Find Academic Supervisors

• Plant Genetics
• Crop Biodiversity
• Breeding Informatics
• +5 more

Karl Schmid is a W3 Professor of Crop Plant Biodiversity and Breeding Informatics at the University of Hohenheim's Institute of Plant Breeding, Seed Science and Population Genetics within the College of Agricultural Sciences. His research integrates evolutionary genetics, population genomics, and machine learning to address agricultural challenges. Ph.D. in Biology, University of Munich (1996) Postdoctoral Research, Cornell University (1997-1999) Emmy-Noether Research Group, Max Planck Institute of Chemical Ecology (2000-2006) Group Leader, Leibniz Institute of Plant Genetics (2006-2008) Professor of Genetics, Swedish Agricultural University (2008) His research focuses on crop biodiversity conservation, evolutionary genetics of plant pathogens, and breeding informatics applications. Current work leverages deep learning for phenotyping (quinoa panicles, barley genomics) and analyzes pathogen evolution (Exserohilum turcicum in maize). His team actively develops computational tools like GGoutlieR for geo-genetic pattern detection. Recent publications demonstrate strong trends in applying AI to agricultural genomics, particularly in quinoa improvement and pathogen surveillance. His group leads the EU H2020 INVITE project on molecular markers in plant variety protection and organizes international symposia like the 2024 Quinoa Symposium at Hohenheim. Head of Crop Biodiversity and Breeding Informatics Group Principal Investigator, EU H2020 INVITE project Organizer, International Quinoa Symposium 2024

• Biophysics
• Molecular Dynamics Simulations
• Membrane Biology
• +4 more

Balázs Fábián is a postdoctoral researcher at the Max Planck Institute of Biophysics in the group of Gerhard Hummer. He holds a PhD from the University Bourgogne Franche-Comté (France) and Budapest University of Technology and Economics (Hungary). His research focuses on molecular dynamics simulations of lipid membranes and viral systems, particularly studying viral budding mechanisms in enveloped viruses like HIV. Fábián’s work bridges computational biophysics and membrane biology, with applications ranging from anaesthesia mechanisms to neurodegenerative diseases. Education: BSc and MSc in Chemical Engineering from Debrecen and Budapest Universities (Hungary), followed by a PhD in Biophysics. Previously, he conducted postdoctoral research at the Czech Academy of Sciences and the Max Planck Institute. Research Interests: Computational modeling of lipid bilayers, viral membrane interactions, anaesthetic effects on membranes, and protein aggregation in neurodegenerative contexts. His methods include molecular dynamics simulations and coarse-grained modeling (e.g., Martini force field). Teaching and Mentorship: Guides junior researchers in computational techniques and simulation methodologies. Active in conference presentations and publication preparation. Future Goals: Aims to lead a junior research group via the Emmy Noether program, focusing on advancing computational tools for membrane systems and viral dynamics.

• Cyber-Physical Systems
• Industry 4.0
• Augmented Reality
• +4 more

Thomas Ludwig is a Professor of Information Systems with a focus on Cyber-Physical Systems at the University of Siegen. He holds a PhD (summa cum laude) from the same institution and has led numerous research initiatives in Industry 4.0, digital transformation, and human-centered technology design. His work spans augmented reality (AR), gamification, and AI integration in manufacturing. Ludwig co-founded and coordinates the 'Mittelstand 4.0-Kompetenzzentrum Siegen' to support SMEs in digitalization. He has authored over 50 publications in top-tier journals and conferences, including Computer Supported Cooperative Work (CSCW) and Proceedings of the ACM on Human-Computer Interaction . His research has been recognized with awards such as the IHK Preis 2017 for Best Dissertation and the Artur-Woll-Preis. Education: Diplom-Wirtschaftsinformatiker from University of Siegen (2012), PhD in Information Systems (2016), with a focus on socio-technical systems and mobile/social media research. Research Interests: Cyber-Physical Systems, AR applications, gamification design, AI in production planning, and digital competency frameworks for SMEs. He leads projects like Fusion, KOKOS, and EKPLO, addressing challenges in collaborative work, disaster management, and industrial digitalization. Grants & Projects: Projects include EU-funded EMERGENT, BMBF-funded KOKOS, and the self-acquired EKPLO initiative for APS systems in SMEs. He also coordinates the Zukunftszentren KI NRW and the EDIH Südwestfalen. Awards: 32. IHK Preis 2017, Artur-Woll-Preis, pwc-Preis, and multiple best paper awards at international conferences. Labs/Teams: Part of the Cyber-Physical Systems Lab at University of Siegen and the interdisciplinary team behind the 'Rendezfood' and 'Advanced Planning Systems' initiatives.

Dongheui LeeView profile

Assistant Professor

• Human motion understanding
• Physical human-robot interaction
• Machine learning in robotics
• +5 more

Dongheui Lee is an Assistant Professor at the Institute of Automatic Control Engineering (LSR) within the Faculty of Electrical Engineering and Information Technology at Technische Universität München (TUM). She leads the Dynamic Human Robot Interaction for Automation System Lab. Her research focuses on human motion understanding, physical human-robot interaction, and machine learning in robotics. Education: B.S. and M.S. in Mechanical Engineering from Kyunghee University (2001-2003), PhD in Mechano-Informatics from the University of Tokyo (2007). Prior roles include research scientist at KIST Korea (2001-2004) and project assistant professor at the University of Tokyo (2007-2009). Research Interests: Human-robot collaboration, probabilistic robotics, motion recognition, and incremental lifelong learning mechanisms. She has contributed to advancements in motion primitives, compliant physical interaction, and real-time object tracking. Selected Awards: Finalist for KUKA Service Robotics Best Paper Award (2009), Hirose Scholarship (2006-2007), and multiple grants from KRF, KOSEF, and international robotics competitions. Key Publications: Focus on prioritized inverse kinematics, motion imitation, and adaptive control systems. Her work bridges robotics theory and practical applications in humanoid robots and human-robot interaction.

Michael OrtizView profile

Professor

• Cardiac Mechanics
• Computational Mechanics
• Biomedical Engineering
• +3 more

Michael Ortiz is the Dotty and Dick Hayman Professor of Aeronautics and Mechanical Engineering at the California Institute of Technology (Caltech). He holds the Hans Fischer Senior Fellowship at the Technical University of Munich's Institute for Advanced Study (TUM-IAS) since 2010. His research focuses on developing the Advanced Cardiac Mechanics Emulator (ACME) to model human heart function in healthy and diseased states. He has a BS from the Polytechnic University of Madrid, and MS/PhD from UC Berkeley. Previously, he was at Brown University (1984–1995). Professor Ortiz leads Caltech’s DoE/PSAAP Center on High-Energy Density Dynamics of Materials. His honors include the IUTAM Rodney Hill Prize (2008), election to the American Academy of Arts & Sciences (2007), and Humboldt Research Award (2002). He has advised national labs like Lawrence Livermore and Sandia on predictive science and engineering review panels. His work spans computational mechanics, materials science, and multiscale modeling. Recent research emphasizes cardiac biomechanics, fracture mechanics, and quantum materials simulations. Over 100 highly cited papers showcase contributions to meshfree methods, variational fracture, and orbital-free DFT.

Yelda TurkanView profile

Associate Professor

• Digital twins
• Scan-to-BIM
• Machine learning
• +7 more

Dr. Yelda Turkan is an Associate Professor in the School of Civil and Construction Engineering at Oregon State University and a Hans Fischer Fellow at the Technical University of Munich (TUM-IAS). Her research focuses on leveraging computer vision, machine learning, and digital twins to enhance sustainability and resilience in the built environment. She holds a Ph.D. in Civil Engineering from the University of Waterloo, Canada, and dual B.Sc. degrees in Civil Engineering and Geomatics Engineering from Istanbul Technical University, alongside an M.Sc. in Remote Sensing. Her work integrates advanced technologies like LiDAR and BIM to improve construction monitoring, structural safety, and fire protection. She has authored over 80 peer-reviewed publications and secured $4.5M in grants from agencies like the NSF. Dr. Turkan serves as Vice President of the International Association for Automation and Robotics in Construction and chairs the ASCE Computing Division Executive Committee. Her research spans digital twins for infrastructure performance, fire safety simulations, and automated progress tracking. Key contributions include frameworks for bridge construction monitoring, fire safety management in timber structures, and BIM-based energy fault detection. Awards include the Robert C. Wilson Faculty Scholar (2023–2025) and ASCE ExCEEd Teaching Fellow (2015).

Hai (Helen) LiView profile

Professor

• Neuromorphic Computing
• Machine Learning
• Emerging Memory Technologies
• +3 more

Hai (Helen) Li is a Professor and Clare Boothe Luce Associate Chair at Duke University's Electrical and Computer Engineering department. She was a TUM-IAS Hans Fischer Fellow (2017) hosted by Prof. Ulf Schlichtmann in the Neuromorphic Computing focus group. Education: B.S./M.S. from Tsinghua University, Ph.D. from Purdue University Positions: Qualcomm, Intel, Seagate, Polytechnic Institute of New York University, University of Pittsburgh Her research spans neuromorphic computing systems , machine learning acceleration , emerging memory technologies , and low-power circuits . Publications demonstrate expertise in ReRAM/memristor-based accelerators, sparse neural networks, and processing-in-memory architectures. Key contributions include cross-layer optimization frameworks and robust neuromorphic designs. Her awards include: 9 Best Paper Awards (ASPDAC, ICMLA, ISVLSI, etc.) NSF Career Award DARPA Young Faculty Award IEEE Fellow (2019) ACM Distinguished Member (2017) IEEE TCSDM Outstanding Leadership Award (2021)

• Computational Fluid Dynamics
• Fluid Dynamics
• Numerical Simulation
• +3 more

Dr. Dirk Lucas serves as the Head of the Computational Fluid Dynamics department at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR). His research focuses on advanced computational methods in fluid dynamics, including turbulence modeling, numerical simulation techniques, and their applications in engineering and aerodynamics. He is affiliated with the Fluid Dynamics Institute at HZDR, a leading research center in Dresden, Germany. His work contributes to advancing computational tools for understanding complex fluid systems. No specific awards, publications, or grants are explicitly listed in the provided text. Contact details include his email at d.lucas@hzdr.de and office location at Bautzner Landstraße 400, 01328 Dresden.

• Wireless Networks
• Machine Learning
• Federated Learning
• +3 more

Choong Seon Hong is a Professor at Kyung Hee University's Department of Computer Science and Engineering in Yongin, South Korea. He earned his PhD in Instrumentation Engineering from Keio University, Japan, in 1997. His research focuses on next-generation wireless networks, with emphasis on 6G systems, federated learning, edge computing, and network optimization. Recent collaborative work explores semantic communication, UAV deployment, and multimodal learning frameworks. His publications highlight technical innovations in: Wireless network optimization for terrestrial, aerial, and satellite systems Federated learning architectures with knowledge distillation and prototype transfer Energy-efficient resource allocation in IoT and vehicular networks Security frameworks for EV charging stations and Open RAN systems Current trends show strong collaboration with Zhu Han, Walid Saad, and younger researchers like Apurba Adhikary and Yan Kyaw Tun. The work spans technical solutions for 6G non-terrestrial networks, holographic MIMO systems, and semantic communication frameworks.

• Biomedical Engineering
• Machine Learning
• Computer Vision
• +3 more

Aggelos K. Katsaggelos is a Professor in the Department of Electrical Engineering and Computer Science at Northwestern University's McCormick School of Engineering. His research focuses on biomedical imaging, machine learning, and computer vision applications in healthcare. He has collaborated extensively with interdisciplinary teams, including clinicians and engineers, to develop advanced algorithms for medical diagnosis and image analysis. Key research interests include medical image processing, deep learning for diagnostics, and computational methods in cardiology. His work spans applications such as MRI and ultrasound analysis, automated pathology detection, and multimodal sensing for health monitoring. Recent articles highlight contributions to myocardial scar quantification, lung ultrasound scoring, and AI-driven cough detection. His methodologies often combine domain-specific physics with modern machine learning techniques to solve real-world clinical challenges. Notable collaborations include projects with institutions like the University of Chicago and international teams in astrophysics and cognitive science. His work emphasizes translating algorithmic advancements into practical clinical tools.

• Artificial Intelligence
• Automated Planning
• Temporal Reasoning
• +4 more

Alfonso Emilio Gerevini is a prominent researcher in artificial intelligence with over 30 years of continuous academic contributions. His work spans theoretical foundations of automated planning to practical healthcare applications, with recent publications demonstrating significant impact in both traditional AI domains and emerging interdisciplinary areas. His research interests focus on automated planning systems , temporal reasoning , and multi-agent coordination , with recent expansion into healthcare applications using machine learning techniques. Gerevini has made fundamental contributions to planning algorithms, particularly in width-based search, case-based planning, and privacy-preserving multi-agent planning. His work on PDDL (Planning Domain Definition Language) has been influential in standardizing planning representations. Analysis of his 15 most recent publications reveals a strategic evolution from core planning research toward impactful healthcare applications, particularly during the COVID-19 pandemic. While maintaining his expertise in planning algorithms, he has successfully integrated machine learning techniques to address real-world medical challenges including radiology report analysis, prognosis prediction, and lab test interpretation. His work demonstrates exceptional versatility across both theoretical and applied domains of artificial intelligence. Gerevini maintains a robust collaborative network, primarily with Italian researchers including Ivan Serina, Alessandro Saetti, and Luca Putelli. His publications appear consistently in top-tier AI venues including Artificial Intelligence journal, Journal of Artificial Intelligence Research, and AAAI/ICAPS conferences. The collaborative patterns suggest he leads a significant research group focused on advancing planning systems while applying them to critical real-world problems.

• Computer Vision in Medical Imaging
• Machine Learning
• Medical Imaging Segmentation
• +3 more

Dr. Antonio Ortiz is a Researcher at the University of Bonn, affiliated with the Life and Medical Sciences Institute (LIMES) and the IRU Mathematics and Life Sciences group. He works under the supervision of Professors Alexander Effland and Jan Hasenauer. His research focuses on Computer Vision in Medical Imaging and Machine Learning applications. He holds a Ph.D. in Electric and Electronics Engineering from Cinvestav, Mexico (2023), a Master's in Computer Science from Cicese, Mexico (2019), and a Bachelor's in Mechatronic Engineering (2017). His research integrates Bayesian methods, deep learning, and optical flow techniques for cardiac MRI segmentation, visual-inertial SLAM systems, and 3D shape measurement. Recent work emphasizes adaptive algorithms for medical imaging and robotics applications. Publications span medical imaging, robotics, and materials science, with a focus on algorithmic innovation and interdisciplinary applications. No scientific awards are explicitly mentioned, but his work demonstrates strong academic contributions. His advising activities and grants are not detailed in the provided text. He collaborates within the Effland Lab and IRT Mathematics and Life Sciences team.

Olfa Lopez-D’AngeloView profile

Researcher

• Granular Rheology
• Additive Manufacturing
• Space Technology
• +3 more

Dr. Olfa Lopez-D’Angelo is a researcher at the Department of Multiscale Simulation of Particulate Systems at Friedrich-Alexander-Universität Erlangen-Nürnberg. Her research focuses on granular rheology, additive manufacturing for space applications, and the behavior of materials under microgravity conditions. She leads the Rheologie granularer Materialien unter Weltraumbedingungen project (2023–2026), funded by the German Ministry for Economic Affairs and Climate Action (BMWK). Her work bridges theoretical physics, experimental engineering, and space technology. Key research interests include granular fluid dynamics, powder-based manufacturing processes in low-gravity environments, and the structural analysis of metamaterials. She has contributed to pioneering studies on acoustically propelled macroparticles and granular piston-probing in microgravity. Her interdisciplinary approach is evident in collaborations with institutions like ESA and DLR, as well as her involvement in projects such as the VIP-DROP2 module for droplet dynamics experiments. Awards: Granular Matter Gordon Research Conference Poster Prize (2022) ELGRA Research Prize (2021) Fly Your Thesis! 2019 (2018) ESA Networking/Partnering Initiative Fellowship (2017) Dr. Lopez-D’Angelo actively disseminates her work through international conferences (e.g., DPG, IAC) and public engagement initiatives, including the podcast Talk That Science . Her research emphasizes practical applications in space exploration, such as in-situ resource utilization and advanced manufacturing systems for extraterrestrial environments.

• Eye Tracking Methodology
• Human-Computer Interaction
• Computer Graphics
• +5 more

Andrew T. Duchowski is a Professor at Clemson University, specializing in Eye Tracking Methodology, Human-Computer Interaction, and Computer Graphics. His work spans over two decades with significant contributions to gaze-based interaction systems, foveated rendering, and cognitive load measurement. He authored three editions of the influential textbook Eye Tracking Methodology (Springer, 2003/2007/2017). Duchowski's research integrates eye movement analysis with applications in virtual reality, medical imaging (e.g., colonography viewers), and aviation safety. He actively collaborates with institutions globally and serves on editorial boards for journals like Proceedings of the ACM on Human-Computer Interaction . His recent projects include developing real-time gaze analytics pipelines and exploring entropy-based metrics for visual attention analysis. Publications (selected 15 recent): Focus on advancing gaze interaction in immersive environments, optimizing 3D visualization, and measuring cognitive load through pupillary activity and microsaccades. Key co-authors include Krzysztof Krejtz, Matias Volonte, and Donald House.

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +5 more

Christian Eichhorn is an Assistant Professor in the Department of Computer Science at Technical University of Munich, specializing in Human-Computer Interaction, Virtual Reality, and Augmented Reality applications. His research primarily focuses on developing serious games and immersive technologies for healthcare, education, and older adults. He has established a strong collaborative network, particularly with David A. Plecher and Gudrun Klinker, resulting in numerous publications in top HCI and VR venues. Dr. Eichhorn's research interests center around creating accessible and engaging technology applications. His work demonstrates particular expertise in developing serious games for various educational purposes (language learning, history education), healthcare applications (rehabilitation, dementia care), and technologies specifically designed for older adults. His research combines technical innovation in AR/VR systems with practical applications addressing real-world challenges in healthcare and education. Analysis of his recent publications (2022-2025) reveals a consistent focus on practical applications of immersive technologies. His work spans educational tools for programming and language learning, healthcare applications for rehabilitation and clinical training, and specialized technologies for older adults. The research demonstrates a strong interdisciplinary approach, bridging computer science with healthcare, education, and gerontology. His technical contributions include innovations in AR/VR system design, collaborative environments, and novel interaction techniques. Dr. Eichhorn has been actively involved in organizing workshops and contributing to major conferences in the VR/AR field, including IEEE VR and ISMAR. His collaborative approach is evident in his extensive co-authorship network spanning multiple institutions. His laboratory work focuses on developing practical AR/VR applications, with particular emphasis on creating systems that bridge virtual and physical experiences. Current projects include serious games for health behavior change, rehabilitation assessment tools using wearable sensors, and social VR environments for older adults.