Find Academic Supervisors

• Theoretical Physics
• Cosmology
• String Theory
• +3 more

Professor Ivo Sachs is a distinguished theoretical physicist at the Ludwig-Maximilians-Universität München (LMU), where he holds a position at the Arnold Sommerfeld Center for Theoretical Physics with a Chair on Cosmology. His research spans multiple areas of theoretical physics with a particular focus on string theory, quantum field theory, and cosmological applications. He maintains an active research program with numerous recent publications in prestigious journals. Professor Sachs' research interests center around fundamental theoretical physics, with significant contributions to string field theory, cosmological perturbation theory, and the mathematical structures underlying quantum gravity. His work often bridges abstract mathematical concepts with physical applications, particularly in understanding the early universe and quantum aspects of gravity. He has developed innovative approaches to studying cosmological correlators, spinning particles, and the relationship between quantum field theory and gravitational physics. Analysis of his recent publications reveals a strong focus on the intersection of cosmology and string theory, with particular attention to mathematical structures in quantum gravity. His work demonstrates consistent exploration of how quantum field theory techniques can be applied to cosmological problems, especially regarding correlation functions in the early universe. He frequently collaborates with researchers across Europe, indicating an active international research network. Martín Enríquez Rojo (PhD, 2022): Asymptotic symmetries in FLRW and deformations of gravitational symmetry algebras

• Mathematical Data Science
• Machine Learning
• Compressed Sensing
• +5 more

Johannes Maly is an Assistant Professor at the Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence at LMU Munich. He previously held postdoctoral positions at Catholic University of Eichstaett-Ingolstadt and RWTH Aachen University, and completed his PhD at TUM Munich under Prof. Massimo Fornasier. PhD in Mathematics (2019, TUM Munich) M.Sc. in Mathematics (2015, TUM Munich) B.Sc. in Mathematics (2013, TUM Munich) His research focuses on mathematical data science and machine learning, specifically addressing: Robust covariance estimation under quantization Neural network approximation properties Implicit bias in gradient descent training Multi-structured signal recovery Quantization effects in deep learning and compressed sensing His recent publications analyze dithered quantization in covariance estimation, implicit regularization in overparameterized models, and multi-structured data recovery. He applies mathematical rigor to practical challenges in wireless communications (e.g., MIMO systems) and neural network training. Scientific recognition includes: relAI Fellow MCML Associate He supervises code/toolbox development for reproducibility and teaches graduate courses in convex optimization, high-dimensional probability, and mathematical data science. His work bridges theoretical mathematics and applied signal processing.

• Digital Signal Processing
• Speech Communication
• Acoustic Signal Processing
• +3 more

Peter Vary is a Professor at the Faculty of Electrical Engineering and Information Technology of RWTH Aachen University, serving as Director of the Institute for Communication Systems. His work focuses on speech and audio signal processing for communication systems. Digital Signal Processing Speech Enhancement Acoustic Echo Control Microphone Array Beamforming Communication Systems Audio Compression His recent publications (2023–2024) emphasize speech coding, noise reduction, and bandwidth extension for hearing aids and mobile devices, with technical innovations in Kalman filters, hybrid digital-analog transmission, and wind noise detection. He holds a leadership role in the Institute for Communication Systems and serves as Ombudsperson for teaching in his faculty. Contact: vary@iks.rwth-aachen.de

A. Lee SwindlehurstView profile

Professor

• Signal Processing
• Wireless Communications
• Biomedical Applications
• +3 more

A. Lee Swindlehurst is a Professor and Associate Dean for Research and Graduate Studies at the Henry Samueli School of Engineering of the University of California, Irvine . He is also a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study , where he collaborates on next-generation wireless communications research. Ph.D., Stanford University (Electrical Engineering, 1991) M.S., Brigham Young University (Electrical Engineering, 1986) B.S., Brigham Young University (Electrical Engineering, 1985) Swindlehurst's research focuses on sensor array signal processing for radar, wireless communications, and biomedical applications. His work addresses detection and estimation theory , system identification, and channel modeling, with recent emphasis on massive MIMO systems , low-resolution hardware, and physical layer security . His 2018-2017 publications demonstrate technical advances in precoding algorithms , channel estimation , and ADC/DAC optimization for emerging wireless architectures. IEEE Fellow (2004) IEEE Signal Processing Society Best Paper Awards (2010, 2006) Stephen O. Rice Prize in Communications Theory (2006) IEEE W.R.G. Baker Prize Paper Award (2000) Karl G. Maeser Research Award (2004) His research has produced foundational work on space-time block codes , vector-perturbation techniques , and blind equalization methods that continue influencing modern wireless system design.

Gerard de MeloView profile

Professor

• Artificial Intelligence
• Large Language Models
• Natural Language Processing
• +9 more

Gerard de Melo is a Professor and Chair of Artificial Intelligence and Intelligent Systems at the Hasso Plattner Institute (University of Potsdam, Germany). He also serves as a member of the Cognitive Sciences Research Focus and ELLIS Unit Potsdam . Research Interests: AI and Machine Learning Natural Language Processing Cross-modal AI (vision-language models, knowledge graphs) Societal and philosophical aspects of AI Medical Informatics Recommendation Systems Graph Neural Networks Recent Article Trends: His work spans generative AI (Vector Grimoire), medical LLM evaluation (CliMedBench), distributed training (Efficient Parallelization), and social media analysis (WallStreetBets) with a focus on multimodal systems and ethical AI . Scientific Recognition: Rutgers CSGSS Best Professor Award (Teaching, Advising) Best Paper Awards: NeurIPS Workshop, CIKM, EACL LANTERN IEEE TCSE Distinguished Paper Award First Runner-Up ACM WebSci Advising & Grants: Mentored students like Rohan Sawahn (Better World Award) and Maximilian Schall (IEEE TCSE Award). Secured major funding including German BMBF Grant for AI Service Center Berlin-Brandenburg and DARPA SocialSim Program support.

Marcel CampenView profile

Professor

• Computer Graphics
• Geometry Processing
• Surface Parametrization
• +4 more

Marcel Campen is a Professor at Osnabrück University specializing in Computer Graphics and Geometry Processing. His research focuses on surface parametrization, quad mesh generation, and computational geometry. He has made significant contributions to the field of geometry processing, particularly in developing algorithms for quad layout generation, surface mapping, and mesh repair. His research interests span Computer Graphics, Geometry Processing, Surface Parametrization, Quad Mesh Generation, 3D Modeling, and Mesh Repair. Campen's work addresses fundamental challenges in representing and processing complex geometric shapes, with applications ranging from animation and simulation to reverse engineering and meshing. His research often combines theoretical insights with practical implementations, resulting in algorithms that are both mathematically sound and computationally efficient. Campen's publications demonstrate a strong focus on developing robust and efficient methods for geometry processing. His work on quad layout generation, parametrization techniques, and surface mapping has resulted in several award-winning papers, including Best Paper Awards at SGP 2021 and 2022. His research often bridges theoretical concepts with practical implementations, making his contributions highly influential in both academic and industrial settings. Best Paper Award (1st place) at SGP 2022 Best Paper Award at SGP 2021 Campen has made significant contributions to the field through his doctoral thesis on quad layout generation and numerous publications in top-tier conferences including SIGGRAPH, Eurographics, and SGP. His work on directional field synthesis, similarity maps, and bijective mappings has advanced the state of the art in geometry processing. He has also contributed to practical tools like libQEx for robust quad mesh extraction, demonstrating his commitment to making theoretical advances accessible to practitioners.

Rajmadan LakshmananView profile

Research Fellow

• Optimal Transport Theory
• Stochastic Optimization
• Financial Mathematics
• +3 more

Rajmadan Lakshmanan is a Research Fellow at the Faculty of Mathematics , Technische Universität Chemnitz , specializing in optimal transport theory, stochastic optimization, and computational finance. Since 2021, he has contributed to academic development through teaching assistant roles and active participation in research seminars and workshops.

• Global Analysis
• Index Theory
• Differential Geometry
• +3 more

Ursula Ludwig is a Professor of Mathematics at Université Côte d'Azur, Nice, France. Her academic journey includes roles as a W2 Professor at the University of Münster (2022–2024), a permanent lecturer at University Duisburg-Essen (2015–2021), and multiple visiting positions. She holds a PhD (2004) and Habilitation (2011) from the University of Freiburg. Her research focuses on the interplay between geometry, topology, and analysis on singular spaces, particularly index theory, analytic torsion, and Morse-Novikov theory. Key contributions include extending the Cheeger-Müller theorem and Witten deformation to singular spaces. **Research Highlights**: She has pioneered work on intersection homology via analytic methods, L2-techniques, and global analysis. Notable achievements include the Bismut-Zhang theorem extension and the Index Formula for intersection Euler characteristics. Her work bridges differential geometry, algebraic topology, and complex analysis. **Grants & Leadership**: Principal Investigator (PI) in DFG-funded RTG 2553 (2020–2024), ANR-DFG project on Quantization and Singularities (2022–2024), and Cluster of Excellence Mathematics Münster. Previously involved in the Research Training Group GRK 1821 at Freiburg. **Teaching**: Courses include Global Analysis, Differential Geometry (at Münster, Duisburg-Essen), and foundational mathematics for computer science students. She has led seminars on index theory, characteristic classes, and geometric analysis. **Awards & Recognition**: Invited Sectional Speaker at the 2024 European Congress of Mathematics. Editorial Board member of the Journal of Singularities . **Outreach**: Organized workshops for high school students, mentoring programs (e.g., MeMPhys), and public lectures promoting mathematics.

Jackson van DykeView profile

Research Fellow

• Topological Quantum Field Theory
• Higher Algebraic Geometry
• Quantum Topology
• +3 more

Dr. Jackson van Dyke is a Research Fellow at the Technical University of Munich under Prof. Dr. Claudia Scheimbauer in the Department of Mathematics (M2) at the TUM School of Computation, Information and Technology. His research explores anomalous properties of functorial quantum field theories. Broad applications include classification of topological orders Higher algebraic geometry Relative Langlands program Publications span 2023-2024 articles on projective TQFT symmetries, 2020 work on knot Floer homology, and 2017-2020 studies in radiation material testing and fission modeling. His presentation history includes talks at University of Lisbon, University of Hamburg, and Simons Collaboration events.

• Differential Geometry
• Geometric Mechanics
• Poisson Geometry
• +6 more

Prof. Dr. Jotz Madeleine is a W2 Professor of Geometry at the University of Würzburg since August 2021. She holds the Chair of Mathematics X (Geometry) within the Department of Mathematics. Her academic journey includes a Junior Professorship and Acting Professorship at the University of Göttingen (2016–2021), a Vice-Chancellor's Fellowship at the University of Sheffield (2013–2017), and postdoctoral positions at UC Berkeley and the University of Göttingen. She earned her PhD in Mathematics at the École Polytechnique Fédérale de Lausanne (EPFL) and a Diplom in Mathematics from the University of Freiburg. Her research focuses on differential geometry, geometric mechanics, and higher structures, with an emphasis on Poisson geometry, Lie n-groupoids/algebroids, Courant algebroids, and geometric structures on double vector bundles. She explores topics such as representations up to homotopy, characteristic classes, and obstructions to symmetries. Her work bridges algebraic topology, category theory, and geometric analysis. Prof. Jotz Madeleine collaborates widely, with notable co-authors including Malte Heuer, Kirill Mackenzie, and Rajan Mehta. Her publications appear in journals like Journal de Mathématiques Pures et Appliquées and Mathematische Annalen . She contributes to the Geometry team at the Institute of Mathematics, advancing the field through interdisciplinary research.

• Data Mining
• Database Systems
• Temporal Databases
• +4 more

John F. Roddick is a Professor affiliated with Flinders University in South Australia. His research focuses on data mining, database systems, and temporal databases, with significant contributions to association rule mining, schema evolution, and privacy-preserving techniques. He has collaborated extensively with researchers like Shu-Chuan Chu and Jeng-Shyang Pan, producing over 138 publications across journals and conferences. Key contributions include work on schema versioning, temporal vacuuming in databases, and algorithms for wireless sensor networks. His research extends to image processing, biometrics, and swarm intelligence, with notable applications in traffic prediction and secure communication systems. He has edited conference proceedings and contributed to encyclopedic entries on database systems and data warehousing. Roddick's work often bridges theoretical foundations with practical applications, emphasizing interdisciplinary approaches to data management challenges. His publications span venues such as IEEE Transactions on Knowledge and Data Engineering, Data & Knowledge Engineering, and the Journal of Network and Intelligence.

• Machine Learning
• Control Systems
• Computer Vision
• +3 more

Jian Sun is a researcher affiliated with the Chinese Academy of Sciences' Institute of Computing Technology. His work spans interdisciplinary fields including machine learning, control systems, robotics, and signal processing. He collaborates with institutions globally to advance theoretical and applied research in computational methods and their real-world applications. Research interests focus on machine learning for healthcare diagnostics, optimization algorithms for complex systems, and sensor fusion technologies for autonomous systems. Recent work emphasizes applications in cognitive impairment detection, UAV-based communication systems, and crystal structure prediction. Publications highlight advancements in adaptive control methodologies, cybersecurity in control systems, and 3D reconstruction techniques. His contributions bridge theoretical foundations with practical implementations in robotics, aerospace, and environmental monitoring.

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.

Robert BamlerView profile

Professor

• Deep Generative Models
• Machine Learning
• Probabilistic Inference
• +3 more

Robert Bamler is a Professor of Data Science and Machine Learning at the University of Tübingen, Germany , and a member of the Cluster of Excellence "Machine Learning: New Perspectives for Science" and the Tübingen AI Center . Current affiliation: University of Tübingen (since November 2020) Prior roles: Postdoctoral Scholar at UC Irvine (with Stephan Mandt), Machine Learning Researcher at Disney Research (Pittsburgh/Los Angeles) Education: PhD in Theoretical Statistical and Quantum Physics from University of Cologne (2016), advised by Achim Rosch Research Focus : Algorithm development for deep generative models (including large language models) Resource-efficient inference and model compression Probabilistic machine learning applications in natural sciences Theoretical foundations in statistics, information theory, and physics Scientific Contributions : German Telekom Foundation PhD scholarship awardee Co-founder of the BamlerLab reading group on probabilistic modeling and compression Key Collaborations : Stephan Mandt (UC Irvine) Bernhard Schölkopf (MPI-IS) Cluster of Excellence "Machine Learning" (Tübingen) Teaching : Lecturer for "Data Compression With and Without Deep Probabilistic Models" (2021-2025) Organizer of weekly reading groups on function-space inference and compression algorithms

• Parallel Computing
• Distributed Systems
• Intelligent Storage Systems
• +5 more

Cheng Li is an Associate Professor at the School of Computer Science, University of Science and Technology of China , and Director of the Information Computing Platform at the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center. His research focuses on parallel and distributed intelligent computing systems, with an emphasis on optimizing computational efficiency through data-centric approaches. Education: PhD in Computer Science from Max Planck Institute for Software Systems (MPI-SWS) and Saarland University (2016) Bachelor's degree in Computer Science from Nankai University (2009) Research interests include distributed systems, machine learning optimization, database systems, and high-performance computing. Notable contributions include innovations in distributed training of deep neural networks, geo-replicated databases, and efficient graph processing. His work has been published in top-tier conferences like NSDI, AAAI, VLDB, and SOSP. Professional Activities : PC member at OSDI 2025, EuroSys 2024/2025, FAST 2024, and SOSP 2021. Teaching includes Systems Seminar and Compiler Principles at USTC since 2017. Grants : Secured $500k/year funding from Chinese government agencies and collaborations with Huawei/Alibaba. Active in cloud-native systems and AI infrastructure research.