Dr. Jörg Waitelonis serves as Scientific Co-Worker at FIZ Karlsruhe – Leibniz Institute for Information Infrastructure and Senior Researcher at Karlsruhe Institute of Technology's Institute of Applied Informatics and Formal Description Methods (AIFB), working under Prof. Dr. Harald Sack. His career spans over 15 years in semantic technologies research, beginning at Hasso-Plattner-Institute (2009-2018) and continuing at KIT/FIZ Karlsruhe. Dr. Waitelonis' research focuses on practical implementations of Semantic Web technologies across diverse domains. His work bridges theoretical knowledge representation with real-world applications in cultural heritage informatics, materials science, historical document analysis, and sports science. Key contributions include developing domain-specific ontologies (CourtDocs, PMD Core), advancing FAIR data implementation within Germany's NFDI framework, and creating knowledge graph solutions for cross-disciplinary research data integration. His publication record demonstrates consistent output in top Semantic Web venues (ISWC, SEMANTiCS) with recent work (2023-2025) emphasizing practical ontology engineering for national research data infrastructure projects. Current research directions show increasing focus on materials science ontologies, historical document processing, and BFO-based knowledge representation frameworks. As founder of yovisto GmbH since 2012, Dr. Waitelonis maintains strong industry connections while pursuing academic research. His work demonstrates the practical application of semantic technologies to solve real-world data integration challenges across multiple scientific domains.
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Yang Liمشاهده پروفایل
دانشیار
Yang Li serves as Associate Professor of Marketing and Associate Dean for the MBA Program at Cheung Kong Graduate School of Business (CKGSB). Holding a PhD in Marketing from Columbia Business School alongside dual master's and bachelor's degrees from Columbia and Peking University respectively, he bridges advanced statistical methodologies with practical business applications. His research centers on statistical machine learning and Bayesian nonparametrics applied to consumer behavior analysis, with specialization in online personalization, text mining, and choice modeling. Recent work demonstrates significant focus on fragmented attention economies, ethical AI frameworks, and NFT network dynamics, reflecting contemporary digital market challenges. Management Science Marketing Science Journal of Marketing Research Journal of Consumer Research Harvard Business Review Professor Li's publications reveal evolving expertise from foundational pricing elasticity studies toward cutting-edge AI applications in consumer contexts. His work increasingly integrates generative models and graph neural networks to decode complex consumer collection behaviors and digital ecosystem dynamics. Scientific recognition includes being a Finalist for the 2021 Paul E. Green Best Paper Award. Industry impact is demonstrated through executive education programs and strategic consultancies with Tencent, Haier, and Tmall. As Associate Dean for MBA Programs, he oversees curriculum development while maintaining active corporate governance roles on boards of publicly traded companies across China and Hong Kong, directly applying his research insights to strategic decision-making in digital transformation initiatives.
Mathias Sablé-Meyerمشاهده پروفایل
پژوهشگر ارشد
- Mechanistic implementation of compositional mental representation
- Geometry perception in humans and non-human primates
- Human reasoning and cognitive fallacies
- +۵ مورد دیگر
Mathias Sablé-Meyer is a Postdoctoral Researcher at University College London's Sainsbury Wellcome Centre, working in Tim Behrens's lab. He completed his PhD under the supervision of Stanislas Dehaene at PSL/Collège de France and NeuroSpin, CEA, where he investigated humans' ability to manipulate highly abstract structures, particularly focusing on the perception of geometry. His research spans cognitive neuroscience, computational modeling, and experimental psychology, with a focus on understanding the mechanistic implementation of compositional mental representations. He employs methodologies including MEG, fMRI, behavioral experiments, and computational models to investigate how humans mentally represent abstract structures like geometric shapes, language, and mathematical concepts. Sablé-Meyer's work reveals fascinating insights about human cognitive uniqueness, particularly in geometric perception compared to non-human primates. His recent research examines sequence processing mechanisms and aims to establish foundations for mechanistic implementations of Language of Thought models. He has published in top journals including Cognitive Psychology , Trends in Cognitive Sciences , PNAS , and Journal of Neuroscience . Glushko Dissertation Prize from the Cognitive Science Society (2023) As a supervisor, he co-advises Master's students including Maxime Cauté, who is exploring cross-modal representation of sequences, and is involved with several other students including Svenja Kuchenhoff, Amy Wong, and others. His lab follows open science principles, with code systematically published on the Open Science Framework alongside articles. His research program bridges cognitive science, neuroscience, and artificial intelligence, with implications for understanding both human cognition and developing more human-like AI systems. He maintains active collaborations across institutions including UCL, Collège de France, MIT, and École Normale Supérieure.
Professor Ulrich Eisenecker serves as the Director of the Institute for Business Informatics at Leipzig University's Faculty of Economics and Business Administration. He holds the Chair of Business Informatics with specialization in software development for business and administration, a position he has maintained since October 2004. Prior to this, he served as Dean of the Faculty (2012-2016) and Pro-Dean (2008-2012). His academic journey includes professorships at Kaiserslautern University of Applied Sciences (1999-2004) and Heidelberg University of Applied Sciences (1995-1999), following research positions at Daimler-Benz Research Institute and Mannesmann Kienzle GmbH. Professor Eisenecker's research focuses on Generative Software Development , Software Product Lines , Software Visualization (including 2D, 3D, AR and VR applications), and E-Assessment systems . His work bridges theoretical computer science with practical business applications, particularly evident in his application of set theory to software features and product lines. He leads the ongoing 'Visual Software Analytics' project and has previously directed projects funded by the European Social Fund and German Federal Ministry of Education and Research. His publication record spans over two decades, highlighted by the influential 2000 book 'Generative Programming' co-authored with K. Czarnecki and the 2017 Most Influential Paper Award from the Software Product Line Conference. Recent work (2023-2025) continues to advance software engineering and educational technology, particularly in automated assessment systems using AI techniques. Notable recognition: Most Influential Paper Award from Software Product Line Conference 2017 (SPLC 2017) Professor Eisenecker supervises doctoral and master's students, with numerous successful completions including Dr. Richard Müller, Dr. Max Lillack, and Dr. Johannes Kristan. His research group includes several scientific staff members and regularly publishes with student co-authors. He teaches 'Introduction to Computer Science' for economics students, 'Programming,' and 'Software Engineering' courses, integrating his research in automated feedback systems into his pedagogy. His research group maintains strong connections between academic research and practical applications, particularly through open source initiatives and industry collaborations focused on software analytics and educational technology.
Prof. Dr. Hans-Peter Lenhof holds the Chair for Bioinformatics at Saarland University since 2000, where he leads research in computational biology and disease mechanism analysis. His career includes: Postdoctoral research at Max Planck Institute for Informatics (1993-1999) Research Group Leader at MPI (1999-2000) Professor at Saarland University (2000-Present) His group develops innovative bioinformatics methods with three primary focus areas: Personalized Cancer Therapy : Creating AI/ML approaches to optimize drug selection from over 200 cancer therapeutics, addressing tumor heterogeneity through predictive modeling of treatment efficacy. Diagnosis & Prognosis : Pioneering blood-based diagnostic methods using autoantibody and miRNA profiles that demonstrate high clinical sensitivity for multiple cancers and neurological disorders through collaborative studies. Pathogenic Mechanism Analysis : Employing graph-based network models to visualize and analyze deregulated biological processes, particularly signaling cascades in cancer progression. The lab maintains active collaborations with Andreas Keller's Clinical Bioinformatics group and Eckart Meese's Human Genetics team. Computational tools developed include BALLView for molecular visualization, GeneTrail for high-throughput data analysis, and specialized frameworks for therapy optimization (MERIDA) and miRNA networks (miRTargetLink).
- Algorithms
- Bioinformatics
- Comparative Genomics
- +۵ مورد دیگر
Séverine Bérard is a Lecturer in the Computer Science Department at the Faculty of Sciences, University of Montpellier, where she holds a Habilitation à Diriger des Recherches (HDR) since 2016. Her institutional roles include: Co-director of the Bioinformatics Master's program Elected member of the University Board of Directors (since 2021) Elected member of the Faculty of Sciences Council (since 2017) Appointed member of the University Training Committee (since 2016) Her research at ISE-M's Phylogeny and Molecular Evolution Team bridges computer science and bioinformatics, with core focuses on: Development of text algorithms and graph-based methods for genomic analysis Comparative genomics and ancestral genome reconstruction Quality assessment of genome assemblies and meta-assemblies Evolutionary modeling of chromosome rearrangements Her recent publications (2016-2021) demonstrate strong emphasis on algorithmic innovations for evolutionary genomics, including genome scaffolding techniques, DCJ rearrangement models, and ancestral genome reconstruction methods applied to organisms ranging from mosquitoes to bacteriophages. In education, she teaches across all academic levels (L1-M2) in both practical computer science (networks, programming) and theoretical disciplines (discrete mathematics, text algorithms), while leading curriculum development as co-director of the Bioinformatics Master's program.
Jihyeok Parkمشاهده پروفایل
استادیار
Jihyeok Park is an Assistant Professor in the Department of Computer Science and Engineering at Korea University's College of Informatics, where he has been a faculty member since March 2023. Previously, he was a Post Doctoral Fellow at Oracle Labs, Australia (2022-2023). He earned his Ph.D. from KAIST under Professor Sukyoung Ryu, focusing on JavaScript static analysis for evolving language specifications. His academic background includes: Integrated M.S. & Ph.D. in School of Computing, KAIST (2016-2022) B.S. in School of Computing and Mathematical Sciences, KAIST (2012-2016) Dr. Park's research centers on programming languages and software engineering, with expertise in program analysis, mechanized specification, program synthesis, and automated testing. He leads the ESMeta project, which extracts mechanized specifications from the ECMAScript standard to generate language-based tools. His work particularly targets JavaScript, aiming to improve the reliability and security of modern software systems through innovative specification and analysis techniques. His recent publications at top conferences (including ASE 2025 and ESEC/FSE 2025) demonstrate a strong trend in static analysis and specification for JavaScript. These works, such as Debun for detecting bundled libraries and JSSpecVis for specification visualization, reflect his commitment to developing practical tools that address real-world software engineering challenges. Dr. Park has received numerous honors and awards: Korea University Excellent Course Award for COSE212 Programming Languages (2023-2) Ph.D. Dissertation Award, College of Engineering, KAIST (2022) Outstanding Ph.D. Thesis, School of Computing, KAIST (2022) ACM SIGSOFT Distinguished Paper Award, ICSE 2021 Ph.D. Fellowship Award, NAVER Corp. (2020) Outstanding Teaching Assistant Award for KAIST CS320 Programming Languages (awarded multiple times between 2016 and 2019) Outstanding Teaching Assistant Award for KAIST CS109 Programming Practice (2016 Spring) Best Paper Award, SOAP 2017 ACM Student Research Competition 3rd Place, Modularity 2014 KAIST Presidential Fellowship (2013) He is actively recruiting graduate students, undergraduates, and postdoctoral researchers for his research group at Korea University. His work is conducted within the Programming Language Research Group (PLRG), where he leads the ESMeta project and collaborates on advancing programming language theory and software engineering practice. Future research directions include extending ESMeta to support more language features and improving the scalability of specification-based tools.
Prof. Dr. Erhan Genç serves as a University Professor (W2) for 'Neuroscientific Foundations of Differential Psychology' at TU Dortmund University since 2023, operating under the Jülich model for research activities at IfADo (Leibniz Research Centre for Working Environment and Human Factors). He leads the 'Neuroimaging and Interindividual Differences' research group at the Institute for Occupational Safety and Health of the German Social Accident Insurance in Dortmund, Germany. His primary research focuses on: Neural basis of interindividual differences in cognitive functions and personality Application of multimodal neuroimaging methods (7T, 3T EEG/fMRI, TMS/fMRI, DWI, neurogenetics) Genç's research program investigates how variations in brain structure and function correlate with differences in cognitive abilities and personality traits. His work employs advanced neuroimaging techniques to uncover neural mechanisms underlying human intelligence and cognitive control processes, with particular emphasis on structural and functional brain connectivity. His publication record demonstrates consistent contributions to understanding the relationship between brain microstructure (particularly white matter organization and neurite architecture), brain network properties, and cognitive abilities. His recent work has established important links between polygenic scores, brain network efficiency, and intelligence measures. Methodologically, his expertise spans diffusion MRI for assessing microstructural properties of brain tissue, functional MRI for investigating brain connectivity patterns, and multimodal integration of different neuroimaging techniques to provide comprehensive insights into brain-behavior relationships.
Yao Wanمشاهده پروفایل
دانشیار
Yao Wan is an Associate Professor at the School of Computer Science and Technology, Huazhong University of Science and Technology (HUST) in Wuhan, China. He leads the ONE Lab, focused on empowering machines to interact with the physical world through unified natural language interfaces (Language + X paradigm). He obtained his Ph.D. from Zhejiang University and has research visiting experience at Chinese University of Hong Kong, University of Technology Sydney, and University of Illinois Chicago. His research bridges Artificial Intelligence and Software Engineering, with core interests in: Natural Language Processing for code intelligence Large Language Model applications Multimodal learning across code, vision, and UI domains Program analysis and code generation Software engineering automation His publications demonstrate strong focus on applying transformer-based models to software engineering challenges, with recent work expanding into multimodal applications. Research spans code model security, GUI generation, data visualization, and compiler understanding, predominantly using deep learning approaches. Awards: IEEE TCSE Distinguished Paper Award for SANER 2025 publication He actively mentors students through the ONE Lab and serves on program committees for top conferences including ASE, ISSTA, and ICSE. He is seeking highly-motivated undergraduate researchers to join his team. The ONE Lab conducts cutting-edge research at the intersection of programming languages and artificial intelligence, with ongoing projects in code intelligence, multimodal learning, and LLM applications for software engineering.
Ajitha Rajan is a Professor (Personal Chair of Software Testing & Verification) at the School of Informatics, University of Edinburgh. She joined the university in December 2012 as a Reader (equivalent to Associate Professor in American terms) and was promoted to Professor in 2024. Prior to her position at Edinburgh, she held postdoctoral positions at Oxford University and Laboratoire d'Informatique de Grenoble in France. She earned her PhD in Computer Science from the University of Minnesota in August 2009 under Professor Mats Heimdahl. Her research focuses on two primary directions: Automated Software Testing (including test input generation, test oracles, and coverage measurement) and Biomedical AI (particularly cancer survival models and interpretability for biological sequences and medical images). Her work has applications in safety-critical systems, blockchains, embedded systems, and medical diagnostics. She has made significant contributions to explainable AI for healthcare applications, especially in lung cancer detection and cancer survival analysis. Her recent publications demonstrate a strong trend toward interdisciplinary research at the intersection of software engineering and biomedical applications. She has numerous publications in top venues including ICSE, ASE, and healthcare-focused conferences. Her work increasingly focuses on making AI systems more interpretable and trustworthy, particularly in medical contexts where model decisions can have life-or-death consequences. ACM SIGSOFT Distinguished Reviewer Award, ISSTA 2025 Best Paper Award at ICHI 2025 Promoted to Professor (Chair in Software Testing & Verification) 2024 SICSA Best Supervisor Award 2024 ACM Distinguished Paper Award 2008 Professor Rajan actively supervises PhD students in both software testing and biomedical AI domains. She leads several funded projects including MANIFEST (a cancer immunotherapy response research platform), a Huawei Joint Lab project on RobustCheck, a Royal Society Industry Fellowship on AutoTest, and the KATY project on clinical knowledge for personalized medicine. Her research group includes current PhD students working on explainable AI for medical image analysis, scenario-based testing for autonomous driving, and protein design applications.
Raimund Dachselt is a Professor at the Institute of Software and Multimedia Technology within the Faculty of Computer Science at Dresden University of Technology. His research focuses on advanced visualization techniques and human-computer interaction systems. His primary research interests include: Data visualization for non-planar displays Augmented reality with photorealistic lighting Collaborative work with interactive display walls Analysis of multivariate graphs in multi-display environments Understandable software systems for cyber-physical worlds Professor Dachselt leads multiple significant research initiatives funded by the German Research Foundation (DFG), with particular emphasis on immersive analysis of cyber-physical systems and interactive exploration of visual models. His work bridges theoretical computer science with practical applications in collaborative environments. His scientific contributions span across several major research centers including: TRR 248: Fundamentals of Understandable Software Systems EXC 2050: Center for Tactile Internet with Human-in-the-Loop (CeTI) EXC 2068: Physics of Life - The Dynamic Organization of Living Matter