design, and interdisciplinary data integration. Labs/Teams: Engages in collaborative projects at UC Davis, though specific lab names are not listed in the provided information.
Aleksandra Raonic is an Associate Professor at the Norwegian University of Science and Technology (NTNU), affiliated with the Department of Architecture and Technology under the Faculty of Architecture and Design. She previously held an Associate Professorship at Xi'an Jiaotong-Liverpool University (XJTLU) in China from 2014 to 2020, where she led Year 3 architecture programs and collaborated with the University of Liverpool. Raonic is also the founder and principal architect of RAUM, an award-winning architectural studio known for research-driven design projects. Her work spans architectural education, urban design, and innovative residential/commercial projects, with a focus on sustainability and community engagement. Her research emphasizes experimental pedagogy and the integration of design practice with academic teaching. Notable projects include the Stubline Kindergarten (2017 S.ARCH Award) and the Central Greenmarket in Negotin (2019 DANS International Award). Raonic has received over 25 design and teaching awards, including the Jiangsu Province Tutor Award (2018) and the Suzhou Excellent Educator Award (2016). She has supervised numerous student projects recognized at national and international levels. Raonic’s teaching philosophy combines theoretical rigor with hands-on practice, evident in her co-authored publications like Framing Indeterminacy (2019). Her recent exhibitions, including Barnas Katedral (2023) and Work in Progress (2023), highlight her commitment to experimental design and public space innovation. She actively collaborates across institutions, such as the Threads of Innovation project with CEPT University in India (2021). Education Background: Professional journey began with early architectural competitions (e.g., 1998 student award for urban design in Pancevo). Formal training includes studies at the Städelschule in Frankfurt, influencing her experimental design ethos. Awards Overview: Over 25 awards spanning teaching excellence, design competitions, and architectural innovation, including Grand Prix (Leonardo 2005) and multiple jury-selected projects. Grants & Projects: Leads applied research initiatives like NTNU’s Threads of Innovation , focusing on space interventions and cross-cultural academic partnerships. Raonic’s architectural practice and academic roles are deeply intertwined, reflecting her belief in education as a platform for advancing architectural discourse and societal impact.
Edriss S. Titi is a University Distinguished Professor and Arthur Owen Professor of Mathematics at Texas A&M University within the College of Arts & Sciences. His research focuses on nonlinear partial differential equations, applied mathematics, and geophysical fluid dynamics. He leads studies on fluid mechanics, atmospheric and oceanic dynamics, data assimilation, and control theory. His work often addresses mathematical rigor in modeling complex systems like climate dynamics and turbulent flows. Research Interests: Nonlinear PDEs and their applications Fluid dynamics and turbulence Data assimilation algorithms Climate and ocean modeling Infinite-dimensional dynamical systems Recent publications emphasize Navier-Stokes equations , primitive equations , and data assimilation in chaotic systems . His methodologies bridge theoretical analysis and computational modeling, with applications to weather prediction and geophysical flows. Collaborations include the Institute for Applied Mathematics and Computational Science (IAMCS) at Texas A&M. Notable contributions include rigorous analysis of global well-posedness for oceanic models and development of CDAnet, a physics-informed deep learning framework for fluid flow downscaling.
Khanh Nguyen is an Assistant Professor in the Department of Computer Science & Engineering at Texas A&M University, part of the College of Engineering. His research focuses on improving scalability and efficiency in Big Data systems through compiler and runtime innovations, particularly in memory management and distributed computing. Education: Ph.D. in Computer Science, University of California, Los Angeles (2019) M.S. in Computer Science, University of California, Irvine (2015) B.S. in Computer Science, University of California, Irvine (2012) His research interests include programming languages, compiler design, memory management, and Big Data systems. He has developed techniques such as Gerenuk for thin computation over big data, Skyway for distributed heap connectivity, and Yak , a high-performance garbage collector. His work emphasizes resource efficiency and workload scalability, particularly for machine learning and data-parallel applications. Recent publications (2021–2024) highlight advancements in adaptive memory management for warehouse-scale computers, semantics-aware swapping in disaggregated systems, and query-driven distributed tracing. Awards: Google Ph.D. Fellowship (2017) Facebook Ph.D. Fellowship Finalist (2017) His research bridges compiler/runtime systems with large-scale data processing, addressing challenges in distributed systems and far-memory utilization. He collaborates with industry and academic partners to advance practical, scalable solutions for modern data-intensive workloads.
Professor Joseph Tzanopoulos is a Professor in Landscape Ecology and Biodiversity Conservation at the School of Ecology and Conservation , University of Kent , and serves as the Academic Lead for SEDarc. He is also a member of the Durrell Institute of Conservation and Ecology. His interdisciplinary research integrates ecological, geographical, and socio-economic perspectives to evaluate the impacts of policy and land-use change on biodiversity and rural sustainability. His educational background includes a BSc in Agricultural Sciences from the Agricultural University of Athens and a PhD in vegetation ecology from Imperial College London. Prior to his appointment at Kent, he held research fellow positions at Wye College, Imperial College London, Aristotle University of Thessaloniki, and the Centre for Agri-Environmental Research at the University of Reading. Professor Tzanopoulos’s research spans landscape ecology, biodiversity conservation, agricultural landscapes, land-use change, GIS, remote sensing, sustainability assessment, and environmental governance . He employs interdisciplinary methods to analyze drivers of change in complex land-use systems, with a focus on reconciling conservation with sustainable development. His recent publications reflect a strong trend in large carnivore conservation, human-wildlife conflict, agroecology, climate change perceptions, and landscape connectivity . Many studies apply spatial modeling and scenario analysis in regions such as Colombia, Oman, Southern Africa, and Europe, often in collaboration with interdisciplinary teams. He is actively involved in supervision, mentoring numerous PhD students on topics including jaguar conservation, lynx reintroduction, marine protected areas, and socio-ecological dynamics. He has also contributed to policy-relevant research and serves on the editorial board of Nature Conservation . His work is supported by collaborations across national and European-funded projects, emphasizing stakeholder engagement, participatory governance, and science-policy integration. He teaches undergraduate modules in geography and GIS, contributing to the training of future environmental scientists.
Anna-Karin Tornberg is a Professor in Numerical Analysis at the Department of Mathematics, KTH Royal Institute of Technology. She holds positions as Vice Chair of the Department of Mathematics and previously served as Head of the Numerical Analysis division (2011–2023). Her research focuses on numerical methods for PDEs, particularly boundary integral methods for fluid flows involving particles and drops. She is active in the Linne FLOW Centre and Swedish e-Science Research Center (SeRC). Key roles include membership in the Royal Swedish Academy of Engineering Sciences (IVA), Royal Academy of Sciences, and receipt of awards like the Göran Gustafsson Prize (Mathematics, 2014). She has advised numerous PhD students and postdocs, including current supervisees Anna Broms, David Krantz, and Emanuel Ström. Her work spans theoretical, computational, and applied fluid dynamics with emphasis on microfluidics and high-accuracy numerical techniques. Education includes a PhD in Numerical Analysis from KTH (2000) followed by postdoctoral positions at NYU’s Courant Institute. Promoted to Full Professor at KTH in 2012. Service roles include membership in KTH’s University Board, Faculty Council, and editorial roles at Advances in Computational Mathematics and BIT Numerical Mathematics . Active in international conferences, delivering plenary/invited lectures at ICIAM, ECM, and ICM. Research group projects include development of fast numerical methods for microfluidics and molecular dynamics simulations. Current openings for PhD candidates in numerical methods for non-elliptic PDEs in time-dependent domains. Her lab collaborates on high-performance computing and fluid-structure interaction problems.
Giovanna Tinetti is a Professor of Astrophysics and Vice Dean (Research) at King's College London's Faculty of Natural, Mathematical & Engineering Sciences. She leads the European Space Agency's Ariel mission, a space telescope surveying exoplanet atmospheres, set to launch in 2029. As co-founder of the London Centre for Space Exochemistry Data and Blue Skies Space Ltd, she pioneers satellite technology for scientific data collection. She holds a PhD in Theoretical Physics from the University of Turin, with prior affiliations at Caltech/JPL, the Institute of Astrophysics in Paris, and University College London (UCL), where she was a Royal Society University Research Fellow. Her research focuses on exoplanetary atmospheres, molecular spectroscopy, and advanced data science techniques. With over 300 publications, her 2019 paper on water vapor in K2-18b's atmosphere achieved the highest altmetric score in Physical Sciences that year. She has delivered over 350 international talks and lectures. Education: PhD in Theoretical Physics (University of Turin) Affiliations: King's College London, UCL (past), ESA's Ariel Mission, Blue Skies Space Ltd Research Interests: Exoplanet atmospheres, molecular spectroscopy, space science, data-driven analysis methodologies, and atmospheric modeling. Her work bridges observational astronomy with computational chemistry to interpret exoplanet compositions and climates. Awards: Royal Society University Research Fellow Highest Altmetric Score (2019 Physical Sciences) Grants & Projects: Principal Investigator for ESA's Ariel mission Co-leader of the Ariel Data Challenge 2025 Labs/Teams: London Centre for Space Exochemistry Data, Blue Skies Space Ltd technical team, and the international Ariel collaboration network.
Ethan McCormick is an Assistant Professor in the School of Education at the University of Delaware, specializing in longitudinal and psychometric modeling. He holds a Ph.D. in Psychology from the University of North Carolina at Chapel Hill (2020) and a B.S. in Biochemistry from the University of Arkansas (2013). His research focuses on integrating short-term and long-term longitudinal models to study behavioral and cognitive changes across the lifespan, with recent emphasis on educational data analysis and nonlinear random effects modeling. He is a Resident Faculty member of the University of Delaware’s Data Science Institute and previously served as an Assistant Professor of Methodology & Statistics at Leiden University (2022–2024). Dr. McCormick’s grants include the NWO Veni SSH Grant (2024–2027) for tracking educational outcomes via statistical modeling and the Jacobs Foundation Fellowship (2024–2026) for studying complex growth in math ability. His work bridges methodological rigor with applied neuroscience, examining brain-behavior relationships in developmental contexts through large-scale collaborations. Professional Experience : Assistant Professor, University of Delaware (2024–present); Assistant Professor, Leiden University (2022–2024) Key Research Themes : Longitudinal modeling, time series analysis, psychometrics, developmental cognitive neuroscience Awards : NWO Veni SSH Grant, Jacobs Foundation Fellowship His recent articles emphasize improving time-series methodologies, addressing limitations of two-time-point studies, and advancing models for asymmetric temporal dynamics. He collaborates internationally on projects simulating developmental datasets and analyzing neural correlates of behavior.
Prof. Dr. Steffi Pohl holds the Chair of Methods and Evaluation/Quality Assurance at the Faculty of Education and Psychology, Freie Universität Berlin since 2019. Previously, she was a Junior Professor (2013-2019) and researcher at institutions including Friedrich-Schiller University Jena and University of Bamberg. She earned her PhD in Psychometrics from Friedrich-Schiller University Jena (2010) and holds a Diplom in Psychology (2004) from Freie Universität Berlin. Her research focuses on advanced statistical methods in educational and psychological testing, including response time modeling, missing data mechanisms, and causal inference in assessment. She has pioneered work on test engagement detection via response patterns and log数据分析. Awards include the 2020 Psychometric Society Early Career Award and 2011 Gustav A. Lienert Dissertation Prize. Pohl serves on editorial boards of Psychometrika , Journal of Educational and Behavioral Statistics , and Zeitschrift für Psychologie . She chairs the Berlin School of Mind and Brain faculty and holds governance roles in academic senates. Her research projects include the National Educational Panel Study (NEPS) and collaborations on test design innovations. Current teaching includes advanced courses in empirical research methods, multivariate statistics, and educational measurement. She actively develops methodologies for analyzing log数据 from digital testing platforms and improving assessment reliability in large-scale studies.
Jazlin Ebenezer is a Professor and Charles H. Gershensen Distinguished Faculty Fellow in the College of Education at Wayne State University, Detroit, MI, USA, where she has been since Fall 2001. Prior to this, she served for ten years at the University of Manitoba, Canada. Her academic journey includes a Ph.D. in Science Education from the University of British Columbia (1991), an M.Ed. and B.A. in Education (Physical Science) from Western Washington University, and a B.Sc. (Hons) in Chemistry from Madurai University, India. Her research is centered on conceptual change teaching and learning in science and technology-embedded scientific inquiry . She has made significant contributions to science teacher education through curriculum development, qualitative research, and international collaboration. Her work emphasizes student-centered, inquiry-based learning and the integration of technology to enhance scientific understanding. The 15 most recent publications reflect a strong focus on technology integration in science education, teacher and student conceptions, and innovative pedagogical models. Key themes include phenomenography as an assessment tool, discourse in science classrooms, cognitive development through multiple representations, and the use of environmental research to foster inquiry. Her research spans K-12 and higher education contexts, with a consistent emphasis on equity, holistic development, and reflective practice. Charles H. Gershensen Distinguished Faculty Fellowship (2019-21) Fulbright Specialist Award (2013-18) Marquis America Who's Who (2003) Rh Award (Research), University of Manitoba (2000) Research Merit, Faculty Association, University of Manitoba (1999) Outstanding Students Honoring Outstanding Teachers Award, University of Manitoba (1994) Dr. Ebenezer has been a principal investigator on multiple grants, including an NSF ITEST grant (PI, $1.2M) and a $1.2M NSF grant for integrating IT into Lake Erie ecosystem research. She has served as a consultant on international projects, such as a TÜBİTAK project in Turkey. Her advising includes mentoring pre-service teachers and guiding research on conceptual change and curriculum development. She has also been a member of advisory boards for large-scale educational initiatives. She has established and led research models such as the Common Knowledge Construction Model and the Technology-Embedded Scientific Inquiry (TESI) Model . She has conducted extensive international work, delivering keynotes and seminars across India, Turkey, Thailand, China, and Sri Lanka, often focusing on science education reform, qualitative research, and curriculum innovation.
Gérard Ben Arous is a Silver Professor of Mathematics at New York University's Courant Institute of Mathematical Sciences, where he has served as Director and Vice Provost for Science and Engineering Development since 2011. He holds a PhD in Mathematics from the University of Paris VII (1981) and has previously taught at the University of Paris-Sud, École Normale Supérieure, and the Swiss Federal Institute of Technology in Lausanne. His research focuses on probability theory, stochastic analysis, and their applications to physics and industrial problems, particularly exploring complex systems' long-time behavior and aging phenomena in disordered media. Education: PhD in Mathematics, University Paris 7, France (1981) M.Sc. in Statistics, University Paris-Sud Orsay, France (1979) B.S. in Mathematics, École Normale Supérieure (Paris), France (1978) His research interests bridge probability with partial differential equations, dynamical systems, and statistical mechanics. Key contributions include studies on random media, random matrices, and the interplay between complexity, disorder, and aging in physical systems. He has held leadership roles in academic institutions, including directing the mathematics departments at Orsay and École Normale Supérieure, and founded Lausanne's Bernoulli Center. Notable awards include Fellow of the Institute of Mathematical Statistics and the Montyon Prize from the French Academy of Sciences. His work is published in top journals like Annals of Probability and Communications in Pure and Applied Mathematics , and he co-edits Probability Theory and Related Fields . Ben Arous has advised numerous researchers and contributed to interdisciplinary projects, including studies on machine learning landscapes and financial mathematics. His lab focuses on stochastic modeling and its applications across disciplines.
Dr. Panagiotis Andriotis is a Lecturer in Computer Science at the School of Computer Science, University of Birmingham, within the College of Engineering and Physical Sciences. He is also a GIAC Certified Forensic Examiner (GCFE, GASF) and a Senior Fellow of the Higher Education Academy (SFHEA). His interdisciplinary research spans Cyber Security, Human Factors, and Mobile and Ubiquitous Computing. He teaches courses in Computer Science, Cyber Security, and Digital Forensics. His educational background includes a PhD in Computer Science from the University of Bristol (2016), an MSc with Distinction in Computer Science from the same institution (2011), and a BSc in Mathematics from the National and Kapodistrian University of Athens (2004). Dr. Andriotis’s research interests focus on user-centered security, particularly in mobile environments. He investigates how users interact with Android’s permission systems, develops novel authentication mechanisms like Bu-Dash, and explores adversarial machine learning in cybersecurity. His work bridges technical and human aspects, aiming to improve both system robustness and user experience. His recent publications reflect a strong trend in adversarial machine learning, mobile malware detection, usable privacy, and the societal implications of AI in education. He has contributed to high-impact journals such as IEEE Transactions on Cybernetics, ACM Transactions on Privacy and Security, and Elsevier’s Journal of Information Security and Applications. Best Paper Award at HCI International 2020 Impact Award, UWE Bristol Student Union GIAC Certified Forensic Examiner (GCFE) GIAC Advanced Smartphone Forensics (GASF) SANS Lethal Forensicator Coin Dr. Andriotis has advised PhD students, including Andrew McCarthy, and has been involved in funded research projects such as those related to fuzzing, software security, and critical infrastructure protection in collaboration with Airbus. He has served as an External Examiner at Cardiff Metropolitan University and is currently on the editorial boards of Digital Threats: Research and Practice (ACM) and the Journal of Responsible Technology (Elsevier). He has held visiting roles at the National Institute of Informatics in Tokyo, including as a JSPS Fellow and Toshiba Fellow. He leads research in digital forensics and security, with a lab focus on mobile ecosystems, behavioral modeling, and AI-driven threat detection. His team explores both technical and human dimensions of cybersecurity, contributing to tools and frameworks that enhance mobile security and user awareness.
Isabella Di Lenardo is a Lecturer and Scientist at the Digital Humanities Institute (DHI) at École Polytechnique Fédérale de Lausanne (EPFL), where she also serves as the coordinator of the EPFL Time Machine Unit and the European Local Time Machines. She holds affiliations across multiple departments, including DHI-GE, SAR-ENS, SHS-ENS, and EDDH-ENS, reflecting her interdisciplinary role in teaching and research. Her educational background includes a PhD in Theories and Art History, with postdoctoral and faculty experience at institutions such as INHA (Paris), EPFL, and IUAV (Venice). Her research spans Digital Humanities, Art History, Urban History, and GIS , with a focus on digital urban reconstruction, historical cadastres, and AI applications in cultural heritage. She employs advanced computational methods including machine learning, 4D modeling, and semantic segmentation to analyze historical maps, cadastral records, and art archives. Her work bridges humanities scholarship with computer science, particularly in reconstructing urban evolution and analyzing visual patterns. The recent publications reveal a consistent trend in AI-powered historical data analysis , especially in processing non-standardized historical documents, reconstructing urban spaces, and developing open-source tools for digital heritage. Her work frequently involves large-scale datasets from Venice, Lausanne, Paris, and Jerusalem, demonstrating a transnational and interdisciplinary approach. She has contributed to significant collaborative projects such as the Venice Time Machine , Parcels of Venice , and Time Machine Organization , often acting as a principal investigator or project leader. Her role involves coordinating diverse teams of researchers, engineers, and cultural institutions. Scientific contributions include: Development of the Morphograph tool for visual pattern recognition in art archives Automatic vectorization and analysis of Napoleonic cadastres Creation of 4D models for historical cities AI-driven text and pattern extraction from historical maps Building discovery engines for digital art history She actively teaches ex cathedra courses in Digital Urban History and Art History at EPFL and internationally. Her work in grants and projects emphasizes open data, reproducibility, and interdisciplinary collaboration. She has led research funded by organizations supporting digital heritage innovation. She is a key member of the Digital Humanities Laboratory at EPFL and the Time Machine Organization , where she fosters collaboration between computer scientists, historians, and cultural institutions. Her work in the Replica Project and ARCHiVe center highlights her leadership in digitizing and making accessible large art historical archives.
Jingrui He is an Assistant Professor in the Computer Science Department at Stevens Institute of Technology, with primary research focuses on statistical machine learning and large-scale data mining. Her work spans theoretical algorithm development and practical applications in diverse domains. University: Stevens Institute of Technology Department: Computer Science Department Academic Rank: Assistant Professor Research interests include: Heterogeneous machine learning techniques Rare category analysis and detection Social network analysis Public safety applications Traffic analytics Multimedia processing Virtual metrology in semiconductor manufacturing Publishing trends show consistent contributions to machine learning, data mining, and graph-based methods across multiple domains including semiconductor manufacturing, social networks, and multimedia. She has collaborated with researchers from Stevens Institute of Technology, IBM, and Carnegie Mellon University on both theoretical and applied problems.
