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Sabrina BüttnerView profile

Professor

• Cellular Aging
• Organelle Communication
• Membrane Contact Sites
• +5 more

Prof. Sabrina Büttner leads the Cell Biology group at the Institute of Integrative Cell Biology and Physiology, University of Münster. Her research focuses on intracellular communication during cellular aging, stress responses, and metabolic adaptation, utilizing yeast and Drosophila models. She investigates organelle connectivity via membrane contact sites and their role in proteostasis, neurodegeneration, and longevity. Her work integrates molecular biology, genetics, and imaging to explore: Organelle communication networks Proteostasis collapse in aging Autophagy and lipid metabolism Neurodegenerative disease mechanisms Recent publications emphasize membrane contact sites, stress-induced nuclear/vacuole dynamics, and autophagy regulation. Trends include organelle interfaces in proteostasis, mitochondrial quality control, and translational applications in longevity biotechnology. She mentors PhD students including Irene Álvarez-Guerra, Emma Block, Patricia Grabher, and Simon Prokisch. Her lab collaborates with CRC projects (e.g., CRC 1009, 1348, 1459, 944) and graduate programs (CiM-IMPRS, IRTG, SP BioSciences).

Brigitte PientkaView profile

Professor

• Programming Languages
• Verification
• Type Theory
• +6 more

Brigitte Pientka is a Professor at McGill University's School of Computer Science , where she leads the Computation and Logic group . She earned her PhD from Carnegie Mellon University in 2003 and previously studied at the University of Edinburgh and Technical University of Darmstadt. Education PhD in Computer Science, Carnegie Mellon University (2003) University of Edinburgh Technical University of Darmstadt Research Interests Her work focuses on the theoretical and practical foundations for building reliable software systems, combining logic, type theory, and verification with system-building. Key areas include: Type Theory and Dependent Types Logical Frameworks and Mechanized Metatheory Session-Typed Concurrency and Linear Logic Metaprogramming and Contextual Type Systems Theorem Proving and Formal Verification Functional Programming and Language-Based Security Professional Roles She has served as: PC Chair for ICFP'24 and CPP'24 General Chair for POPL'20 Executive Editor of Logical Methods in Computer Science Steering Committee Member for LICS, POPL, and ESOP Scientific Awards Dr. Pientka has received: Test of Time Award at PPDP'18 Humboldt Fellowship for research at MPI-SWS, Germany Labs & Teams She actively develops the Beluga programming language , a tool for mechanizing meta-theory proofs and type-driven program manipulation.

• Statistical Relational Learning
• Machine Learning
• Probabilistic Graphical Models
• +5 more

Lise Getoor is a Professor in the Department of Computer Science at the University of California, Santa Cruz, within the Baskin School of Engineering. She previously held positions at the University of Maryland, College Park and has established herself as a leading researcher in statistical relational learning and neuro-symbolic artificial intelligence. Her research focuses on developing principled approaches to reasoning and learning with rich, relational data. She has made significant contributions to probabilistic soft logic, statistical relational learning, knowledge graph construction, and the integration of symbolic and neural approaches to AI. Her work bridges theoretical foundations with practical applications in areas including social network analysis, sustainable recommendations, cyberbullying detection, and fair machine learning systems. Analysis of her recent publications reveals a strong trend toward neuro-symbolic integration, with increasing focus on combining neural networks with logical reasoning frameworks. Her research demonstrates consistent innovation in developing scalable algorithms for structured prediction across diverse application domains while addressing critical issues of fairness and interpretability in AI systems. Professor Getoor has advised numerous PhD students who have become active contributors to the field, including Connor Pryor, Charles Dickens, Eriq Augustine, and Varun Embar. Her research has been supported by multiple grants from major funding agencies, though specific details aren't provided in the current data. She leads research in the Statistical Relational AI (StaRAI) Lab at UC Santa Cruz, where her team develops frameworks that combine logical reasoning with probabilistic modeling to address complex real-world problems requiring both structured knowledge and statistical learning.

• Human-Computer Interaction
• Social Computing
• Artificial Intelligence
• +5 more

Bongwon Suh is a Professor in the Department of Computer Science at the Korea Advanced Institute of Science and Technology (KAIST), College of Computing. With a prolific publication record spanning over two decades, Suh has established himself as a leading researcher in Human-Computer Interaction, Social Computing, and Artificial Intelligence applications. His research interests focus on Human-Computer Interaction, Social Computing, Artificial Intelligence, Large Language Models, Information Visualization, Recommender Systems, Multi-Agent Systems, and Accessibility Technologies. Suh's work often explores the intersection of social dynamics and technological systems, examining how AI and interactive systems can enhance human experiences in diverse contexts including education, entertainment, communication, and accessibility. Recent publications (2023-2025) demonstrate a strong focus on Large Language Model applications, with significant contributions in social simulation for education, conversational AI systems, multi-agent coordination, and accessibility technologies. His work frequently appears in top-tier venues including CHI, CSCW, UIST, and SIGIR, reflecting the high impact of his research. Suh has collaborated extensively with researchers across KAIST and internationally, with frequent co-authors including Changhoon Oh, Kyusik Kim, Hyungwoo Song, and Jeongwoo Ryu. His research program consistently bridges theoretical insights with practical applications, particularly in developing systems that enhance human social experiences through technology.

• Work and Organizational Psychology
• Human-Robot Interaction
• Social Exclusion Dynamics
• +5 more

Professor Günter Maier is a distinguished academic in Work and Organizational Psychology at Bielefeld University, Germany, situated within the Faculty of Psychology and Sport Science, Department of Psychology (Unit 10 - Work and Organizational Psychology). He maintains dual affiliations with the Department of Psychology and the Research Institute for Cognition and Robotics (CoR-Lab), reflecting his interdisciplinary approach bridging psychology with robotics and artificial intelligence. His academic journey began with a Diploma (MSc) in Psychology from LMU Munich in 1992, followed by a summa cum laude Doctorate in 1996. After positions as Research Assistant, Scientific Associate, and Assistant Professor at LMU Munich, he joined Bielefeld University as Professor in Work and Organizational Psychology in 2003, where he continues his tenure. His research spans human-robot interaction dynamics, leadership behavior, corporate social responsibility, and AI implementation in workplace contexts. Professor Maier's research reveals fascinating asymmetries in human social responses to robots versus humans, demonstrating that exclusion by robot coworkers hurts less while inclusion by human coworkers satisfies more. His work on leadership examines daily behaviors and their impact on leader well-being through team identification, while his CSR research investigates relationships with employee green behavior and potential negative consequences. His recent publications increasingly focus on AI ethics in personnel selection, healthcare scheduling, and resource allocation. Methodologically, he has pioneered AI-assisted research tools, developing techniques for creating AI-generated images for vignette studies and evaluating GPT models for qualitative data analysis. His work aligns with Bielefeld University's strategic research area of the Socio-Technical World, investigating how humans, robots and AI interact in complex environments. As an educator, Professor Maier teaches across multiple Work and Organizational Psychology modules, including Basic and Advanced Applied Subject courses and Project Modules in Work, Organizational and Social Psychology. His teaching reflects his research interests, preparing students for technology-integrated workplaces through modules like 27-AF-AO1, 27-AF-AO2, and 27-AP-ProjectAOS.

Alexander SchwoererView profile

Professor

• Cardiovascular Physiology
• Cardiac Arrhythmias
• Heart Failure
• +3 more

Prof. Alexander Schwoerer is a faculty member at the University of Hamburg's Faculty of Medicine, affiliated with the Center for Experimental Medicine and the Institute of Cellular and Integrative Physiology. His research focuses on cardiovascular physiology, particularly cardiac arrhythmias, mechanical unloading effects on heart function, and calcium homeostasis. He has developed novel animal models (e.g., heterotopic heart transplantation) to study cardiac remodeling and arrhythmia mechanisms. Schwoerer also contributes to medical education, integrating interdisciplinary approaches in dental and physiological training programs. Leading research on ventricular arrhythmias and calcium signaling dysregulation Expertise in engineered heart tissue models for myocardial repair studies Key publications on nitro-fatty acids' antiarrhythmic effects and genetic influences on arrhythmia susceptibility His work bridges experimental physiology with clinical translation, emphasizing translational research methodologies. He collaborates with teams at the University Heart Center Hamburg (UKE) and the Center for Molecular Neurobiology Hamburg (ZMNH).

Elena ZuccaView profile

Associate Professor

• Programming Languages
• Type Systems
• Formal Semantics
• +6 more

Elena Zucca is an Associate Professor in the Department of Computer Science, Bioengineering, Robotics and Systems Engineering (DIBRIS) at the University of Genoa, Italy. She has a strong research focus on programming languages, particularly in the areas of type systems, formal semantics, and coinduction. Her work bridges theoretical foundations with practical implementations, as evidenced by her publications on topics like Featherweight Java, corecursion, and soundness proofs for programming language features. Her research interests span the theoretical and practical aspects of programming languages. She investigates the formal semantics of programming constructs, particularly focusing on the boundaries between finite and infinite computations. Her work on coinduction and corecursion explores how to safely handle infinite data structures and computations. She has made significant contributions to understanding soundness in programming language features, especially in relation to resource-aware semantics. Her research often combines theoretical foundations with practical implementations, as seen in her work on Featherweight Java extensions and effect systems. Analysis of her recent publications reveals a consistent focus on advanced type systems and semantics. Her work explores the theoretical boundaries of programming language features while maintaining practical relevance. A recurring theme is the relationship between finite and infinite computations, with particular attention to soundness guarantees. Her research has evolved from foundational work on lambda calculus and object-oriented programming toward more specialized topics like graded types, coeffects, and resource-aware semantics. Elena Zucca has been actively involved in the programming languages research community, serving on program committees for major conferences including SPLASH, ECOOP, and POPL. She has mentored students through doctoral courses on Declarative Programming and (Co)Induction. Her research has been supported through participation in various academic programs, including the SEPL research program mentioned in her course materials. She teaches a diverse range of courses at the University of Genoa, from undergraduate to doctoral levels. Her teaching portfolio includes Automata Theory and Computability, Algorithms Analysis and Design, Principles and Paradigms of Programming Languages, and specialized doctoral courses on Declarative Programming and (Co)Induction. Her courses often reflect her research interests, covering theoretical foundations of programming languages, formal methods, and advanced programming paradigms.

• Corporate Finance
• Executive Compensation
• Capital Structure
• +10 more

Eric R. Brisker is an Associate Professor and Department Chair at the University of Akron College of Business , specializing in Finance . With over 20 years of teaching experience, he instructs courses in Corporate Finance , Financial Analytics , and Investments , including advanced and internship programs. His research focuses on corporate finance , executive compensation , and capital structure dynamics. Education: PhD in Finance, Florida State University MA in Finance, Ohio University MBA in Finance, Ohio University BS in Finance, Shawnee State University Brisker's publications in journals like the Journal of Banking and Finance and Financial Management explore CEO inside debt, cash holdings, and financial literacy. His work connects to broader fields such as corporate governance , investment strategies , and behavioral finance . Recent articles examine corporate risk-taking in China and sin bond investments in the insurance sector. Scientific recognition includes the University of Akron College of Business Teaching Award , Research Award , and induction into Beta Gamma Sigma . He serves on editorial boards for journals like the Journal of Risk and Financial Management and has chaired multiple university and departmental committees, including Finance Department RTP Committee and Graduate/MBA Curriculum & Assessment . As a Derivative Analyst at Fifth Third Bank, he brings industry experience to academia. His grants include funding from the University of Akron Department of Finance Advisory Board and Florida State University for research travel.

• Automata Theory
• Formal Methods
• Tree Automata
• +4 more

Christof Löding is an Adjunct Professor at the Department of Logic and Theory of Discrete Systems (Computer Science 7) at RWTH Aachen University. His research focuses on automata theory, formal verification, and logical foundations of computer science, with significant contributions to Büchi automata, tree automata, and stochastic games. Academic affiliation: RWTH Aachen University, Germany Research areas: Automata theory, Formal methods, Game theory, Logic in computer science Contact: loeding@informatik.rwth-aachen.de His recent work spans deterministic parity automata construction, finite-valued transducers, and algorithmic solutions for infinite games. Publications emphasize theoretical foundations and practical applications in program verification and XML processing. Articles analyze automata learning, uniformization problems, and lookahead degrees in infinite games, showing interconnections between automata theory and formal verification.

Nathanaël FijalkowView profile

Researcher

• Games
• Machine Learning
• Automata Theory
• +9 more

Nathanaël Fijalkow is a Researcher at CNRS in LaBRI (Bordeaux) and a Research Fellow at The Alan Turing Institute in London. His primary research fields include games , machine learning , automata theory , and dynamical systems , with a focus on synthesizing programs from logical specifications and probabilistic models. Research Interests span program synthesis (programming by example), controller synthesis (temporal logic specifications), games on graphs (parity/mean payoff games), probabilistic automata (bounded ambiguity), and invariants for linear dynamical systems. He bridges formal methods with machine learning through projects like DeepSynth . Scientific Contributions include: Undecidability results for probabilistic automata Advances in parity game algorithms (quasi-polynomial lower bounds) Foundations of probabilistic modal logics Efficient synthesis techniques using SMT solvers and distributional learning Supervision involves guiding postdocs and PhD students such as Guillaume Lagarde, Antonio Casares, and Pierre Ohlmann. He has secured grants like the Momentum DeepSynth project (2019-2021) , aiming to merge formal methods with ML for program synthesis.

Johannes LangerView profile

Researcher

• Machine Teaching
• Abstract Reasoning
• Neuro-Symbolic/Hybrid AI
• +3 more

Johannes Langer is a Researcher affiliated with the Cognitive Systems Group at Faculty of Information Systems and Applied Computer Sciences , Otto-Friedrich-Universität Bamberg, Germany. His academic journey includes a B.Sc. in Psychology (Faculty of Human Sciences and Education) and subsequent roles in Computing in the Humanities. Research and Teaching Assistant (since 2024) Former Teaching Assistant (2022-2024) His research focuses on Machine Teaching , exploring how humans teach machines through sequential interactions. Additional interests include Abstract Reasoning , Neuro-Symbolic/Hybrid AI , and Representation Learning . Recent publications and workshop activities highlight his work in explanatory machine learning, inductive programming, and AI education. Article trends show interdisciplinary work bridging Cognitive Science and Computer Science , particularly in Human-Centered AI and Educational Technology . He participates in academic seminars like the Dagstuhl Seminar on Approaches and Applications of Inductive Programming.

• Automata Theory
• Formal Verification
• Logic in Computer Science
• +3 more

Christof Löding , currently an Adjunct Professor at the Lehrstuhl für Logik und Theorie diskreter Systeme (Informatik 7) department of RWTH Aachen University , is a leading researcher in Automata Theory , Formal Verification , and Logic in Computer Science . His work bridges theoretical foundations with practical applications in software verification, automata minimization, and game theory. Research Interests include automata theory, formal verification, logic, tree automata, game theory, and computational models. Publications span topics like Finite-valued Streaming String Transducers , Deterministic Parity Automata , and Stochastic Game Strategies . Collaborations with researchers like Emmanuel Filiot , Sarah Winter , and León Bohn highlight his contributions to automata and verification. Email : loeding@informatik.rwth-aachen.de He has actively published in venues such as ICALP , LICS , and STACS , focusing on deterministic automata, transducers, and logic-based computational systems. His work on Hyperlogic for Strategies in Stochastic Games (2025) and Minimal History-Deterministic Automata (2025) showcases his ongoing influence in formal methods and automata theory.

• Software Engineering
• Model Checking
• System Modeling
• +5 more

Seung Yeob Shin serves as a Research Scientist at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), where he contributes to the Software Verification and Validation (V&V) Lab under Prof. Lionel Briand. His active participation in major software engineering conferences includes serving on ASE 2025's Research Papers Program Committee and authoring multiple journal-first publications presented at premier venues like ICSE and ESEC/FSE. Shin earned his PhD in 2016 from the Laboratory for Advanced Software Engineering Research (LASER) at the University of Massachusetts Amherst's College of Information and Computer Sciences. His research expertise centers on applying formal methods to complex software systems, with particular emphasis on model-based verification techniques. His current research program bridges theoretical modeling and practical system validation across critical domains. Key focus areas include developing simulation frameworks for software-defined networks, creating model-checking approaches for cyber-physical control loops, and establishing probabilistic methods for real-time system verification. This work consistently targets reliability challenges in safety-critical infrastructure through rigorous engineering methodologies. Recent publications demonstrate a cohesive trajectory in applying formal verification to emerging system paradigms. The 2024 journal-first papers reveal increasing sophistication in handling non-deterministic behaviors across networking, embedded systems, and requirements engineering domains, with notable emphasis on failure induction and probabilistic safety guarantees. No scientific awards were documented in the available materials. While conference contributions indicate significant scholarly engagement, no information regarding student advising or research grants appears in the provided documentation. As a core member of the V&V Lab at SnT, Shin contributes to Luxembourg's national cybersecurity research infrastructure. The lab specializes in developing mathematical frameworks for system validation, with current projects addressing verification challenges in autonomous systems, critical infrastructure, and secure communications protocols through model-driven approaches.

Christian MeilickeView profile

Researcher

• Artificial Intelligence
• Knowledge Graphs
• Ontology Matching
• +5 more

Christian Meilicke is a Researcher at the Data and Web Science Group (DWS) within the School of Business Informatics and Mathematics at the University of Mannheim. His work focuses on artificial intelligence, ontology matching, and knowledge graph completion, with recent contributions to rule-based methods and their applications in business process modeling. He is heavily involved in teaching, coordinating courses such as 'Modeling Business Processes' and 'Artificial Intelligence.' His research interests include the integration of open and structured knowledge, probabilistic reasoning frameworks, and improving the efficiency of knowledge base systems. He has explored topics like inductive logic programming, automated debugging of ontologies, and the use of Markov Logic Networks for root cause analysis in IT systems. In terms of trends, his recent publications emphasize combining symbolic rule-based approaches with machine learning for knowledge graph tasks, such as activity recommendation and link prediction. He also investigates explainability in embeddings and temporal forecasting in knowledge graphs. His work often bridges theoretical advancements with practical applications in business informatics and data integration. No scientific awards have been explicitly mentioned. Christian has advised no formal students listed here but has contributed to teaching and mentoring through his courses and tutorials. His research and teaching are closely tied to the DWS Group, which focuses on data-centric AI and semantic technologies.

Roopsha SamantaView profile

Assistant Professor

• Program synthesis
• Program repair
• Concurrency
• +3 more

Roopsha Samanta is an Assistant Professor in the Department of Computer Science at Purdue University, where she leads the Purdue Formal Methods (PurForM) research group and is a core member of the Purdue Programming Languages (PurPL) group. She completed her PhD at the University of Texas at Austin in 2013 under the supervision of E. Allen Emerson and Vijay K. Garg, followed by postdoctoral research at IST Austria (2014-2016) with Thomas A. Henzinger. Her research focuses on developing foundational techniques at the intersection of formal methods and programming languages, with primary interests in: Program synthesis and repair using semantic guidance Modular verification of distributed systems Concurrency and synchronization synthesis Robustness analysis of I/O systems Her publication record shows consistent contributions across programming languages and formal methods venues, with recent emphasis on explainable program synthesis, bounded verification of distributed systems, and semantics-guided approaches to enhance synthesis robustness. Her work frequently appears in premier conferences including PLDI, POPL, OOPSLA, and CAV. Notable scientific recognitions include: NSF CAREER Award (2019) Amazon Research Award (2021) She actively advises graduate and undergraduate researchers in the PurForM group, with current students including Nouraldin Jaber, Christopher Wagner, and Yongwei Yuan. Her research is supported by grants from NSF and Amazon. Beyond research, she teaches courses on program reasoning (CS560) and neurosymbolic program synthesis (CS592), and serves on steering committees for VMW@CAV and DARS. She also co-edits the ACM SIGPLAN Blog on PL Perspectives.