Find Academic Supervisors

Martin LacknerView profile

Researcher

• Artificial Intelligence
• Computational Social Choice
• Algorithms
• +3 more

Martin Lackner is a Researcher at the Vienna University of Economics and Business (WU Wien) within the Institute for Data, Process and Knowledge Management. He previously held postdoctoral positions at the University of Oxford and TU Wien, and earned his doctoral degree (Dr. techn.) in computer science from TU Wien in 2014. His research focuses on artificial intelligence, computational social choice, and algorithm design, with a particular emphasis on multi-winner voting systems, approval-based methods, and fairness in decision-making processes. Education: PhD in Computer Science (TU Wien, 2014), Mathematics in Computer Science studies at TU Wien, and a semester at the University of Illinois at Urbana-Champaign (USA). Research interests include computational social choice topics such as multi-winner voting, approval-based committee rules, liquid democracy, and axiomatic analysis of voting systems. He has contributed to the development of the abcvoting Python library for implementing approval-based voting rules and co-authored the book Multi-Winner Voting with Approval Preferences (Springer, 2023). His work bridges theoretical computer science with practical applications in democratic processes and algorithmic fairness. Key contributions include studies on proportional representation mechanisms, participatory budgeting fairness, and long-term decision-making frameworks. Lackner's research frequently addresses the algorithmic aspects of collective decision-making, with publications in venues like Artificial Intelligence , Journal of Economic Theory , and top conferences such as AAAI and IJCAI. Grants and Projects: Principal investigator of the FWF-funded project Algorithms for Sustainable Group Decision Making (TU Wien, 2025–present), and co-developer of the abcvoting open-source software project.

• Bioinformatics
• Computational Biology
• Genomics
• +3 more

Mark Robinson is a Full Professor for Statistical Genomics at the University of Zurich's Institute of Molecular Life Sciences. His research focuses on computational biology, bioinformatics, and genomics with expertise in RNA sequencing analysis and single-cell data science. He actively contributes to open-source tools and methodologies for genomic data processing. Key research interests include developing statistical frameworks for differential expression analysis, clustering of single-cell RNA-seq data, and integration of multi-omics datasets. His work emphasizes reproducible research practices and open-science initiatives. Notable contributions include peer-reviewed publications on single-cell data challenges and RNA-seq analysis workflows. His lab (robinsonlabuzh.github.io) develops software packages like 'conquer' and 'scRNAseq_clustering_comparison' for genomic analyses. Active on GitHub, he maintains repositories related to statistical genomics and bioinformatics tooling.

• Static Analysis
• Logic Programming
• Program Verification
• +4 more

Manuel V. Hermenegildo is a Professor at the Universidad Politécnica de Madrid, Spain. He is a prominent researcher in the field of programming languages and static analysis, with significant contributions to logic programming, program verification, and formal methods. His work focuses on advancing static analysis techniques, compiler optimization, and energy-efficient computing. He has co-authored numerous papers and organized international conferences such as LOPSTR and SAS, demonstrating his leadership in academic and research communities. His research explores topics including abstract interpretation, runtime checking, and parallel logic programming systems. He is a key contributor to the Ciao Prolog system, emphasizing comprehensive tool integration and formal methods. His research interests span static analysis frameworks, program verification, resource usage analysis, and energy efficiency in computing. He has developed methodologies for optimizing program performance while ensuring correctness, with applications in both theoretical and applied domains. His work often bridges the gap between high-level program analysis and low-level hardware constraints, particularly in embedded systems. Recent trends in his publications include advancements in static cost analysis, dynamic inference of invariants, and tools for incremental assertion checking. His collaborations with institutions like the University of Copenhagen and the University of Kent reflect a global network in advancing computational logic and software engineering. He has been actively involved in academic service, including editorial roles for conference proceedings and journals. His contributions highlight a commitment to both foundational research and practical tools for the programming language community.

• Multimedia Communications
• Self-organizing Systems
• Mobile Systems
• +7 more

Prof. Ralf Steinmetz is a Full Professor of Multimedia Communications at Technische Universität Darmstadt since 1996 and head of the Multimedia Communications Lab. His research focuses on adaptive multimedia systems, self-organizing networks, mobile/sensor networking, and educational technologies. He has held leadership roles at IBM's European Networking Center and Fraunhofer IPSI. His work spans cybersecurity, IoT, disaster communication systems, and industrial networking. Education : Dr.-Ing (PhD) in Electrical Engineering, TU Darmstadt (1986) Habilitation in Computer Science, Goethe University Frankfurt (1994) Research Interests : He pioneers innovations in networked multimedia systems , including fault-tolerant communication, aerial-ground disaster monitoring (e.g., CAMON system), and 5G/Industry 4.0 infrastructure. His work emphasizes resilience, adaptive protocols, and cyber-physical integration. Recent Work Trends : Publications from 2022-2025 highlight advancements in: Wireless communication protocols (ESP-NOW, LoRa) Cybersecurity (intrusion detection via machine learning) Disaster response networks (aerial-ground cooperation) Time-sensitive networking for industrial applications Key Contributions : Developed Nature 4.0 sensor systems for biodiversity monitoring Pioneered P4-programmable network hardware solutions (P4-CODEL, P4-BNG) Advanced UAV-based emergency communication frameworks

Konstantin NestmannView profile

Research Fellow

• Quantum Thermodynamics
• Open Quantum Systems
• Quantum Information
• +3 more

Konstantin Nestmann is a Postdoctoral Researcher in the Department of Physics at Lund University's Faculty of Engineering since 2023, funded by an EU Marie Skłodowska-Curie fellowship. His research focuses on quantum thermodynamics and open quantum systems using techniques from statistical field theory and quantum information. His educational background includes a PhD in Physics (summa cum laude) from RWTH Aachen University (2018-2022) and a combined BSc and MSc in Physics from Dresden University of Technology (2011-2018). His doctoral thesis addressed the dynamics of open quantum systems from quantum information and statistical physics perspectives. Nestmann's research centers on non-perturbative quantum master equations, quantum non-Markovianity, and quantum thermodynamics. He develops theoretical frameworks and computational tools, such as the RealTimeTransport library, to study quantum transport in the strong coupling regime. His work bridges fundamental quantum dynamics with practical applications in nanoelectronics. His publication record from 2019 to 2024 reveals a consistent focus on the interplay between time-local and time-nonlocal descriptions of quantum dynamics, with significant contributions to renormalization group methods and fermionic duality. These works span exact solutions for open quantum systems, non-perturbative approximations, and numerical implementations. Scientific awards include: Marie Skłodowska-Curie fellowship Nestmann has served as a lead teaching assistant for Quantum Information and Introduction to Theoretical Physics, and as a teaching assistant for Statistical Physics and Quantum Mechanics. His research is supported by the Marie Curie fellowship and collaborative projects with institutions including RWTH Aachen and Forschungszentrum Jülich. He is an active member of the quantum transport and open systems research community, contributing to open-source software development and collaborative theoretical advancements.

Olaf LandsiedelView profile

Professor

• Distributed Systems
• Wireless Sensor Networks
• Peer-to-Peer Systems
• +4 more

Olaf Landsiedel is a Full Professor and head of the Distributed Systems Group at Kiel University, where he leads research in distributed computing, wireless sensor networks, and peer-to-peer systems. He has been a key contributor to the field since joining COMSYS in 2006 and earning his PhD in 2010. His research interests center on enabling accurate, scalable, and energy-efficient network simulations and protocols. He focuses on bridging the gap between simulation and real-world deployment, improving timing accuracy, modeling power consumption, and designing robust communication for unstable wireless environments. His work emphasizes modularity, flexibility, and reliability in distributed systems. The 15 most recent publications reflect a strong trend toward enhancing simulation fidelity, addressing bursty wireless links, enabling dynamic software updates in sensor networks, and developing tools for realistic experimentation. His work spans both theoretical models and practical implementations, often validated through simulation frameworks and testbeds. Olaf Landsiedel has advised numerous students on topics ranging from routing protocols to modular communication frameworks and ontology design, primarily during his time at RWTH Aachen University. While no specific grants are mentioned, his sustained publication record suggests consistent research funding and collaborative projects. He leads the Distributed Systems Group, which conducts cutting-edge research in network simulation, protocol development, and sensor network reliability. The group's work includes tools like KleeNet for bug detection and Horizon for parallel simulation, indicating a strong focus on practical system building and validation.

Arnold Arz von StraussenburgView profile

Researcher

• Internet of Things (IoT)
• Artificial Intelligence
• Data Integration
• +3 more

Arnold Arz von Straussenburg is a Researcher at the University of Koblenz, Department of Business Information Systems and Smart Data, since October 2022. He holds an M.Sc. and has experience in academic and corporate roles, including student assistantships at the Universities of Koblenz-Landau and Münster, and working as a tutor and working student in software development and verification training. His research focuses on IoT data platforms, AI integration, sensor technologies, and educational technology. He has contributed to projects like responsible LLM-based grading systems, CO2-based occupancy detection in smart spaces, and hybrid architectures for AI-driven chatbots. His work emphasizes practical applications of technology in education and urban environments. Education includes studies in Business Information Systems, reflected in his roles as a member of the Board of Symposium Oeconomicum Münster eV and his academic publications. His research spans IoT interoperability, AI literacy, and high-availability data architectures. Key research trends in his articles include leveraging IoT for smart city solutions, integrating large language models ethically in education and chatbots, and optimizing sensor-based systems for workplace efficiency. He has developed frameworks for evaluating conversational agents and improving data model flexibility in IoT systems. Arnold has no listed scientific awards but has been actively involved in collaborative projects and academic organizations. His work on automated application deployment and sensor-based smart parking demonstrates his interest in both theoretical and applied computing.

Daniel StrüberView profile

Associate Professor

• Model-Driven Engineering
• AI Engineering
• Software Quality Assurance
• +7 more

Daniel Strüber is an Associate Professor in Software Engineering at Chalmers University of Technology and the University of Gothenburg, Sweden, and an affiliate of the Department of Software Science at Radboud University Nijmegen, Netherlands. His research focuses on model-driven engineering, AI engineering, and empirical software engineering, addressing challenges in software quality, variability management, and security. He holds a PhD (summa cum laude) from Philipps University Marburg and has held academic positions including Assistant Professor at Chalmers and postdoctoral roles at King's College London and Philipps University Marburg. Education: PhD in Computer Science, Philipps University Marburg (2011–2016) Diplom (M.Sc. equivalent) in Computer Science, Philipps University Marburg (2005–2011) Research Interests: Strüber's work spans model-driven engineering, AI integration in software systems, and empirical studies. Key areas include: Model-based languages and tools for software quality assurance Machine learning-enabled systems and their engineering principles Robotics software engineering and variability management Formal methods for consistency and security Search-based optimization in model-driven development Recent Contributions: Recent work includes studies on LLM-assisted reverse engineering, empirical analysis of manual abstraction in software systems, and model-driven approaches for edge deployment of ML models. His research bridges theory with practical implementations in domains like robotics and web-based systems. Awards: Best Reviewer Award (SoSyM 2025) Distinguished Reviewer Awards (GPCE 2024, SPLC 2023) Transformation Tool Contest Awards (2020, 2016) EASST Best Paper Awards (ICGT 2020, ICGT 2017) Grants & Leadership: Co-editor of a JSS special issue on Product Line Engineering (2024) and program co-chair of SPLC 2024. Active in conferences like ICSE, ICGT, and MODELS. Leads grants such as the VR SEMLA project (2022–2024) and the DFG EUphORia fellowship (2019). Teaching: Courses include 'Software Engineering for AI Systems' at Chalmers and 'Software Product Lines' at Radboud University. Involves students in real-world projects via GiPHouse, a student-run company.

• Clothing Technology
• CAD Pattern Construction
• Technical Textiles Manufacturing
• +3 more

Prof. Katerina Rose is a Professor of Clothing Technology & CAD at Reutlingen University's TEXOVERSUM School of Textiles. She leads the Department of Clothing Technology and CAD, focusing on innovative textile design methodologies. Her expertise includes 3D pattern construction, technical textiles manufacturing, and AI-driven garment design. Her research emphasizes digital avatars for clothing simulation, low-cost 3D scanning technologies, and soft tissue modeling. Notable projects include the InBiO initiative for bio-based automotive interiors and the FLAX365 regional textile chain initiative. She holds a patent (DE102020119338A1) for patternless garment cutting methods. Teaching areas: Clothing Technology, CAD Pattern Construction, Technical Textiles Manufacturing Labs: Sewing & CAD Lab, Material Testing Lab, Electronic Textiles Lab Key collaborations: Hometrica Consulting, SciTePress, Browzwear Recent work explores microwave imaging for body dimension capture and AI-enhanced pattern generation, published in journals like Communications in Development and Assembling of Textile Products. Her contributions bridge textile engineering with digital innovation in fashion and medical applications.

• Digital Piracy and Innovation
• Intellectual Property
• Software Industry
• +5 more

Wendy A. Bradley is an Assistant Professor of Strategy, Entrepreneurship and Business Economics at Southern Methodist University's Cox School of Business, where she is affiliated with the Strategy & Entrepreneurship Department. Her research bridges the fields of innovation economics, intellectual property, and entrepreneurial finance with a particular focus on how digital piracy affects innovation in knowledge-based industries. Dr. Bradley's research interests span digital piracy and innovation, intellectual property, software industry dynamics, entrepreneurship, venture capital, cross-border investments, and metaverse trademark issues. Her work employs rigorous empirical methods including natural experiments, difference-in-differences, and instrumental variables to analyze how firms respond to competitive threats in digital markets. Her publication record shows a clear trajectory examining how digital piracy affects innovation across different industries, from software firms to the movie industry. She has explored how piracy impacts R&D spending, copyright and trademark strategies, and new product development across multiple sectors. More recently, her research has expanded into metaverse trademark dynamics and gender differences in entrepreneurship in developing economies. Dr. Bradley has received significant scholarly attention for her work on piracy and innovation, with her papers appearing in prominent research series including USPTO Economic Working Papers and SMU Cox School of Business Research Papers. Her research has been cited by scholars examining the relationship between piracy and innovation across various industries. She actively collaborates with researchers from diverse institutions including the United States Patent and Trademark Office, Monash University, and the University of Oxford. Her work demonstrates strong methodological rigor and relevance to both academic theory and practical business strategy in knowledge-intensive industries facing digital disruption.

• In-flight ice accretion
• Numerical simulation and optimization of electro-thermal ice protection systems (ETIPS)
• Icing wind tunnel testing and measurement techniques
• +6 more

Mariachiara Gallia is a Research Fellow at the Institute of Fluid Mechanics , Technische Universität Braunschweig , Germany. She specializes in in-flight ice accretion and numerical simulation of electro-thermal ice protection systems (ETIPS) for aerospace applications. Research Focus: Ice accretion modeling, robust optimization, uncertainty quantification, CFD, machine learning for fluid dynamics, ice roughness characterization. Projects: Participated in the European ICE-GENESIS project; currently co-supervises Ph.D. students in the MSCA DN-JD TRACES project. Education: Holds a Ph.D. in Aerospace Engineering from Politecnico di Milano, Italy. Her work spans numerical frameworks for ice protection systems, icing wind tunnel testing , and roughness effects on heat transfer . Key publications address robust optimization under uncertain cloud conditions, machine learning in fluid dynamics, and modular ETIPS designs for wind turbines.

Vivek SarkarView profile

Professor

• Parallel Computing
• Heterogeneous Computing
• High-Performance Computing
• +5 more

Vivek Sarkar is currently the Chair of the School of Computer Science and the Stephen Fleming Chair for Telecommunications in the College of Computing at Georgia Institute of Technology. His career spans both industry and academia, with significant contributions to parallel computing, including programming models, compilers, and runtime systems. Ph.D. from Stanford University (1995-2007: IBM Academy of Technology member) 2007-2017: Chair of Computer Science Department at Rice University 2017-present: Georgia Institute of Technology Research Interests focus on programmability and productivity in parallel, heterogeneous, and high-performance computing systems. His work encompasses: Programming language design (e.g., X10, Habanero-C/C++) Compiler optimization and runtime systems Formal verification for parallel programs Education initiatives (Coursera specialization on parallel programming) Recent Publications highlight verification techniques in compilers, machine learning integration for code optimization, and Rust-based interfaces for distributed C++ systems. Scientific recognitions include: ACM Fellow IEEE Fellow 2020 ACM-IEEE CS Ken Kennedy Award He has mentored over 30 Ph.D. students/postdocs and leads the Habanero Extreme Scale Software Research Laboratory , which develops scalable parallel programming frameworks. Current advisory roles include: US Department of Energy’s ASCAC (2009-present) Computing Research Association (CRA) Board (2015-2022) Founding co-chair of CRA-Industry committee (2021)

• Educational Technology
• Collaborative Learning
• Computer-Supported Learning
• +3 more

Markus Kuhn is a researcher at the University of Cambridge with a diverse academic career spanning over two decades, evidenced by publications from 2003 to 2023. His work bridges educational technology, computer science, and autonomous systems, demonstrating significant interdisciplinary reach across multiple domains. Dr. Kuhn's research has evolved through distinct phases. Initially focused on educational technology (2003-2007), he published extensively on classroom scenarios, collaborative learning, and media integration. His work then broadened to include physics computation (2008) and process support for inquiry learning (2010). More recently (2016-2023), his research has shifted toward autonomous systems, with publications on self-localization technologies and map generation for autonomous vehicles. This publication trajectory reveals a researcher who has successfully adapted his expertise from educational applications to more technical domains while maintaining connections to his foundational work in learning systems. His research demonstrates consistent innovation in applying computational approaches to solve practical problems across different contexts. Dr. Kuhn has maintained long-term collaborations with researchers including Heinz Ulrich Hoppe, Andreas Harrer, and Andreas Lingnau, indicating strong interdisciplinary networks. His work has been published in diverse venues ranging from IEEE Access and Microelectronics Reliability to Research and Practice in Technology Enhanced Learning and International Conferences on Computer-Supported Collaborative Learning.

• Knowledge Representation
• Ontology Engineering
• Semantic Web
• +6 more

Cassia Trojahn is a permanent Lecturer at the University of Toulouse 2 Jean Jaurès , affiliated with IRIT - UMR 5505, Department of Mathematics and Computer Science. Her career spans institutions in France, Portugal, Brazil, and the Netherlands, with roles including Expert Engineer at Joseph Fourier University and Post-Doc at INRIA Rhône-Alpes. Education Semantic Web, Ontology Alignment, Business Intelligence (University of Toulouse) Functional Programming (Haskell, Scala), Information Extraction (Pierre Mendès University) Graph Theory and Complexity (University of Évora) Research Interests : Knowledge representation and semantic web technologies Ontology alignment methodologies (argumentation, complex alignments, holistic approaches) Earth observation data integration with contextual information Open science and FAIR data principles Argumentation frameworks for mapping reconciliation Query rewriting with complex correspondences Advising : Co-supervised 5 PhD theses across France and Brazil, including: Jordane Dorne (2018-2021) - Earth observation semantic change detection Élodie Thiéblin (2016-2019) - Complex ontology alignment Roger Granada (2011-2015) - Hierarchical relations extraction Projects : Participated in international (CAMELEON, MULTIFARM) and European (EFFECTOR, CANDELA, SEALS) projects focused on multilingual ontology alignment, maritime situational awareness, and semantic earth observation data analysis.

• Digitalization in Physical Education
• Media Pedagogy
• Hockey Instruction
• +3 more

Konstantin Rehlinghaus is a researcher at the Institute of Sport Didactics and Physical Education at German Sport University Cologne. His work bridges physical education, digital media integration, and curriculum development, with a focus on media pedagogy and hockey instruction. Research: Specializes in digitalization trends in school sports, AI applications in teaching, and hockey education. Teaching: Involved in bachelor's and master's programs, offering seminars on inclusion in sports, hockey, and practical training. Publications: Recent works include a monograph on field hockey and studies on AI in lesson planning. Awards: Recipient of the 2016 TutorInnenpreis for educational excellence. Activities: Regularly participates in conferences, organizes symposia, and delivers guest lectures on media competence and AI in education.