Dr. Andrey Sobolev is a PostDoc researcher at the Faculty of Biology, Ludwig Maximilian University of Munich, affiliated with the Benedikt Grothe Research Group. His work focuses on neurophysiological data management, electrophysiological data handling, and neural systems analysis. Key contributions include developing the Neo Python library for electrophysiology data handling and the G-Node Python Client for reproducible research workflows. Research interests span computational neuroscience, data management systems, and behavioral paradigms in freely moving animals. Notable publications include studies on hippocampal ensemble remapping under sensory conflicts (2021), the Sensory Island Task behavioral paradigm (2020), and metadata standards in neurophysiology (2016). Technical contributions include creating integrated platforms for electrophysiological data storage (2014) and foundational database systems for biomedical applications (2011). Collaborates widely with neuroscientists and software engineers to advance open science practices in neuroscience research.
Richard Bubel is a Researcher in the Software Engineering group at Technische Universität Darmstadt. His work focuses on formal methods, deductive verification, and automated theorem proving with applications in software engineering and smart contract development. He has contributed to the KeY verification tool and is involved in projects like SF 4.0 and KeY's development. Bubel has participated in numerous academic committees and reviewing activities, including roles in TASE, FMSPLE, and the KeY Symposium. His research interests span formal specification, program analysis, and security, with a particular emphasis on ensuring software reliability through rigorous verification techniques. His affiliations include: Technische Universität Darmstadt, Department of Computer Science KeY Project (main developer and coordinator) European research initiatives (EU FP7, COST IC0701) Research Interests: Formal methods, deductive verification, automated theorem proving, software engineering, smart contracts, and program analysis. Key contributions include the development of the KeY verification tool, formalization of Java strings, and work on trace-based verification. His community involvement includes organizing conferences and workshops, such as the KeY Symposium and HATS Annual Meeting.
Michael Haustermann is a Researcher at the University of Hamburg's Faculty of Informatics, within the Theoretical Foundations Group. His work focuses on Petri net-based modeling tools, software engineering methodologies, and domain-specific languages. He contributes to the development of the Renew toolset for Petri net modeling and simulation, emphasizing formal methods and their application in collaborative systems. His research spans IoT architectures, agent-oriented software systems, and education technologies like adaptive testing frameworks (VideoFOS and FormAdTe). He has published extensively on Petri net applications in concurrency, software engineering, and system design, collaborating with institutions globally. Current projects include advancing Petri net tools for model-based development and exploring edge computing architectures.
Dr. Hariprasath Ganesan is a Senior Scientist at the Research Center Jülich, affiliated with the Institute for Advanced Simulation (IAS) and the Materials Data Science and Informatics (IAS-9) department. His expertise spans Atomistic Simulations, Nanomechanics, and Materials Informatics, focusing on computational modeling of materials' behavior under extreme conditions. He leads research into high-temperature deformation mechanisms in advanced alloys like TiAl, leveraging multiscale simulation techniques such as molecular dynamics and Monte Carlo methods. His work emphasizes GPU-accelerated computational approaches for atomistic simulations, improving efficiency in studying solute segregation, interface dynamics, and thermal-mechanical properties. Recent studies include ultrafast laser-material interactions and creep behavior in nanomaterials. Collaborations bridge theoretical models with practical applications in materials design and additive manufacturing. Publications highlight contributions to understanding lamellar interface stability, Cottrell atmosphere formation, and parallel computing frameworks for scale-bridging simulations. His research aligns with Helmholtz energy and materials science initiatives, advancing computational tools for next-generation materials discovery.
Björn Fiedler is a Lecturer at Leibniz Universität Hannover's Department of Computer Science, specializing in Real-Time Systems and Operating System Engineering. He leads the SRA Group and focuses on static analysis, compiler optimization, and embedded systems specialization. His work emphasizes improving non-functional properties of system software through automated hardware abstraction and compiler-driven specialization. Education: PhD in Computer Science (Leibniz Universität Hannover, 2023). Research Interests: Real-Time Operating Systems (RTOS), multi-core specialization, system call optimization, static analysis, and compiler frameworks like ARA. His projects include AHA (Automated Hardware Abstraction) and MultiSSE, targeting performance and predictability in embedded and real-time systems. Publications: Focus on static analysis techniques, RTOS optimization, and compiler-driven system specialization. Notable work includes ARA's whole-system compiler framework and the MultiSSE syscall elision method. Awards: Best Paper Award at OSPERT 2018 Advising: Supervised 8+ theses on topics like static system object instantiation, sparse data structures, and FreeRTOS kernel specialization. Active in grant projects funded by DFG (e.g., AHA: LO 1719/4-1). Labs/Teams: Core member of the SRA Group, collaborating on projects involving LLVM-based compilation, embedded RTOS development, and real-time system analysis.
Leif Bonorden is a Research Associate and Doctoral Student at the Department of Informatics, Faculty of Mathematics, Computer Science and Natural Sciences, University of Hamburg. He works within the Software Engineering and Construction Methods research group led by Professors Matthias Riebisch and André van Hoorn. His academic background includes a B.Sc. and M.Sc. in Mathematics from Technische Universität Berlin (2010-2018), with thesis work in Probability Theory and Functional Analysis. Since 2019, he has been pursuing doctoral research at the University of Hamburg while also studying for an M.A. in Higher Education. 2010-2018: Student, B.Sc. and M.Sc. Mathematics, Technische Universität Berlin 2012-2015: Student Teaching Assistant, Software Engineering group, TU Berlin 2015-2017: Assistant Researcher, FZI Forschungszentrum Informatik 2019-present: Research Associate & Doctoral Student, University of Hamburg 2020-present: M.A. Higher Education student, University of Hamburg Bonorden's research centers on API evolution and deprecation processes, with particular focus on how deprecated web APIs can be detected through tracing techniques. His work bridges theoretical software engineering with practical applications in API design and documentation. He has developed expertise in systematic mapping studies of API deprecation practices and their impact on software maintenance. His publication record demonstrates consistent focus on API-related research, with multiple systematic studies and empirical analyses. He has also contributed significantly to software reengineering knowledge through the SREBOK initiative and explored innovative educational approaches for teaching software engineering concepts through research-based learning. Active member of Software Engineering and Construction Methods research group Contributor to German Informatics Society's software reengineering special interest group Member of ACM, GI (Gesellschaft für Informatik), and DMV professional organizations Bonorden serves on multiple university committees including the Committee for Teaching and Studies, Building Committee, Faculty Council, and various examination boards for computer science programs. His teaching portfolio includes Software Design, Introduction to Software Engineering, and Bachelor Seminars in Software Engineering at both University of Hamburg and TU Berlin.
Florian Kern is a PhD candidate in Human-Computer Interaction at the University of Würzburg, supervised by Prof. Marc Erich Latoschik. He holds an M.Sc. in Computer Science focusing on HCI (2018). His research centers on Extended Reality (XR), particularly text input methods, surface alignment for handwriting/sketching, and VR applications in rehabilitation. Key projects include the Off-The-Shelf Stylus framework for XR interaction and the Reality Stack I/O modular framework for cross-platform XR development. Research Interests: XR Interaction: Handwriting/sketching in VR/AR, physical-virtual surface alignment. Rehabilitation Technology: VR-based gait training (e.g., Homecoming application for MS/stroke patients). Framework Design: Cross-platform tools like Reality Stack I/O, modular animation pipelines. User Experience: Evaluating input techniques, sketching behavior, and usability in immersive systems. Publications emphasize technical innovations (e.g., stylus calibration, surface refinement) and interdisciplinary applications (e.g., healthcare VR). Collaborations span HCI, psychology, and engineering departments.
Sarath Menon is a computational materials scientist at Ruhr-University Bochum and Max-Planck-Institut für Eisenforschung GmbH. His work focuses on atomistic simulations, machine learning interatomic potentials, and thermodynamic property calculations. He contributes to open-source software like pyiron and pace. Doctor of Engineering, Mechanical Engineering (2021) Master of Science, Materials Science and Simulation (2018) Bachelor of Technology, Mechanical Engineering (2012) His research centers on developing machine learning potentials for thermodynamic modeling, with applications in phase diagrams and nucleation studies. He employs methods like transition path sampling and hyperdynamics. Menon teaches Python programming, electronic structure methods, and atomistic simulation techniques. He has organized workshops on reproducible workflows and quantum mechanics in solid-state physics. Key software contributions include: pyscal : Structural analysis tool for atomic environments pace : High-performance Atomic Cluster Expansion implementation calphy : Free energy calculation library atomRDF : Ontology-based structure manipulation
Ralf Hielscher is a Professor at the Institute of Applied Analysis within the Faculty of Mathematics and Computer Science at the Technical University of Freiberg, Germany. His research lies at the intersection of applied mathematics, materials science, and imaging, with a strong focus on crystallographic texture analysis and electron backscatter diffraction (EBSD). He is a core developer and leading figure behind MTEX, a widely used open-source MATLAB toolbox for texture and orientation data analysis. Research Interests: His work centers on mathematical methods for analyzing crystallographic orientations, including spherical harmonic transforms, kernel density estimation on rotation groups, manifold-valued data processing, and inverse problems in tomography and texture reconstruction. He develops algorithms for parent grain reconstruction, orientation mapping, denoising, and visualization of microstructures. The recent publications reveal a consistent trend in advancing computational techniques for EBSD and texture analysis, particularly through the MTEX platform. His work bridges theoretical mathematics with practical materials characterization, enabling more accurate and efficient analysis of polycrystalline materials across geology, metallurgy, and engineering. Email: ralf.hielscher@math.tu-freiberg.de Scientific Contributions: While no formal awards are listed, his extensive publication record in high-impact journals such as SIAM Journal on Imaging Sciences , Journal of Applied Crystallography , and Inverse Problems underscores his significant contributions to the field. He has developed foundational algorithms now embedded in MTEX, which is used globally by researchers in materials science and geology. Teaching and Advising: He teaches courses such as Function Theory, Analysis 3, and Mathematics for Engineers. Although specific students are not mentioned, his leadership in MTEX and numerous collaborative publications suggest he mentors researchers and contributes to training the next generation of scientists in computational materials analysis. Labs and Teams: He is part of the team at the Institute of Applied Analysis and leads research efforts related to signal and image processing in crystallography. The MTEX project serves as a virtual research platform involving international collaborators in Germany, France, the UK, and beyond, facilitating open science in texture analysis.
Stephan Zelewski is a full Professor at the Faculty of Business and Economics of the University of Duisburg-Essen since 1998 and head of the Institute for Production and Industrial Information Management. He studied business administration and economics at the Universities of Münster and Cologne (1977-1981), earning two diplomas with distinction. Key Research Areas : Production Management, Logistics, Industrial Information Systems, Semantic Knowledge Management, AI/Operations Research applications in business, and Game Theory-based fair distribution models. Academic Leadership : Dean of Studies (1993-1996), founder of the Ruhr Campus Academy (2001-2002), and chair of multiple research projects including KI-LiveS (AI brainware development) and OrGoLo (Semantic Knowledge Management in logistics). Recent Articles focus on AI-based knowledge reuse systems, e-mobility sustainability analysis, and semantic modeling tools. His work integrates Artificial Intelligence with Operations Research and Game Theory across logistics and production domains. Scientific Recognition : Multiple scholarships (Konrad Adenauer, Hoechst, Fritz Honsel Foundations) Cologne University Prize (1992) Leadership in academic associations (VHB, Wissenschaftliche Kommission Wissenschaftstheorie)
Nikolas Zöller is a research scientist at the Max Planck Institute for Human Development 's Adaptive Rationality department. His work focuses on collective intelligence, human-AI collaboration, and computational modeling of social systems. He combines methods from physics, computer science, and psychology to study decision-making processes in both natural and artificial collectives. Ph.D. candidate at Constructor University Bremen (2020-2024) Research Associate at Potsdam University of Applied Sciences (2015-2022) Master of Science in Physics from Freie Universität Berlin (2014) Bachelor of Science in Physics from Freie Universität Berlin (2010) His research spans: Collective intelligence frameworks Human-AI collaborative diagnostics Agent-based modeling of social networks Technological co-diffusion patterns Thermodynamic optimization in physical systems Recent publications highlight his work on: Diagnostic accuracy in human-AI collectives GitHub collaboration topology Affect control theory in group dynamics Co-diffusion of complementary technologies Scientific recognition includes: European Press Prize (2022) as part of a team Springer Best Masters Award (2014)
Shweta Suran is a Postdoctoral Fellow at the Max Planck Institute for Human Development (Berlin, Germany) with affiliations as an External Researcher at Tallinn University of Technology (School of Information Technologies, Department of Software Science) and IT University of Copenhagen (Collective Intelligence Research Group). She previously held roles at TalTech, The Open University (UK), and Krishna Engineering College. Doctor of Philosophy (2022) in Computer Science, Tallinn University of Technology Research Master's Degree (2014) in Knowledge Engineering, SRM Institute of Science and Technology Her research focuses on Collective Intelligence, Collective Behaviour, Social Network Analysis, Data Mining, and Digital Image Processing. She explores how individuals interact with online content, the impact of conversational affordances on deliberation quality, and correlations between social media preferences, media choices, and socio-economic/political factors. Her recent publications include work on a digital collaborative platform for the silver economy (2023), frameworks for collective intelligence (2020), pathfinding in medical imaging (2014), and AI applications in spatial data infrastructure (2019-2021). She co-supervised Sijo Arakkal Peious (2019 Master's thesis). Marie Skłodowska-Curie Postdoctoral Fellowship (2024) Seal of Excellence from European Commission (2023) SAP Fellowship Award (2016) Gold Medal at SRM University (2014) She contributed to projects like the EU Green Deal-aligned Waterway Safety Management program (2020-2021) and cost-effective 3D spatial data infrastructure (2019-2021), with funding totaling €1,996,000. Her work bridges ICT, collective behavior, and societal challenges.
Steve Riddle is a Research Professor with extensive contributions to software engineering, systems of systems (SoS) modeling, and requirements engineering. His work spans formal methods, traceability frameworks, and safety-critical system design across institutions and projects. Active in software traceability and requirements engineering Key contributor to SoS architectural modeling Collaborator in formal methods education initiatives His research focuses on traceability in software systems , contract-based analysis of SoS , and protective wrapping for off-the-shelf components . He explores how project metrics predict change-proneness and develops frameworks for competency-based computing education. Recent publications analyze team-based capstone projects in computing education and instructor perspectives on software engineering pedagogy. His work bridges theoretical approaches (like VDM++) with industry-aligned problem-solving .
Prof. Dr. Tobias Lasser is an Adjunct Professor at the Technical University of Munich (TUM) since 2024, leading the Computational Imaging and Inverse Problems research group. He holds affiliations with the TUM School of Computation, Information and Technology and the Munich Institute of Biomedical Engineering. His academic career includes a PhD (2011) and habilitation (2017) in Computer Science from TUM, along with prior roles as a Postdoctoral Fellow and Akademischer Rat at TUM's Chair for Computer Aided Medical Procedures. His research focuses on computational imaging , inverse problems in tomography , and clinical decision support systems . Key areas include X-ray phase-contrast/dark-field imaging, light field microscopy, and multi-modal medical data analysis. Notable contributions include advancements in sparse-view CT reconstruction, artifact-free deconvolution techniques, and AI-driven diagnostic tools. Recent work emphasizes integrating deep learning with traditional imaging modalities, such as encoder-decoder architectures for anomaly detection and attention-based models for skin lesion classification. His team also explores robotic sample holders for advanced CT setups and open-source frameworks like elsa for tomographic reconstruction. Educations: Diplom-Informatiker (2006), Diplom-Mathematiker (2008), Dr. rer. nat. (2011, summa cum laude), Habilitation (2017) Awards: IEEE editorial award (2023), Best Poster (2021), Supervisory Excellence (2021), Teaching Award (2021) Labs/Teams: Munich Institute of Biomedical Engineering, Computational Imaging Group (TUM)
Dr. Christoph Hennersperger is a Co-Founder and CTO of OneProjects, an Irish-German MedTech startup focused on cardiac imaging and data-driven healthcare solutions. He is affiliated as a senior research scientist and lecturer at the Chair of Computer Science Applications in Medicine (Prof. Navab) at Technical University of Munich (TUM). His research integrates medical device development, computational sonography, and robotics in surgical applications. He has directed the MedInnovate fellowship program and led the EU Horizon2020 EDEN2020 project. Education: Electrical Engineering (Information Technology) from TUM (2006–2011). Professional History includes roles as a Research Fellow at Trinity College Dublin (2016–2019), Research Manager at Klinikum Rechts der Isar (2016–2018), and Fellow at BioInnovate Ireland (2015–2016). He has supervised over 20 MSc/BSc theses on topics like Ultrasound-Guided Interventions and Surgical Robotics. Teaching: He has lectured since 2014 on courses including Computer Aided Medical Procedures , Medical Augmented Reality , and MedInnovate . Research focuses on 3D ultrasound imaging, robotic interventions, and AI-driven medical solutions. Current projects include RoBildOR (robotics for multimodal imaging) and SUPRA (real-time ultrasound processing). Key innovations include the SegThy Dataset and Leg-3D-US Dataset for medical imaging, and developments in 3D ICE imaging for cardiac interventions. His work bridges hardware, software, and clinical needs, emphasizing collaborative team-driven healthcare innovation.
