Prof. Harald Sternberg is a distinguished academic at HafenCity University Hamburg, holding the position of University Professor for Hydrography and Geodesy. His affiliations include the Department of Geodesy and Geoinformatics, where he leads research in hydrographic education and advanced geomatics technologies. He previously served as Vice President for Teaching and Studies (2009-2022) and Acting President (2010) of HCU. Education: Ph.D. in Geodesy from University of the Bundeswehr Munich (1999), specializing in trajectory determination of land vehicles using hybrid systems. Early career included roles as scientist at Bundeswehr University (1991-2001) and academic leadership at HAW Hamburg (2005-2009). Research focuses on underwater mapping, navigation systems, and sensor integration. Key projects include: Level 5 Indoor Navigation (5G-based positioning), hydrothermal vent exploration using deep-towed multibeam systems, and low-cost mobile mapping solutions. He also investigates smartphone-based inertial navigation and autonomous underwater vehicles for infrastructure monitoring. Publications span underwater vision systems, satellite-derived bathymetry, and 3D point cloud analysis. Over 200 peer-reviewed articles and book chapters reflect expertise in geomatics applications. Current research emphasizes 5G-enabled indoor navigation and environmental sensor networks. Grants include BMWK-funded autonomous deep-sea monitoring and BGR exploration projects in the Indian Ocean. His lab develops innovative tools like the HOMESIDE sled for seafloor surveys. Supervises Ph.D. research on hydrothermal vent analysis and data-driven inertial localization.
Stefania Degaetano-Ortlieb is an Associate Professor of English Linguistics and Corpus Linguistics at Saarland University's Department of Language Science and Technology. She serves as Principal Investigator for the Collaborative Research Center (SFB 1102) 'Information Density and Linguistic Encoding,' leading Project B1 on diachronic information density in English scientific writing (17th century-present). Her interdisciplinary work bridges computational methods with sociolinguistics, focusing on register variation, language change, and digital humanities. Research interests center on text mining, data analytics, and probabilistic modeling of language variation. Key areas include: Diachronic evolution of scientific registers and linguistic densification Information-theoretic approaches to language efficiency Computational sociolinguistics and register diversification AI applications in humanities education (e.g., ChatGPT integration) Her publications show a strong trend toward quantitative diachronic analysis, with recent work emphasizing: interpretable AI models for linguistic change detection; propagandistic narrative analysis in conflict zones; and multi-word expression dynamics in scientific discourse. Cross-disciplinary collaborations frequently intersect with history, psychology, and media studies. Awards include the Fellowship Excellence Program for Young Female Scientists (2015-2018). Current grants: EU Horizon MSCA Doctoral Network 'CASCADE' (€521K to UdS, 2024-2027) Data-Pin Project for AI in education (€50K, 2023-2024) SFB 1102 Project B1 (€595K, 2022-2026) Advises PhD candidates in the EU CASCADE project on computational semantic change. Leads a research team exploring Russian media narratives, personality modeling in LLMs, and multi-word expressions. Directs teaching modules integrating AI tools for humanities students.
Prof. Dr. Heiko Paulheim is a Professor of Data Science and currently serves as University Vice President at the University of Mannheim. He leads the Data and Web Science Group (DWS), which focuses on Web Data Mining, Knowledge Graphs, and Semantic Web technologies. His research group contributes to open source knowledge graphs like DBpedia and develops new knowledge graphs such as WebIsALOD and DBkWik. As of October 1, 2024, he has limited teaching capacity due to his vice presidential duties. Prof. Paulheim's research interests span Knowledge Graphs, Semantic Web, Web Data Mining, Machine Learning, and Natural Language Processing. His work particularly focuses on knowledge graph refinement, embedding techniques (notably RDF2vec), and applications in various domains including news recommendation, biomedical informatics, and environmental monitoring. His group develops practical tools like the RapidMiner Linked Open Data Extension and RDF2vec for knowledge graph applications. His recent publications demonstrate a strong focus on knowledge graph embeddings, with particular attention to RDF2vec variants, applications in news recommendation systems, biomedical data integration, and spatio-temporal knowledge graphs for environmental monitoring. His work bridges theoretical advances in knowledge representation with practical applications across multiple domains. Among his notable achievements are a nomination for the Best Paper Award at CAiSE 2025 and securing an Open Science Grant for the SpatialBenchRAG project. His research has significant impact in both academic and industrial contexts, with multiple papers accepted at top conferences like ISWC and ESWC. Prof. Paulheim has supervised numerous PhD students including Alexander Brinkmann and Michael Schlechtinger, and has led several research projects including the DFG Project Mine@LOD, State of BW Project SyKoW², and BMBF Project DS4DM. His group maintains strong industry connections with partners like SAP AG, Daimler AG, and IDS.
Jun.-Prof. Dr. Christian Krupitzer is a Tenure Track Professor in Food Informatics at the University of Hohenheim's Institute of Food Science and Biotechnology, part of the Faculty of Natural Sciences. He leads the Department of Food Informatics and is a member of the Computational Science Hub (CSH). His research focuses on self-adaptive software systems, machine learning (especially edge computing), IoT technologies, and software engineering applied to food processing and agricultural systems. Education: PhD in Business Information Systems (Dr. rer. pol.), University of Mannheim (2018) M.Sc. and B.Sc. in Business Information Systems, University of Mannheim (2010–2012) High School Diploma (Abitur) from Wilhelmi-Gymnasium Sinsheim (2007) Research Interests: Krupitzer’s work integrates computational methods with food science, emphasizing adaptive systems for food quality monitoring, IoT in agriculture, and machine learning for predictive analytics. He explores edge computing’s role in real-time decision-making and secure group communication schemes for IoT networks. Publications: His recent work spans predictive maintenance in Industry 4.0, digital twins in food systems, and blockchain applications in supply chain authentication. The articles highlight trends in interdisciplinary approaches combining AI, IoT, and domain-specific challenges in food production and logistics. Awards: No scientific awards explicitly listed in the provided materials. Grants & Advising: While specific grants are unmentioned, his roles as department head and tenure-track professor suggest involvement in research funding. No formal advisee list provided, though his team includes postgraduate researchers like Dana Jox, Daniel Einsiedel, and others. Labs & Teams: Leads the Food Informatics department and collaborates with the Computational Science Hub. His team focuses on developing innovative solutions for food systems through computational methods.
Véronique Hoste is Senior Full Professor of Computational Linguistics at Ghent University's Faculty of Arts and Philosophy, where she serves as Department Head of Translation, Interpreting and Communication and Director of the LT3 language technology research team. She also holds the position of Research Director for the Faculty of Arts and Philosophy. Her educational background includes a PhD in Computational Linguistics from the University of Antwerp (2005) focused on optimization in machine learning for coreference resolution. Key research areas encompass machine learning for natural language processing, semantic and discourse modeling, including specialized work in event detection, entity/event coreference resolution, irony detection, and emotion analysis. Hoste's publication trends reveal strong interdisciplinary focus, with recent work bridging NLP with crisis communication, digital humanities, and ethical AI. Her team develops high-quality datasets (e.g., EmoTwiCS for emotion trajectories) and collaborates extensively with commercial partners on projects like SentEMO for aspect-based sentiment analysis. Current research emphasizes multimodal emotion analysis, fuzzy rough set methods for sentiment detection, and cross-document event coreference. Elected member of the Royal Flemish Academy of Belgium for Science and the Arts (KVAB) Francqui Chair appointment by Université Libre de Bruxelles (2023-2024) Co-founded LT3 spin-off AlfaSent (2024) for customer feedback analysis Authored first Dutch-language book on NLP: "Taaltechnologie ontrafeld" She actively supervises multiple PhD students on projects including Common-sense knowledge in irony detection (Common-sense), cross-document event coreference (Encore), and empathy modeling in conversational agents (FlandersAI). Her team secures funding through interdisciplinary collaborations like NewsDNA for news recommendation and METRICS for emotion trajectory analysis. Hoste also engages in public outreach through the "AI at school" initiative and advises on language technology integration in high school curricula. The LT3 laboratory under her leadership maintains strong industry partnerships and develops practical NLP tools including EmotioNL and Automatic Term Extraction systems, while advancing core research through projects like CLARIAH-VL for data curation.
Jarno Vanne is a Professor at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences at Tampere University. His research focuses on video coding standards, real-time systems, and hardware acceleration, particularly in the context of FPGA implementations and open-source tools. He leads projects involving VVC (Versatile Video Coding), V-PCC (Volumetric Video Coding), and HEVC (High Efficiency Video Coding), with an emphasis on efficiency, low latency, and machine learning integration. Key research interests include point cloud compression, saliency-guided encoding, parallelization schemes, and real-time video communication protocols. His work often addresses challenges in multi-party video streaming, embedded systems, and encryption mechanisms for privacy protection. He has contributed to open-source projects like the UVG dataset, Kvazaar encoder, and CiThruS simulation frameworks. Recent publications highlight advancements in VVC intra encoding optimizations, machine learning-driven partitioning schemes, and FPGA-accelerated solutions for edge computing. His research bridges theoretical video coding algorithms with practical implementations, aiming to improve compression efficiency while maintaining real-time performance.
Helen Suh is a Professor at Tufts University, jointly appointed in the departments of Civil and Environmental Engineering and Community Health . As an internationally-recognized expert in air pollution health effects, she combines environmental epidemiology , exposure science , and data analytics to investigate how pollutants impact human health. Sc.D. , Harvard University (1993) M.S. , Harvard University (1990) S.B. , Massachusetts Institute of Technology (1985) Her research focuses on three areas: air pollutant impacts on cognitive performance and child development , multi-pollutant health effects , and GIS-based spatio-temporal modeling for epidemiological studies. Recent publications highlight her work on PM2.5 measurement error correction , hormonal disruptions in pregnancy , and machine learning applications in environmental health analysis. Current trends include: Advanced statistical methods for exposure assessment Multi-omics approaches to cardiometabolic health International comparative studies (e.g., Tehran, Puerto Rico) Long-term mortality analysis in Medicare populations Pollution-immune system interactions in vulnerable groups Policy-relevant modeling for air quality standards Helen Suh has served as an Associate Editor for the Journal of Exposure Science and Environmental Epidemiology and advised major U.S. and international health organizations. Her work spans over 150 publications and integrates multidisciplinary team leadership in environmental health science. Her laboratory develops large-scale data analytics tools and spatio-temporal exposure models to support population-level health research. Current projects include air pollution and aging cohorts , urban environmental noise measurement , and epigenetic responses to pollutants .
Dr. Tamás Koltai is a Professor and Dean at the Faculty of Economics and Social Sciences of Budapest University of Technology and Economics (BME). He leads the doctoral school's Specialization Group in Production Management. His roles include overseeing academic programs and research in production management, operations research, and efficiency analysis. Education: Doctor of the Hungarian Academy of Sciences (2016) Dr. habil. (2000), Budapest University of Technology and Economics Candidate of Technical Sciences (1987), Hungarian Academy of Sciences M.Sc. in Mechanical Engineering (1983), BME Faculty of Mechanical Engineering Research Interests: Dr. Koltai focuses on production management optimization, including the application of Data Envelopment Analysis (DEA), sensitivity analysis in mathematical models, and the integration of robotics in assembly lines. His work bridges theoretical models (e.g., MILP/CP optimization) with practical industrial challenges, particularly in healthcare efficiency and educational management. Notable Awards: IEOM Society Teaching Excellence Award (2021) BME GTK Faculty Memorial Medal (2016) János Susánszki Award (2013) Széchenyi Professorship Scholarship (1999–) Teaching & Leadership: He has held visiting roles at the University of Seville (1990–1992) and the University of Michigan (1988/89). His teaching excellence is recognized through awards and his contributions to business simulation education. His research often collaborates with industry partners to address real-world operational challenges. Labs/Teams: Leads the Production Management Specialization Group and contributes to interdisciplinary teams focusing on manufacturing efficiency and healthcare operations within BME.
Dr. Wei David Dai is an Assistant Professor of Computer Science at Purdue University Northwest and Director of the Advanced Intelligence Software (AIS) Lab. His research focuses on robust deep learning, data quality, and public safety technologies like gunshot detection systems. He previously worked at IBM China as a senior engineer and served in Arkansas state government as a data scientist. Education: Ph.D. in Computer and Information Sciences (University of Arkansas at Little Rock, USA, 2020) M.S. in Information Science (University of Arkansas at Little Rock, USA, 2016) M.S. in Software Engineering (South China University of Technology, China, 2013) B.S. in Computer Science (Central South University, China, 2007) Research Interests: His work spans robust deep learning models, distributed computing systems, and privacy-preserving technologies. Notable projects include public safety innovations such as acoustic gunshot detection and AI-driven campus security systems. Articles Trends: Recent publications emphasize public safety applications (e.g., mass school shooting simulations) and deep learning robustness evaluation (e.g., the Accuracy-Stability Index metric). Earlier works address cloud computing optimization and data quality frameworks. Awards: Recipient of the 2024 Excellence in Research Award and multiple IBM honors for technical excellence and instruction. Grants & Advising: Leads the Indiana Space Grant Consortium-funded satellite imaging project and Purdue Provost Grant for gunshot detection. Advises doctoral and master’s students on AI ethics, distributed systems, and public safety. Labs: The AIS Lab develops AI tools for public safety, equipped with GPU resources for audio and image analysis.
Brian D. Gregory is a Professor of Biology at the University of Pennsylvania's School of Arts & Sciences. His research focuses on RNA modifications, computational biology, and plant genetics, particularly studying how RNA modifications regulate gene expression in plants and animals. He holds a Ph.D. from Harvard University (2005) and a B.S.A. from the University of Arizona (2000). Research Interests: RNA epitranscriptomics (e.g., m6A, NAD+ caps) RNA secondary structure and protein interactions Genomic approaches to study plant stress responses Development of high-throughput sequencing tools like PIP-seq Recent Work Highlights: Recent studies include analyzing pathogen-induced RNA modifications' role in plant immunity (Plant Cell 2023), global RNA structure/protein interaction mapping, and epitranscriptomic dynamics in drought tolerance. His lab's work bridges computational methods with molecular genetics to uncover post-transcriptional regulatory mechanisms. Lab & Collaborations: The Gregory Lab uses Arabidopsis thaliana as a primary model organism but also explores animal systems. They collaborate with institutions like Cornell University and have developed protocols published in Current Protocols in Molecular Biology. Teaching: BIOL 4231: Genome Sciences and Genomic Medicine BIOL 6010: Communication for Biologists
Miklós Koren is a Professor of Economics at the Central European University (CEU), Vienna. He serves as Head of the MS in Business Analytics Program and a Core member of the Economics Doctoral School. His research focuses on international trade, economic development, and the role of management in economic growth. He holds a Ph.D. from Harvard University (2005), an M.A. from CEU (2000), and a B.A. from Corvinus University Budapest (1999). Education: Ph.D. in Economics, Harvard University, 2005 M.A. in Economics, Central European University, 2000 B.A. in Economics, Corvinus University Budapest, 1999 Research Interests: Dr. Koren’s work examines the impact of managerial practices on economic development, trade policies, and firm performance. He has explored topics such as the effects of international experience on managerial talent, the role of expatriate CEOs in enhancing productivity, and the long-term implications of social distancing on industries reliant on face-to-face interactions. His research integrates empirical analysis with theoretical frameworks, often using large datasets to address questions of economic volatility and diversification. Key Contributions: He leads the CEU MicroData research group and has received an ERC Starting Grant for his work on trade and development. His publications span journals like the Quarterly Journal of Economics and PLoS ONE, addressing issues ranging from managerial skills in post-communist economies to the predictive power of machine learning in geospatial flows. Awards: Recipient of the Peter Kenen Fellowship and the Nicholas Káldor Prize, recognizing his contributions to economic theory and applied research. Grants & Labs: His research has been supported by grants from the European Research Council. He contributes to the development of research tools like the Stata package 'eventbaseline' for event study analysis.
Dimitris Mitropoulos is an Assistant Professor at the National and Kapodistrian University of Athens (NKUA) in the Department of Business Administration, where he teaches courses on Distributed Ledger Technologies, Data Security and Privacy, Algorithms and Business Analytics, and Introduction to Programming. He also serves as Head of the Reliability Engineering Directorate at the National Infrastructures for Research and Technology (GRNET), Greece's national research and education network organization. Previously, he was a Postdoctoral Researcher in the Computer Science Department at Columbia University. Dr. Mitropoulos received his Ph.D. degree in Secure Software Development Technologies from the Athens University of Economics and Business (AUEB) in 2014. His doctoral research was supported by the Heracleitus II Scholarship, co-financed by the European Union and Greek national funds. He is a member of prestigious professional organizations including ACM, IEEE, and USENIX. Dr. Mitropoulos conducts pioneering research at the intersection of software engineering and cybersecurity, with particular expertise in secure software development, vulnerability analysis, and blockchain security. His work spans multiple dimensions of software security including code injection attacks, infrastructure as code security, smart contract analysis, and dependency management in software ecosystems. His research methodology combines static and dynamic analysis techniques with empirical studies of real-world software systems, particularly focusing on Java, Python, and Solidity ecosystems. His recent work has made significant contributions to understanding security vulnerabilities in modern software development practices and infrastructure management. Dr. Mitropoulos has received numerous prestigious awards for his research contributions, including the Research Excellence Award from NKUA (2025), Distinguished Paper and Artifact Awards at PLDI '22, Best Data Showcase Award at MSR 2018, and multiple postdoctoral research funding scholarships. His work on "Finding typing compiler bugs" was recognized with both Distinguished Paper and Artifact Awards at PLDI '22, highlighting the significance and reproducibility of his research. He has also received recognition for his service to the academic community, including a Certificate of Appreciation from ESEC/FSE '21 for his contributions to conference organization. Dr. Mitropoulos has been actively involved in securing research funding and leading significant research projects. He currently serves as Principal Investigator for the SecOPERA project (2023-Today), funded by the European Commission under Horizon Europe. Previously, he contributed to several major EU and US-funded projects including eSSIF-Lab (2019-2022), FASTEN (2019-2022), PRIViLEDGE (2018-2021), CERTCOOP (2017-2020), PANORAMIX (2016-2019), and TREDISEC (2016-2018). His research has been supported by diverse funding sources including the European Commission's Horizon 2020 program, the National Science Foundation, and the Defense Advanced Research Projects Agency (DARPA). Dr. Mitropoulos plays an active role in the international research community through various leadership positions. He serves on program committees for top-tier conferences including OOPSLA (2026), ICSE (2026), ESEC/FSE (2025), and ISSTA (2025). He has previously served as Workshop Co-Chair for ISSTA 2025 and Student Volunteer Chair for ESEC/FSE 2021. His contributions to mentoring the next generation of researchers include serving as a mentor for the ICSE Student Mentoring Workshop (2022) and supervising Google Summer of Code projects (2017).
Yannic Noller is a Professor at the Faculty of Computer Science at Ruhr University Bochum (RUB), leading the Software Quality group. Previously, he held positions as Assistant Professor at Singapore University of Technology and Design (SUTD) and Research Assistant Professor at National University of Singapore (NUS). His research focuses on automated software engineering, including program repair, machine learning analysis, and software testing. He earned his Ph.D. from Humboldt-Universität zu Berlin under Prof. Lars Grunske, with a thesis on hybrid differential software testing. Education: Ph.D. in Computer Science (2016-2020, Humboldt-Universität), M.Sc. (2013-2016, University of Stuttgart), B.Sc. (2010-2013, University of Stuttgart). Research interests include automated program repair techniques, machine learning model analysis, and intelligent tutoring systems for programming education. Notable contributions include HyDiff (hybrid differential analysis tool) and CPR (concolic program repair). Awards include the Distinguished Artifact Reviewer at ISSTA'2021 and multiple scholarships for academic excellence. Teaching includes courses on software engineering, requirements engineering, and automated software engineering.
Prof. Vesa Välimäki is an Audio Signal Processing Professor at Aalto University's School of Electrical Engineering, leading the Audio Signal Processing Research Group within the Aalto Acoustics Lab. He also serves as Vice Dean for Research and Head of the Doctoral Programme at the university. His research focuses on digital signal processing, machine learning, and their applications in audio, acoustics, and music technology, particularly in artificial reverberation, audio filter design, and virtual analog modeling. He has pioneered techniques like velvet noise for reverberation synthesis and contributed to open-source tools like FLAMO. His academic accolades include IEEE, AES, and AAIA Fellowships, along with multiple best paper awards at venues like DAFx and ICASSP. He has advised numerous students, including recipients of prestigious awards like the Huawei Master's Thesis Award. Prof. Välimäki has held editorial roles at the Journal of the Audio Engineering Society and organized major conferences such as SMC-17. His work extends to applied projects like acoustic optimization for early childhood education facilities and immersive audio in virtual reality (e.g., the 'Space Walk' project). Key Projects: NordicSMC (Nordic University Hub for Sound and Music Computing), Aalto Acoustics Lab, FLAMO library Grants: NordForsk funding (2018–2023), Foundation for Aalto University Science and Technology His research spans both theoretical advancements (e.g., diffusion models for audio restoration) and practical implementations (e.g., real-time equalizers, headphone compensation systems). He collaborates internationally, contributing to acoustic measurement techniques and noise reduction strategies for diverse environments.
Cliff Zou is a Professor in the Department of Computer Science at the University of Central Florida (UCF), where he coordinates master’s programs in cybersecurity, privacy, and digital forensics. He directs the UCF Alliance for Cybersecurity and contributes to the university’s Cyber Security and Privacy Cluster. Education: Ph.D. in Electrical and Computer Engineering from University of Massachusetts-Amherst His research focuses on computer and network security , network modeling , and performance evaluation . Key areas include malware analysis, botnet defense, and adaptive cybersecurity protocols. His publications address threats like email worms, peer-to-peer botnets, and internet worms, reflecting his work in proactive threat mitigation and network resilience. Scientific recognition includes: Senior Member of IEEE Best Student Paper Award (ACSAC 2007) UCF Teaching Incentive Program (TIP) award (2013) Best Paper runner-up (PADS 2005, ICCCN 2004) First-place award for undergraduate project 'Personal Medication Monitor' His research has been featured in New Scientist Magazine , EurekAlert! , PCWorld , and The Register . Zou actively contributes to academic conferences as an organizer and program committee member.
