Joseph Glaz is a Professor in the Department of Statistics at the University of Connecticut. His work focuses on applied probability and statistical methodology, particularly in scan statistics and related inference techniques. Contact: joseph.glaz@uconn.edu Phone: (860) 486-4193 (Storrs Campus) Research highlights: Develops scan statistics for discrete , continuous , and conditional data frameworks Specializes in change-point detection for normal data mean/variance Innovates robust methods for outlier-prone datasets Extends scan statistics to network and graph structures Contributed to foundational texts like the Handbook of Scan Statistics Publication trends include: Scan statistics for genomic data (Hi-C translocation detection) Nonparametric and Bayesian extensions of scan methods Approximations and inequalities for sequential testing Applications in quality control , medical imaging , and sensor networks
Irena Vodenska is Professor of Finance and Director of Finance Programs at Boston University’s Metropolitan College, Department of Administrative Sciences. She holds a PhD in statistical finance and an MA in economics from Boston University, an MBA from Vanderbilt University, and a BS in computer information systems from the University of Belgrade. She is also a Chartered Financial Analyst (CFA) charter holder. Her research is at the intersection of finance, complexity science, and artificial intelligence, focusing on systemic risk modeling, ESG investments, and financial network dynamics. She has led major interdisciplinary research projects funded by the National Science Foundation, the European Commission, and the U.S. Army Research Office. PhD, Statistical Finance – Boston University MA, Economics – Boston University MBA – Owen Graduate School of Management, Vanderbilt University BS, Computer Information Systems – University of Belgrade Dr. Vodenska’s research interests include network theory in finance, systemic risk propagation, AI-powered ESG analysis, cryptocurrency price forecasting, and financial regulation. She employs big data, machine learning, and natural language processing to analyze financial news, market dynamics, and corporate sustainability. Her work investigates how climate disinformation spreads via social networks and influences public policy and governance. The recent articles highlight a consistent focus on modeling financial and economic systems using network science and AI. Trends include systemic stress testing, sentiment analysis in financial markets, cascading failures, and the interplay between macroeconomic indicators and financial networks. Her work spans econophysics, behavioral finance, public health economics, and ethical AI in fintech. National Science Foundation (NSF) research grant (2023) NSF EAGER Award (2014–2015) European Commission FET Open Grant (2012–2014) U.S. Army Research Office (ARO) Grant (2020–2021) MEXT Post-K Computer Grant, Japan (2016–2019) Alexander Hamilton Fulbright Fellowship (1994) Owen Graduate School Fellowship (1995–1996) Dr. Vodenska teaches core finance courses such as Investment Analysis and Portfolio Management, Derivatives Securities, and Financial Regulation and Ethics. She co-developed the MET AD 678 course with Professor Tamar Frankel from BU Law, emphasizing real-world case studies and ethical decision-making. Her research grants have supported innovative work in systemic risk modeling, AI for ESG, and financial network stability. She is actively involved in mentoring, conference organization, and editorial roles in leading journals. She is a key organizer of the International School and Conference on Network Science (NetSci) and the Big Data in Economics, Science, and Technology (BEST) Conference. Her lab and research team focus on complexity in financial systems, bringing together economists, physicists, computer scientists, and data analysts to study global financial stability and sustainability.
Elizabeth Yale is an Associate Professor in the Department of History at the University of Iowa, College of Liberal Arts and Sciences, where she also serves as Director of Undergraduate Studies. Her research lies at the intersection of the history of science, book history, and early modern European intellectual culture, with a focus on how knowledge was created and preserved in domestic and archival contexts. Her educational background includes a PhD in the History of Science from Harvard University (2008). She previously taught at Western Carolina University and Harvard before joining the University of Iowa. Dr. Yale's research explores the material and social practices of knowledge-making, particularly in early modern Britain. She emphasizes the role of families, manuscript culture, and archival infrastructures in the development of scientific thought. Her work spans themes such as gender, materiality, and the transmission of medical and natural knowledge. She teaches courses on early modern Europe, the history of science and medicine, book history, and gender, often incorporating hands-on analysis of texts through the University of Iowa Center for the Book. Her recent publications reveal a consistent interest in the material forms of knowledge—letters, lists, marginalia, and archives—and their role in shaping scientific epistemology. She frequently examines how women’s intellectual labor and domestic spaces contributed to scientific advancement. Her collaborative projects, including an NEH-funded initiative with Matthew Brown, aim to build innovative educational spaces for studying global print and manuscript cultures. Visiting Scholar, Max Planck Institute for the History of Science, Berlin (2016) President, Andrew W. Mellon Society of Fellows in Critical Bibliography (2021–2022) Senior Fellow, Andrew W. Mellon Society of Fellows in Critical Bibliography Dr. Yale has been active in mentoring and curriculum development, particularly through experiential learning programs like the Hawkeye History Corps. She has secured external funding, including an NEH Humanities Initiatives Grant, to support interdisciplinary teaching and research. Her advising likely extends to undergraduate and graduate students interested in history of science, gender studies, and material text analysis, though specific students are not listed. She is also engaged with public history, contributing accessible commentary to outlets like The Atlantic , Quartz , and Iowa Public Radio , bridging academic research with broader societal conversations on science, gender, and race. She is involved in collaborative scholarly communities, especially through the Rare Book School and the University of Iowa Center for the Book, where she contributes to projects that integrate book history with scientific and archival studies. These affiliations support a vibrant research and teaching environment centered on material knowledge practices.
Dr. Sunnie Sun Chung is a Professor in the Department of Electrical Engineering and Computer Science at Cleveland State University's College of Engineering. She leads the Big Data Analytics & AI Lab and has received multiple Faculty Merit Recognition Awards (2020-2024) and Golden Apple Awards (2021-2022). Research Interests : Big Data Analytics, Artificial Intelligence, Natural Language Processing, Cyber Security, Machine Learning, and Optimization in Cloud/IoT environments. Teaching : Advanced courses in Data Mining, Big Data Systems, and Deep Learning (DSA460/CIS492/593, CIS611/711, etc.) with dedicated teaching labs. Publications reflect expertise in Knowledge Graphs for Medical QA , Network Intrusion Detection with Graph Models , Privacy-Preserving Cloud Learning , and Basketball Analytics . Her work spans journals like IEEE Transactions on AI and IEEE Access. Scientific Awards : Faculty Merit Recognition Awards (4x) Golden Apple Teaching Award (2x) Students Supervised : Over 10 PhD/Master’s students including Asanka Mananayaka (NLP-based Intrusion Detection), Yixi Luo (Homomorphic Encryption), Dennis Risch (Medical QA Systems), and collaborators with Case Western Reserve University. Labs & Collaborations : Director of the Big Data Analytics & AI Lab since 2018. Hosted annual IBM Health collaborative workshops since 2018. Maintains strong industry ties with Microsoft, Amazon, Oracle, and Cleveland Clinic.
Sandra Geisler is a Junior Professor for Data Stream Management and Analysis at the Department of Computer Science, RWTH Aachen University, a position she has held since September 2021. She is also the leader of the Digital Health Spaces group at the Fraunhofer Institute for Applied Information Technology (FIT) in St. Augustin, reflecting her dual expertise in academic research and applied digital health solutions. Bachelor/Master: Diploma in Computer Science, RWTH Aachen University (2008) PhD: Doctoral degree in Computer Science, RWTH Aachen University (2016) Her research focuses on data stream systems, real-time analytics, data quality, and their applications in digital health and industrial processes. She has made significant contributions to ontology-based data quality management, edge computing for stream processing, and FAIR data principles. Recent work explores the integration of large language models into data management workflows and the development of privacy-preserving platforms for industrial data exchange. Her recent publications demonstrate a strong trend in distributed and edge-based stream processing, interdisciplinary applications in healthcare and supply chains, and the use of AI for data discoverability and quality. Topics include in-network computing, simulation of edge queries, self-tonometry for glaucoma, and cross-company data sharing with privacy awareness. She has served as Associate Editor for the Data & Knowledge Engineering Journal (Elsevier), Public Relation Chair for QDB Workshop (VLDB 2016), and Workshop Chair for IMMoA and HIMoA workshops. She has also edited a special issue on Information Management in Mobile Applications in the Pervasive and Mobile Computing Journal. Geisler has supervised multiple theses on topics including LLM-based ontology integration, edge anomaly detection, and data ecosystem modeling. She has been actively involved in research grants and projects related to industrial data processing, digital health, and sustainable production. She teaches courses such as Data Stream Management and Analysis and Data Ecosystems Lab. She leads the Digital Health Spaces research group at Fraunhofer FIT, focusing on innovative solutions for health data management and patient-centric digital tools. Her work bridges computer science, healthcare, and industrial applications, promoting secure, efficient, and intelligent data ecosystems.
Howard E. Epstein is the Sidman P. Poole Professor in the Department of Environmental Sciences at the University of Virginia, College of Arts and Sciences. He leads an active research group focused on ecosystem ecology, with field sites in the Arctic tundra of North America and Russia, as well as temperate forests in the U.S. Mid-Atlantic region. His work integrates field observations, remote sensing, and biogeochemical analysis to understand ecosystem responses to climate change. Ph.D., Colorado State University, 1997 Dr. Epstein's research centers on arctic vegetation dynamics , carbon cycling , and permafrost-vegetation interactions . He investigates how warming climates drive shrub expansion, ice-wedge degradation, and landscape transformation in tundra ecosystems. His work also explores carbon and water fluxes in temperate forest successional gradients. He employs advanced techniques including drone-based spectroscopy, satellite remote sensing, and flux tower measurements. The recent publications highlight a strong focus on Arctic greening , permafrost degradation , and the use of remote sensing and machine learning to detect ecological change. His work spans spatial scales from fine-resolution drone imaging to continental-scale satellite analysis, with applications in climate modeling and ecosystem monitoring. Dr. Epstein teaches core courses in ecology, including Terrestrial Ecology (EVSC 5220) and Fundamentals of Ecology (EVSC 3200) . He advises graduate students and leads the Epstein Ecosystem Ecology Lab , which conducts fieldwork in diverse ecosystems from Alaska to Virginia. His research is supported by external funding, though specific grants are not listed in the provided text. He has made significant contributions to understanding climate change impacts on high-latitude ecosystems, with publications in top journals such as Global Change Biology , Environmental Research Letters , and Nature Reviews Earth & Environment .
Lim Jit Yan is a Lecturer at the School of Information Technology, Monash University Malaysia. He holds a PhD in Information Technology (2023) from Multimedia University, specializing in self-supervised metric-based meta-learning for few-shot image classification, and a B.IT (Hons) in Artificial Intelligence (2019) from the same institution. His research focuses on few-shot learning, computer vision, and deep learning, with contributions to medical image analysis (e.g., Covid-19 detection), transfer learning applications, and generative models. He has published extensively since 2021, with notable work on self-supervised feature fusion and prototypical networks for few-shot learning. Research interests include few-shot learning techniques, neural architecture design for image classification, and real-world applications like healthcare diagnostics and autonomous systems. Recent work emphasizes self-supervised learning and transformer-based models to address data scarcity challenges in AI. No formal scientific awards are listed. Advising details are not provided in the text, though his publications suggest collaborative research with colleagues like Lim K.M. and Lee C.P. His research spans theoretical advancements and applied projects, including work on pill image recognition, traffic sign detection, and brain tumor classification.
Shamik Roy is a Visiting Researcher at the School of Biological Sciences, University of East Anglia (UEA), actively contributing to research in microbial ecology and soil biogeochemistry. He holds a Doctor of Science from the Indian Institute of Science, awarded in 2021. Doctor of Science, Indian Institute of Science (awarded April 2021) His research focuses on microbial processes in diverse soil environments, including Arctic, volcanic, and agricultural soils. Key interests include antimicrobial resistance dynamics, trace gas metabolism, carbon cycling, and the application of metagenomics and stable isotope probing to study active microbial populations. His work bridges environmental microbiology with climate change and public health implications. The recent publications highlight a trend toward integrating genomic tools with ecological questions, particularly examining microbial functional roles in extreme environments and human-impacted ecosystems. Studies frequently involve collaborations and utilize advanced sequencing and isotopic techniques. Although no scientific awards are listed in the provided text, his work has gained significant attention, being picked up by 29 news outlets, blogged about, and widely shared on social media platforms including X (formerly Twitter), Bluesky, and Facebook. There is no available information about student advising or research grants. However, his active publication record suggests ongoing research engagement and collaboration within the environmental microbiology community. Shamik Roy is involved in a research network focusing on microbial ecology, with external collaborations across countries. His work contributes to understanding microbial roles in global biogeochemical cycles and environmental resilience.
Henrik Høeg Müller is an Associate Professor and Head of Department in Spanish Business Communication at the School of Communication and Culture, Aarhus University, Denmark. He is actively engaged in linguistic research focusing on typological differences between Danish and Spanish, particularly in syntax, morphology, and lexical-schematic distinctions. Institution: Aarhus University School: School of Communication and Culture Department: Spanish Business Communication Position: Associate Professor, Head of Department Email: henhm@cc.au.dk His research centers on the structural and typological contrasts between Danish and Spanish, especially in nominal expressions, predicate formation, and lexical vs. syntactic encoding. Key interests include bare nouns, count/mass distinctions, telicity, motion verbs, and schematicity. His work often employs comparative and cognitive linguistic frameworks. The most recent publications reveal a strong trend in analyzing how lexical and syntactic strategies diverge across languages, especially in expressing similarity, kind, and event structure. Topics such as the Danish 'slags', complex predicates, and ambiguous nominal structures highlight his focus on fine-grained syntactic and semantic analysis. These works contribute to broader discussions in typology and cognitive linguistics. Henrik Høeg Müller has served as an editor for Ny Forskning i Grammatik and frequently presents at academic events, including workshops and conferences. He has no listed scientific awards in the provided text. Editorial Role: Editor, Ny Forskning i Grammatik Presentations: Regular lecturer at seminars and conferences on Danish and Spanish linguistics He is involved in academic networks related to Scandinavian and Romance linguistics, contributing to collaborative research and scholarly discourse. No labs or formal research teams are explicitly mentioned.
Prof. Kenneth Guang-Lih Huang is the Dean's Chair and Full Professor at National University of Singapore (NUS), holding dual appointments in the Department of Industrial Systems Engineering and Management (ISEM) and the Department of Strategy and Policy (NUS Business School). He is the Academic Director of the Master of Science in Management of Technology and Innovation (MOTI) program. His research focuses on innovation management, AI strategy, intellectual property, and institutional change in emerging economies like China and ASEAN. He has published in top journals such as Science, Strategic Management Journal, and Management and Organization Review, and his work has been featured in global media including Reuters and MIT Technology Review. Education: Ph.D. (Technology Management and Policy, MIT), M.S. (Technology and Policy, MIT), B.S. (Biomedical Engineering & Electrical Engineering, Johns Hopkins University). Research Interests: Innovation strategy, AI/ML applications, intellectual property management, entrepreneurship, global strategy, science policy, and institutional analysis in transitional economies. Teaching: Designs courses on IP Management, Technology Strategy, and Entrepreneurship for graduate and executive programs. Recognized with prestigious awards including the NUS Annual Teaching Excellence Award (2024) and multiple teaching honors from NUS and Singapore Management University. Awards: AOM Best Paper Awards, SMS Fellowships, DRUID grants, and INFORMS recognition for contributions to innovation research. Serves on editorial boards of top journals and advises firms like IBM, Singtel, and the Singapore Intellectual Property Office. Professional Roles: Deputy Editor of Management and Organization Review , advisor to the Economist Intelligence Unit, and frequent keynote speaker at global conferences.
Christian Mann is Professor and Chair of Ancient History at the Historical Institute, Faculty of Philosophy, University of Mannheim. He has been in this position since 2011, following research and teaching roles at Freiburg, Frankfurt, Brown University, Konstanz, and Basel. He earned his PhD in 1999 with a thesis on the political significance of athletes in early Greek polis formation and completed his habilitation in 2005 on demagogues in democratic Athens. His research spans Greek and Roman history, with a focus on ancient sports (MAFAS project), political culture, populism, and the social roles of athletes. He examines how ancient athletic competitions functioned as mechanisms of inclusion and exclusion, and draws parallels between classical demagoguery and modern populism. His recent work includes a 2023–2024 Opus Magnum scholarship from the Volkswagen Foundation to write Greek Athletes: A Social History . He is co-editor of KLIO and a member of the Scientific Advisory Board of the Gerda Henkel Foundation. His publications from 1998 to 2024 cover topics such as gladiatorial games, equestrian competitions, democratic theory, and religious aspects of sport. His recent articles reveal a strong trend in analyzing athletic competitions as social institutions intertwined with politics, religion, and identity. He frequently employs epigraphic and literary sources to explore honor systems, talent promotion, and cross-cultural comparisons, particularly between Greek, Roman, and Jewish traditions. Opus Magnum scholarship, Volkswagen Foundation (2023/24) Christian Mann has supervised academic projects and interdisciplinary seminars, such as the Mannheim Hall of Antiquities (2016) and a seminar on Karl Popper’s Open Society (2019). He has received external research funding, notably the Opus Magnum grant, supporting extended scholarly writing. There is no public list of his advisees in the provided text. He leads the MAFAS (Mannheim Research Focus on Ancient Sports) initiative, which investigates the sociopolitical dimensions of athletic competition in antiquity. His chair fosters interdisciplinary collaboration, as seen in joint seminars with colleagues from other departments.
Jennifer D'Souza is a Research Fellow in the Open Research Knowledge Graph (ORKG) project at the Data Science and Digital Libraries research group within the Technische Informationsbibliothek (TIB) . Her current work focuses on natural language machine learning, including knowledge graph construction, ontology alignment, and AI-assisted scientific discovery. Prior to TIB, she held postdoctoral positions at the University of California, Davis (focusing on software engineering and NLP applications) and completed her PhD at the University of Texas at Dallas, specializing in relation mining. She has also contributed to industrial software solutions in concept generation. Education : PhD in Computer Science, University of Texas at Dallas Postdoctoral Researcher, University of California, Davis Research Interests : Information Extraction and Question Answering Scientometrics and Knowledge Organization Natural Language Processing (NLP) for Ontology Learning Large Language Models (LLMs) in Scientific Workflows Awards & Grants : Not explicitly listed, but her contributions to projects like ORKG and participation in hackathons highlight collaborative achievements in AI-driven research. Labs/Teams : Active member of the Data Science and Digital Libraries group at TIB, contributing to projects such as ORKG and the Large Language Models for Ontology Learning Challenge .
Dr. Tillman Weyde is a Reader in the Department of Computer Science at City, University of London , where he has been employed since 2021. He leads the Machine Intelligence and Media Informatics Research Group and is a member of the Machine Learning Group . Prior to this, he served as Senior Lecturer (2009–2021) and Lecturer (2005–2009) at City, and worked as a researcher at the University of Osnabrück (2001–2005), coordinating the MUSITECH project. His academic background includes PhD in Music Technology (2002), MSc in Computer Science (1999), and MSc in Mathematics, Music, Philosophy & Pedagogy (1994), all from the University of Osnabrück. Research Focus: Machine learning and signal processing methods for data analysis with applications in finance, audio, NLP, music, health, security, and education. His recent work emphasizes inductive biases in neural networks for rule-learning, extrapolation, generalization, and interpretability. Grants & Projects: Principal Investigator for the AHRC-funded Digital Music Lab (2012–2017) and Integrated Audio-Symbolic Model of Music Similarity (2017–present). Co-investigator in Innovate UK and EPSRC projects on safer gambling ( Advancing Consumer Protection , 2015–2018) and Raven (2012–2021). Collaborations: Affiliated with the Institute of Cognitive Science (Osnabrück), Intelligent Systems Research Laboratory (Reading), and the MPEG Ad-Hoc Group on Symbolic Music Representation. Awards: Co-author of the 2000 Comenius Medal-winning educational software Computer Courses in Music Ear Training and co-editor of the Osnabrück Series on Music and Computation . Publications: Over 150 peer-reviewed works including conference papers, journal articles, and book chapters, focusing on interdisciplinary applications of machine learning in music, health, and finance. Students: Supervised 13 PhD students across topics like grammar bias in neural networks, emotion recognition from audio, extrapolation behavior in neural networks, relation-based patterns, legal text parsing, and more.
Prof. Dr. Katrin Kraus holds the Chair for Vocational Education and Training and Adult Education at the University of Zurich since 2021. Previously, she served as Professor for Adult Education at the University for Teacher Education FHNW (2009-2014) and held positions at universities in Trier, Zurich, Konstanz, Heidelberg, and Osnabrück. Her research focuses on the intersection of education, society, and the world of work, with emphasis on work-related learning educational governance in VET and adult education actor-oriented theories spatial approaches to learning inclusion in vocational contexts . Her academic career includes a doctorate (2005) and habilitation (2012) on topics related to vocational education and social change. She leads research projects on themes like transversal skills in service sectors sustainability in VET critical events in workplace training appropriation of learning spaces , using qualitative methods, text/image analysis, and case studies. Recent publications analyze frictions in policy implementation design of learning environments historical futurology in vocational training disability inclusion in professional pathways . Her work appears in journals like Studies in Continuing Education and Transfer: Vocational Education in Research and Practice . As an academic leader, she chaired the Executive Board of the University for Teacher Education FHNW (2015-2021), co-edits the Adult Education and Life-long Learning book series, and serves on editorial boards for Swiss and international journals.
Sébastien Fournier is a researcher affiliated with the University of Aix-Marseille, focusing on natural language processing, multimodal data analysis, and agent-based systems. He has contributed to projects like ANR GUIDANCE, ADNvideo, CoPains, and PhysSocial, emphasizing dialogue-assisted information access, video fingerprinting, persuasive health agents, and psychophysiological foundations of social behavior. Research areas: Aspect-Based Sentiment Analysis, Contradiction Detection in Reviews, Multimodal Data, Recommendation Systems Projects: ANR GUIDANCE (Workpackage 3 Leader), ADNvideo (2014-2016), CoPains (2019-2022), PhysSocial (2018-2021) His work extends to evaluating interactions in serious crisis management games, with supervision of PhD students like Ismail Badache and Adrian-Gabriel Chifu. He collaborates with institutions including LIS, LSIS, and ILCB (Institute of Language, Communication and the Brain).
