جست‌وجوی استاد و پژوهشگر

Johannes Flickمشاهده پروفایل

عضو هیئت علمی

• Light-Matter Interactions
• Quantum Physics
• Density Functional Theory
• +۳ مورد دیگر

Johannes Flick is an Assistant Professor at the City College of New York and an Associate Research Scientist at the Center for Computational Quantum Physics within the Flatiron Institute . His work bridges quantum optics , electronic structure theory , and quantum information processing , focusing on light-matter interactions in the strong-coupling regime . Ph.D. in Theoretical Physics, Fritz Haber Institute and Humboldt University, Berlin Diploma in Physics, Karlsruhe Institute of Technology Postdoctoral Researcher, Max Planck Institute for the Structure and Dynamics of Matter DFG Postdoctoral Fellow, Harvard University Research Interests : Johannes develops quantum-electrodynamical density-functional theory (QEDFT) methods to model strongly coupled light-matter systems , with applications in catalysis , spectroscopy , and quantum technologies . His work explores nonlinear light-matter coupling , excited-state nanophotonics , and polaritonic chemistry . Article Trends : Recent publications emphasize QEDFT extensions , machine learning-driven functionals , and quantum simulations in cavity environments , covering electron-photon interactions , defect dynamics in diamond , and topological optical resonances in 2D materials.

Alexander Bernshteynمشاهده پروفایل

استاد آموزشی

• Artificial Intelligence
• Machine Learning

Alexander Bernshteyn serves as a Professor of the Practice at the Artificial Intelligence Center of Skolkovo Institute of Science and Technology (Skoltech), focusing on applied artificial intelligence research and development. Research Interests: Bernshteyn's work centers on Artificial Intelligence with emphasis on Machine Learning methodologies. His research bridges theoretical AI frameworks and practical implementations, targeting real-world problem-solving across technological domains. He is embedded within Skoltech's Artificial Intelligence Center, contributing to the institution's strategic AI initiatives and collaborative projects.

• Robotics
• Human-Machine Interaction
• Deep Learning
• +۳ مورد دیگر

Prof. Hans-Joachim Böhme serves as a Professor in the Department of Mathematics at Dresden University of Applied Sciences' Faculty of Computer Science and Mathematics. His active teaching portfolio for 2025/2026 includes: Fundamentals of Computer Science II (Media Informatics, 2nd semester) Human-Machine Communication/Robotics (Informatics, Applied Informatics, Applied Robotics, Media Informatics) Deep Learning (Applied Robotics, Applied Informatics with Data Science/IKT focus) Neuroinformation Processing (Informatics, 5th/7th semesters) His research centers on intelligent systems with emphasis on: Human-robot interaction frameworks Deep neural architectures for sensory processing Neurocognitive modeling of information systems Machine learning in embedded robotics Real-time adaptive control systems Computational neuroscience applications No scientific awards were documented in source materials. Student supervision details, research grants, and laboratory affiliations remain unspecified despite his active teaching role. Office hours are scheduled for Summer Semester 2025 in room I310.

Maik Thieleمشاهده پروفایل

استاد

• Database Systems
• Data Engineering
• Big Data Analytics
• +۴ مورد دیگر

Prof. Dr.-Ing. Maik Thiele is a Professor at the Faculty of Computer Science and Mathematics , Dresden University of Applied Sciences. He leads the Professorship for Database Systems , focusing on advanced database technologies, big data platforms, and data engineering. Academic Leadership: Dean of Master's program in Applied Computer Science (since 2021), elected member of Faculty Council (since 2024) Research: Data analysis along the data value chain from acquisition to AI-driven processing, with emphasis on Active Learning , Transformer Models , and Mathematical Information Retrieval Applied Projects: Director of Dresden Database Forum , member of Digital Transformation Development Workshop (EDiT) His recent work analyzes Active Learning strategies for biomedical image classification and synthetic data, develops time series matching techniques , and explores ethical AI evaluation for e-commerce chatbots. He supervises student theses on topics ranging from PDF data extraction to Smart Grid monitoring and Speech-to-Text optimization . Professor Thiele serves on program committees for leading conferences including ADBIS , DAWAK , and DOLAP , and contributes to journals like Transactions on Knowledge and Data Engineering and International Journal on Very Large Data Bases .

• Reservoir Computing
• Machine Learning
• Embedded Systems Design
• +۴ مورد دیگر

Jonas Kantic is a Ph.D. student and Researcher at the Chair of Integrated Systems within the Faculty of Electrical Engineering and Information Technology at Technical University of Munich . Holding a Master of Science in Technical Informatics from Leibniz University Hannover, his work focuses on AI acceleration architectures and embedded systems design. Education Master's in Technical Informatics (2017-2020), Leibniz University Hannover Chinese Language Studies (2018-2019), Beijing Foreign Studies University Bachelor's in Technical Informatics (2013-2017), Leibniz University Hannover Research Focus Specializes in reservoir computing architectures Expertise in FPGA-based AI acceleration Investigates temporal/spatial compression techniques Develops efficient edge AI inference systems Applies machine learning to motorcycle control systems Works on hyperdimensional computing models Supervision Mentored 5+ students in RNN accelerators, CNN optimization, and stochastic computing Collaborates with industry partners (BMW Motorrad, NXP Semiconductors) Publications 2024 - Complex & Intelligent Systems: Cellular Automata for Reservoir Computing 2024 - IEEE NorCAS: FPGA Implementation for High-Speed Reservoir Models 2021 - Current Directions in Biomedical Engineering: Hearing Aid CNN Optimization

Jan Lauingerمشاهده پروفایل

پژوهشگر

• IoT Security
• Decentralized Systems
• Privacy and Security
• +۴ مورد دیگر

Jan Lauinger serves as a Researcher at the Technical University of Munich (TUM) within the Department of Electrical and Computer Engineering, specifically in the Associate Professorship of Embedded Systems and Internet of Things directed by Prof. Sebastian Steinhorst. Located in Munich, Germany, he actively teaches courses including "System Design for the Internet of Things" and "IoT Security" across multiple academic semesters, and contributes to research in security for IoT and autonomous systems. His research interests center on IoT Security, Decentralized Systems, Privacy-Preserving Computation, Zero-Knowledge Proofs, Data Provenance, and Identity Management. He explores modern identity frameworks, data compliance mechanisms, and verifiable computation techniques, with applications in decentralized environments and the Internet of Vehicles (IoV). His work addresses critical security and privacy challenges in emerging technologies. Recent publications (2020-2024) highlight his focus on cryptographic solutions for decentralized identity and data security, including zero-knowledge proofs for single sign-on, anonymous domain ownership, and blockchain-based trust management. He has developed frameworks for intrusion response in connected vehicles, attack data generation for autonomous systems, and secure publish/subscribe systems, demonstrating a cohesive research trajectory in securing IoT and autonomous infrastructures. No scientific awards, fellowships, or major prizes are documented in the provided materials. Lauinger has supervised over 15 student theses at TUM, including Master's and Bachelor's projects. His advisees have investigated topics such as TLS support evaluation, secure data distribution using ledger technology, decentralized oracles for web data, sensor attack simulation for autonomous vehicles, and policy-based publish/subscribe security. This reflects his active role in mentoring the next generation of security researchers. As part of Prof. Steinhorst's research group, Lauinger contributes to projects including nIoVe (a cybersecurity framework for the Internet-of-Vehicles), Time-Sensitive Networking, and the Web of Things for Industry 4.0. The team operates within TUM's advanced facilities for embedded systems research, focusing on practical security solutions for industrial IoT and autonomous systems.

Jörg Behlerمشاهده پروفایل

استاد

• Machine Learning Potentials
• Simulation of Chemical Processes at Interfaces
• Materials Science
• +۳ مورد دیگر

Prof. Dr. Jörg Behler is a faculty member at the Ruhr University Bochum , leading the Theoretical Chemistry II chair within the Faculty of Chemistry and Biochemistry . His research focuses on developing machine learning potentials for atomistic simulations of chemical processes at interfaces and materials science.

• Control Systems
• Switched Systems
• Networked Control Systems
• +۶ مورد دیگر

Marc Seidel, M.Sc., is a Research Assistant at the Institute for Systems Theory and Automatic Control , University of Stuttgart. His work bridges theoretical and applied control systems research, focusing on autonomous mobility and networked control. Research Interests include: Controller design for real-time systems under weakly-hard constraints Switched systems with graph-constrained switching Networked Control Systems Event-triggered consensus schemes Orientation estimation using inertial sensors Publications reflect expertise in autonomous e-scooter control, multi-agent coordination, and sensor-based safety filters. Key themes: control theory, robotics, and sustainable transportation. Teaching Roles at the University of Stuttgart include: SS 2024: Formal Methods in Control SS 2022-SS 2023: Concepts of Automatic Control SS 2022: Nonlinear Dynamics WS 2021/22-WS 2025/26: Lab and project courses Academic Background : M.Sc. in Engineering Cybernetics (University of Stuttgart, 2021), thesis on periodic event-triggered consensus with cooperation from Prof. Dimos V. Dimarogonas (KTH Stockholm) B.Sc. in Engineering Cybernetics (University of Stuttgart, 2015-2019), thesis on trajectory tracking control Professional Engagements : 01/2025-03/2025: Research stay at Department of Automatic Control, Lund University 03/2021-08/2021: Internship at Robert Bosch GmbH (Renningen, Germany) 08/2020-11/2020: Study abroad at KTH Stockholm for master's thesis Projects : Lead responsibility in the Autonomous E-Scooter initiative, integrating control theory into sustainable urban mobility solutions.

Luciano Andres Abriataمشاهده پروفایل

پژوهشگر

• Structural Biology
• Structural Bioinformatics
• Protein Modeling
• +۶ مورد دیگر

Dr. Luciano Andres Abriata is a Scientist at the École Polytechnique Fédérale de Lausanne (EPFL) in the School of Life Sciences , affiliated with both the Institute of Bioengineering (UPDALPE group) and the Protein Production and Structure Core Facility . His research spans structural biology, computational biophysics, and bioinformatics with a focus on protein design, membrane dynamics, and educational technology. Employment since 2012 in EPFL's bioengineering units Lecturer for advanced NMR and protein expression courses Key research areas include protein structure prediction , membrane protein biophysics , and augmented reality in science education . He has contributed to improving AlphaFold applications and WebXR platforms for collaborative molecular modeling. Recent publications highlight his work on nanopore engineering , mitochondrial membrane remodeling , and thermostable enzyme design . He co-developed tools like MoleculARweb for accessible molecular visualization and MultiProtScale for physicochemical sequence analysis. His methodological interests combine experimental data with computational modeling , particularly in membrane protein dynamics and metal center characterization . He also serves as a Lecturer for structural biology programs and contributes to science education during the pandemic through digital platforms.

Martin Hebartمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Visual Perception
• Computer Science
• +۴ مورد دیگر

Martin Hebart is a Professor at the Department of Medicine, Justus Liebig University Giessen, and affiliated with the Max Planck Institute for Human Cognitive and Brain Sciences. He leads an interdisciplinary lab integrating psychology, neuroscience, and computer science to decode visual perception mechanisms. Research focus on visual object recognition Developing computational models (deep learning, semantic embeddings) Utilizing neuroimaging (fMRI, MEG) and behavioral datasets Recent work explores: Core dimensions of material perception Alignment of AI models with human vision Distributed neural representations of object features Improving fMRI methodology His lab has produced software tools like THINGSvision and SPoSE for neural network analysis and semantic embedding. Former team members include researchers recognized with Marie Curie Fellowships.

Simon Geerkensمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Railway Systems
• Explainable AI
• +۳ مورد دیگر

Simon Geerkens serves as a Researcher and PhD candidate at Hochschule Düsseldorf's Faculty of Electrical Engineering & Information Technology under Prof. Dr. Braun. Currently embedded in the EU-funded safe.trAIn. consortium, he works on developing safety architectures for driverless regional trains through AI integration. His research focuses on explainability and trustworthiness of AI systems , data quality assurance , and practical AI applications in safety-critical railway environments. With expertise spanning artificial intelligence, deep learning, and data security, his work bridges theoretical machine learning with industrial railway automation requirements. Analysis of his recent publications reveals a strong emphasis on data quality tools (QI², ECS) and safety assurance pipelines for ML systems in rail transport. His research consistently addresses the challenge of implementing verifiable AI in safety-critical infrastructure, particularly through dataset validation methods and complexity assessment frameworks. Professional activities include active participation in the safe.trAIn. project consortium comprising railway industry leaders, technology suppliers, and standardization organizations working toward GoA4 automation standards.

Sven-Hendrik Voßمشاهده پروفایل

استاد

• Digital Signal Processing
• High-Speed Communication Systems
• FPGA Technology
• +۳ مورد دیگر

Prof. Dr. Sven-Hendrik Voß is a Professor at the Berlin University of Applied Sciences (BHT Berlin) since 2011. His academic role includes mentoring first-year students, representing practical phase programs, and leading the Digital Laboratory (Department VI). He has extensive experience in high-speed hardware architectures, FPGA design, and optical communication systems. Doctorate in Electrical Engineering (Microelectronics) from TU Berlin Diploma in Electrical Engineering (Communications) from TU Berlin Research Interests span digital signal/image processing, FPGA-accelerated data processing, high-speed communication systems, embedded vision systems, and methods for image synthesis. He has contributed to light field imaging, real-time processing, and optical interconnects for maskless lithography. Publications focus on FPGA-based solutions for high-speed data processing, optical communication systems, and hardware implementations in fields like 3D media and industrial applications. His work often combines digital circuit design with optical technologies. Teaching includes digital systems design, computer architecture, machine-oriented programming, and image processing. He offers thesis topics involving FPGA development for audio/video applications and communication systems. Professional Background includes leadership roles at Fraunhofer HHI, where he headed the High-Speed Hardware Architectures department (2010-2014) and led hardware groups in earlier roles. He has industry experience in VHDL implementation and PCB design.

• Theoretical Computer Science
• Formal Verification
• Software Systems Verification
• +۵ مورد دیگر

Georg Zetzsche is a tenure-track faculty member at the Max Planck Institute for Software Systems (MPI-SWS) in Kaiserslautern, Germany, where he heads the Models of Computation group. He joined MPI-SWS in November 2018 after postdoctoral positions at IRIF, Université Paris-Diderot (2017-2018) and LSV Cachan (2015-2017). He received his PhD in Computer Science from Universität Kaiserslautern under the supervision of Prof. Dr. Roland Meyer in 2015, with a dissertation in the Concurrency Theory Group. His research focuses on theoretical foundations of verification and synthesis of software systems, with particular emphasis on decidability and complexity issues of infinite-state systems. His work explores synthesis of finite-state abstractions of infinite-state systems (including separability problems, downward closures, and Parikh images), as well as decision problems for infinite groups where he applies methods from verification to gain insights on how to devise infinite-state models with pleasant analysis properties. Zetzsche's research output demonstrates expertise across formal verification, theoretical computer science, and programming language theory. His publications reveal a consistent focus on vector addition systems, reachability analysis, language theory, and decidability questions. His work often bridges theoretical foundations with practical verification problems, particularly in the context of infinite-state systems where traditional verification techniques face significant challenges. 2025 Salomaa Prize ERC Starting Grant for project FINABIS EATCS Best Paper Award at ETAPS 2023 EAPLS Best Paper Award at ETAPS 2021 Distinguished Paper Award at POPL 2021 EATCS Distinguished Dissertation Award He actively serves on program committees for major conferences including LICS 2026, MFCS 2025, DLT 2024, ICALP 2024, POPL 2024, LICS 2023, and many others. He has organized events such as Theorietag 2023 on automata and formal languages. His current group at MPI-SWS includes PhD students Pascal Baumann, Pascal Bergsträßer, Irmak Sağlam, Lia Schütze, and Yousef Shakiba, along with postdocs Moses Ganardi and Chris Köcher.

• Multimodal Generative AI
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Vicky Kalogeiton is a Professor in AI at École Polytechnique's Computer Science Laboratory (LIX) and leads the VISTA team. As an ELLIS member, her research focuses on multimodal generative AI with applications in medical imaging, efficient generation, and structured output modeling. She actively publishes in top venues like CVPR, ICCV, and IJCV, and supports Slow/ Open Science principles. PhD from University of Edinburgh and INRIA Grenoble Habilitation (HDR) from École Polytechnique 2024 Hi!Paris Chaire and multiple grants (ANR, Microsoft, DIM RFSI) Her recent work explores diffusion models for visual geolocation (Around the World in 80 Timesteps), camera motion control (AKiRa & E.T. dataset), and multimodal humor detection (FunnyNet-W). She pioneered coherence-aware training frameworks and cinematic trajectory analysis methods. Scientific recognition includes CVPR 2024 Highlight paper ACCV 2022 Student Honorable Mention ICCV-W 2021 Best Paper Award Outstanding Reviewer Awards (CVPR, ICCV, ECCV) She supervises current PhD candidates and has mentored numerous students across institutions like MBZUAI, Inria, and Telecom Paris. Her teaching includes Advanced Deep Learning and Computer Vision courses at École Polytechnique.

Junjie Shiمشاهده پروفایل

پژوهشگر

• Real-Time Systems
• Embedded Systems
• Real-Time Scheduling
• +۴ مورد دیگر

Dr.-Ing. Junjie Shi is a researcher at the Department of Computer Science (Chair 12) within the Faculty of Computer Science at TU Dortmund University. His work focuses on real-time systems, embedded systems, and resource-aware machine learning approaches. Research Interests: Real-Time Systems, Embedded Systems, Real-Time Scheduling, Resource Synchronization/Sharing Protocols, Resource-Aware Machine Learning, Bayesian Optimization, Reinforcement Learning Address: Otto-Hahn-Str. 16, Room E05, 44227 Dortmund, Germany. Contact: Phone +49 (231) 755-6121.