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Tobias LasserView profile

Adjunct Professor

• Computational Imaging
• Inverse Problems in Tomographic Reconstruction
• X-ray Phase-Contrast and Dark-field Imaging
• +2 more

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)

Christoph HennerspergerView profile

Research Fellow

• Medical Image Computing
• Computer Vision
• Medical Robotics
• +5 more

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.

• Machine Learning
• Artificial Intelligence
• Speech Processing
• +6 more

Saeed Amizadeh is a prominent researcher specializing in artificial intelligence and machine learning, currently affiliated with Microsoft's research division. His work spans multiple domains of AI including speech processing, natural language understanding, computer vision, and time series analysis, with a particular focus on developing novel frameworks that bridge symbolic reasoning with neural approaches. Over the past decade, he has established himself as a significant contributor to the field through publications in top-tier conferences including ICASSP, ICLR, AAAI, KDD, and IJCAI. Dr. Amizadeh's research interests primarily center around advancing the theoretical foundations and practical applications of machine learning systems. His work on neuro-symbolic visual reasoning has contributed to understanding how to effectively disentangle visual perception from logical reasoning in AI systems. He has made significant contributions to differentiable programming, particularly in making classical machine learning pipelines fully differentiable, which enables end-to-end optimization of complex ML workflows. His research on speech enhancement using GANs represents cutting-edge work in audio processing, while his time series anomaly detection frameworks have practical applications in numerous industry settings. Analysis of his publication trends reveals a consistent trajectory from theoretical machine learning foundations toward increasingly applied research with practical industrial relevance. His early work (2010-2015) focused on fundamental algorithms and probabilistic modeling approaches, while his more recent publications (2019-2025) demonstrate a shift toward practical AI systems with direct applications in speech processing, audio separation, and enterprise machine learning. A notable theme throughout his career is the development of frameworks that enable more efficient, scalable, and interpretable AI systems. As a key contributor to Microsoft's ML.NET framework, Dr. Amizadeh has played an important role in developing tools that make machine learning more accessible to enterprise developers. His collaborative work spans academia and industry, with notable partnerships with researchers from various institutions as well as within Microsoft Research.

Andreas ZieglerView profile

Professor

• System Software
• Linux Configuration
• Binary Tailoring
• +6 more

Andreas Ziegler is a Professor at the Department of Computer Science (INF) of Friedrich-Alexander University Erlangen-Nürnberg. His research focuses on system software optimization , particularly in Linux kernel configurability and binary tailoring . He leads the Chair of Computer Science 4 (System Software) and develops open-source tools for minimizing software stacks while preserving functionality. University: Friedrich-Alexander University Erlangen-Nürnberg School: College of Engineering Department: Department of Computer Science Rank: Professor Research Interests: Ziegler investigates methods to automate software stack tailoring. His work spans: Configuration Interface Utilization (e.g., Linux kernel modules) Binary-Level Code Removal (ELF file manipulation without source access) Maintenance Impact Quantification (AST hashing for change detection) Publication Trends: Recent works emphasize attack surface reduction and scalable configuration testing , while earlier studies focus on feature modeling and compilation redundancy . Tools developed include GitHub-hosted open-source solutions . Advising: Supervised multiple Master’s theses on topics like header analysis for dead code detection and dynamic variability management in Linux systems.

Sara NazariView profile

Researcher

• Groundwater Modeling
• Integrated Water Resources Management
• Sustainability Analysis
• +5 more

Sara Nazari is a Researcher at the Leibniz Center for Tropical Marine Research (ZMT) , affiliated with the Working Group: Submarine Groundwater Discharge . She integrates interdisciplinary methodologies to address climate change, land use, and socio-economic impacts on water resources. Education: MSc in Water Resources Management and Engineering, Isfahan University of Technology (2015–2018) Her research emphasizes: Groundwater modeling Integrated and adaptive water resources management Sustainability analysis Big-Data analysis Conflict resolution theories Her publications focus on global groundwater recharge trends, computational models, and conflict resolution frameworks. She developed open-source tools for hydrological assessments and contributed datasets on global recharge patterns. She is based at Fahrenheitstr. 6, Bremen, Germany, and can be reached at sara.nazari@leibniz-zmt.de .

• Cybersecurity
• Dependable Computing
• Performance Evaluation
• +7 more

William H. Sanders is a Professor at the University of Illinois at Urbana-Champaign with over 35 years of research experience in cybersecurity, dependable computing, and performance evaluation. His work bridges theoretical modeling with practical security applications for critical infrastructure systems, particularly power grids and industrial control systems. Dr. Sanders' research focuses on developing quantitative methods for security assessment, with emphasis on cyber-physical systems. He is best known for his leadership in developing the Möbius modeling framework, a comprehensive tool for performance and dependability evaluation. His work spans security metrics, intrusion detection, and resilience mechanisms for smart grid infrastructure. His publication record shows consistent scholarly output through 2023, with recent work focusing on security argumentation frameworks, advanced metering infrastructure security, and cyber-physical state estimation. The research demonstrates a clear progression from foundational modeling techniques to applied security solutions for critical infrastructure protection. Dr. Sanders has collaborated extensively with researchers across multiple institutions, with frequent co-authors including Michel Cukier, Tod Courtney, and Kaustubh Joshi. His work appears regularly in top security and dependability venues including IEEE Transactions on Dependable and Secure Computing, DSN, and QEST. His research has practical implications for securing national critical infrastructure, particularly the electrical power grid. Recent projects focus on detecting electricity theft, securing advanced metering infrastructure, and developing game-theoretic approaches to intrusion response. He has made significant contributions to establishing security metrics as a rigorous scientific discipline within cybersecurity.

• Quantum Software Engineering
• Cyber-Physical Systems
• Digital Twin Technologies
• +3 more

Dr. Shaukat Ali is a leading researcher at Simula Research Laboratory (Certus Software V&V Center, Norway), with a PhD from the University of Oslo . His work bridges quantum software engineering and cyber-physical systems (CPS) validation, focusing on digital twins, autonomous vehicles, and healthcare IoT applications. Collaborates with institutions like South Dakota State University, COMSATS University, and Mohammad Ali Jinnah University Co-developed tools: QuCAT (Quantum combinatorial testing), DeepScenario (autonomous driving datasets), and EvoCLINICAL (medical digital twin evolution) Research spans quantum software testing (IBM quantum computers), uncertainty-aware validation of medical devices, and search-based optimization in CPS. His 2025 work introduces quantum circuit mutants, uncertainty-wise test oracles, and foundational models for digital twin creation. Publications in journals like ACM Transactions on Software Engineering and conferences including ICSE , GECCO , and IEEE Quantum Software reflect his interdisciplinary approach. Current projects address quantum software robustness, LLM-driven scenario realism, and safe adaptation in robotics.

• Self-Organizing Multi-Agent Systems
• Decentralized Coordination
• Distributed Systems
• +3 more

Prof. Dr. Wolfgang Renz is a faculty member at the Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Hamburg. He works on decentralized coordination mechanisms in self-organizing multi-agent systems, with applications in demand-side management, logistics, and urban mobility. Current affiliation: University of Hamburg (Informatik) Research focus: Systemic modeling, emergent behavior analysis, and validation of adaptive systems His publications cover topics like ant-colony optimization for energy management, peer-to-peer coordination spaces, and mesoscopic stochastic models for validating agent dynamics. He has supervised several doctoral and diploma theses on related subjects.

Ghang LeeView profile

Professor

• Building Information Modeling (BIM)
• Artificial Intelligence in Construction
• Information Interoperability
• +5 more

Ghang Lee is a Professor at the Department of Architecture and Architectural Engineering of Yonsei University in Seoul, South Korea. He directs the Building Informatics Group, focusing on Building Information Modeling (BIM) , AI applications in construction , and automated code compliance checking . His work bridges human expertise with artificial intelligence, advancing digital transformation in the built environment. Developed systems: Tower Crane Navigation System (TCVS), IoT-based exit signs, and NADIA (speech-to-BIM tool) Co-author of the internationally recognized BIM Handbook Recipient of Silver Medal (President of Korea) and multiple Outstanding Research Achievement Awards Research Interests span BIM, information interoperability, quality management, and AI-driven construction technologies. His recent work emphasizes: NLP for defect detection and classification Domain-specific corpus embeddings Human-AI collaboration in design Smart construction and digital twinning Building informatics standardization Visual-language models for defect analysis Scientific Awards include Silver Medal (President of Korea), Stanford/Elsevier Top 2% Scholar recognition, and multiple Outstanding Conference Paper Awards from KICEM, AIK, and KAIARI. He also holds Yonsei Distinguished Teaching Awards and Ministry of Land, Infrastructure, and Transport commendations.

Raf RamakersView profile

Associate Professor

• Human-Computer Interaction
• Digital Fabrication
• Physical Computing
• +3 more

Prof. dr. Raf Ramakers is an Associate Professor in Computer Science at Hasselt University in Belgium, affiliated with the research institute Expertise Centre for Digital Media (EDM). His research and teaching focus on Human-Computer Interaction (HCI), particularly novel software and hardware tools for ubiquitous computing devices, physical computing, and digital fabrication. Education highlights include: Ph.D. in Human Computer Interaction from Hasselt University (2016) Master in Computer Science, Human Computer Interaction (Magna Cum Laude) from Hasselt University (2012) Bachelor in Computer Science (Cum Laude) from Hasselt University (2010) His interdisciplinary research spans computer science, electrical engineering, media design, and material science, focusing on creating tools that facilitate making ubiquitous computing devices. Key areas include sensor-based systems, digital fabrication machinery, and physical interface design. Notable scientific awards: FWO IBM Innovation Award (2017) FWO Nokia Bell Scientific Prize (2017) CHI2016 Best Paper Honorable Mention 2nd Place UIST Student Innovation Contest (2013) He actively mentors PhD candidates and students, with research groups focusing on HCI and digital fabrication. His lab develops innovative tools bridging digital and physical interactions, resulting in numerous publications and patents.

Michael SelzerView profile

Researcher

• Computational Materials Science
• Phase-Field Modeling
• Research Data Management
• +7 more

Dr.-Ing. Michael Selzer is a Group Leader in Research Data Management at the Karlsruhe Institute of Technology (KIT), specifically within the Institute of Nanotechnology. He leads the Kadi4Mat project, focusing on FAIR (Findable, Accessible, Interoperable, Reusable) research data infrastructure for materials science. His work bridges computational modeling and digital research workflows. Research Interests: Michael Selzer specializes in computational materials science , with a strong emphasis on phase-field modeling for simulating microstructure evolution, fracture mechanics, and multiphase systems. His research extends to materials informatics , digital workflows , and research data management , particularly in the context of battery materials, porous media, and solid-state systems. He integrates machine learning and data science to analyze and optimize materials properties. Publication Trends: His recent publications (2023–2025) highlight a growing focus on FAIR data infrastructure (e.g., Kadi4Mat, KadiStudio), large language models in battery science (LISA), low-code simulation platforms (MUSICODE), and reproducibility in bioprinting . These reflect a strategic shift toward digitalization and automation in materials research, while maintaining a strong foundation in physics-based modeling. Scientific Contributions: Developed and advanced phase-field models for grain growth, crack propagation, and interfacial phenomena. Contributed to the development of Kadi4Mat, a research data infrastructure for materials science. Integrated machine learning and AI into materials characterization and battery research. Published extensively in journals such as Acta Materialia , Computational Materials Science , and Scientific Data . Advising and Grants: While no direct students are listed, his leadership role in Kadi4Mat suggests mentorship and team supervision. He has likely secured funding for digital infrastructure and computational materials projects, evidenced by sustained publication output and collaborative work with major institutions. His research is highly collaborative, involving teams across KIT and international partners. Labs and Teams: He leads the Research Data Management group under the Kadi4Mat initiative at KIT. This team focuses on developing digital tools for materials research, including electronic lab notebooks (KadiWeb), workflow automation (KadiStudio), and ontology-based data integration. The group operates at the intersection of computational science, data engineering, and materials discovery.

Tim GerritsView profile

Researcher

• Scientific Visualization
• High-Performance Computing
• In-Situ and In-Transit Visualization
• +7 more

Dr. Tim Gerrits is a researcher at the Institute for Visualization (VIS) at RWTH Aachen University, where he leads the Visualization Team. His work bridges scientific visualization, high-performance computing, and immersive technologies, with a strong focus on in-situ and in-transit analysis for large-scale simulations. University: RWTH Aachen University Institute: Institute for Visualization (VIS) Role: Lead of the Visualization Team Tim Gerrits' research centers on developing tools and frameworks for efficient and interactive visualization of complex scientific data. His interests include ensemble data analysis, uncertainty visualization, virtual reality interaction techniques, and leveraging game engines like Unreal Engine for scientific applications. He is particularly active in the domain of neuronal network simulations and oceanographic modeling. His recent publications highlight a strong trend toward accessible, real-time, and hybrid visualization workflows. He has contributed to the development of DaVE, a curated database of visualization examples to support HPC users, and Insite, a lightweight pipeline for in-transit processing in neuroscience simulations. His work emphasizes usability, performance, and integration with existing scientific workflows. Scientific Awards: Best Paper Award at IEEE Uncertainty Visualization Workshop, 2024 Honorable Mention Award at Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM), 2022 Dr. Gerrits actively mentors and collaborates on interdisciplinary projects involving computational neuroscience and climate modeling. He has led the curation of datasets for the IEEE SciVis Contest and promotes open science through Zenodo-hosted resources. His lab focuses on building scalable, user-centered visualization systems that empower domain scientists to gain early insights from massive simulations.

Andy SchürrView profile

Professor

• Model-based Software Engineering
• Embedded Systems
• Software Modeling Languages
• +7 more

Andy Schürr is a Full Professor at the Institute for Data Technology within the Department of Electrical Engineering and Communication Technology at Technische Universität Darmstadt. He holds a Dr. rer. nat. in Computer Science from RWTH Aachen and has held academic positions at institutions including the University of the German Armed Forces Munich and Queen’s University (Canada). His research focuses on model-based software engineering, embedded systems, graph transformation systems, and P2P technologies. Professional Activities: Co-organizer of >20 conferences/workshops Programme Committee Member for >130 conferences Editorial board member of Software & System Modeling (since 2004) Member of steering committees for GI Conference on Modeling, ICGT, and FASE Research Interests: Model-driven development of embedded systems Visual model transformation and specification languages Integration of system engineering tools Graph transformation applications in networking and real-time systems Awards & Recognition: Listed among the most cited computer scientists globally. Grants & Funding: Active in securing research funding for model-based engineering tools, graph transformation applications, and real-time systems development. Labs/Teams: Leads TU Darmstadt’s Real-Time Systems Group , focusing on model-driven prototyping and adaptive communication systems.

• In-Memory Databases
• Data Stream Processing
• Database Systems
• +12 more

Matthias Uflacker is a Professor at the Hasso Plattner Institute (HPI), University of Potsdam, Germany, where he conducts research in database systems, in-memory computing, and data-driven enterprise applications. His work bridges systems research and practical applications in Industry 4.0, education, and bioinformatics. University: University of Potsdam School: Hasso Plattner Institute Department: Department of Digital Engineering Research Focus: In-Memory Databases, Stream Processing, Causal AI, and Database Education His research interests span in-memory database systems , real-time data stream processing , GPU-accelerated analytics , and causal structure learning . He also contributes to computer science education , particularly in agile software engineering and interactive learning tools for K-12. The recent publications reflect a strong trend in enterprise data management , with a focus on benchmarking (e.g., ESPBench), performance optimization (e.g., Kafka, Hyrise), and intelligent decision support using causal models in industrial contexts. His work increasingly integrates AI for monitoring and automation in manufacturing and e-commerce. He has co-authored numerous publications in top-tier venues such as VLDB, ICDE, EDBT, and KDD, often in collaboration with Hasso Plattner and other HPI researchers. Matthias Uflacker leads and contributes to research projects on autonomous database systems , dynamic pricing simulations , and educational technology platforms for programming exercises. His team develops tools for real-time data integration, causal analysis, and classroom software engineering assessment.

Christian ZengerView profile

Professor

• IoT Security
• Wireless Communication Security
• Physical-Layer Security
• +3 more

Prof. Christian Zenger is a Junior Professor at Ruhr University Bochum's Faculty of Electrical Engineering and Information Technology, leading the Secure Mobile Networking department. He co-founded PHYSEC GmbH in 2015, developing anti-tamper radio technology for IoT security, recognized with awards from MIT, BMWi, and ECSO. His academic roles include previous positions as a Lecturer and Post-Doc researcher at Ruhr University, alongside board memberships and advisory roles in cybersecurity and water management sectors. Education: PhD in Electrical Engineering (Ruhr University Bochum, 2013–2017) Research: Focuses on IoT security, wireless systems, nuclear disarmament, and start-up ecosystems. His work bridges academic research with industrial applications, highlighted by PHYSEC's commercial success. Publications: Over 30 peer-reviewed articles since 2013, emphasizing physical-layer security, 6G vulnerabilities, and tamper detection mechanisms. Notable recent work includes anti-tamper radio systems and reconfigurable intelligent surfaces. Awards: MIT Award (2023), BMWi Innovation Prize (2022), and ECSO Security Excellence Award (2021). Advisory Roles: Member of Competence Center Digital Water Management’s Advisory Board and Cube 5’s Technical Board, reflecting his interdisciplinary impact. His lab, Secure Mobile Networking, collaborates with the Horst Görtz Institute for IT Security and promotes start-up culture through academic mentorship.