Find Academic Supervisors

• Planetary Science
• Astrophysics
• Geophysics
• +3 more

Wieland Dietrich is a Researcher and Research Coordinator at the Max Planck Institute for Solar System Research (MPS) , affiliated with the Planetary Science Department. His expertise lies in planetary dynamics, particularly the magnetic fields and atmospheric flows of exoplanets like Hot Jupiters, as well as convection processes in planetary cores and gas giants. Education & Employment : PhD in Physics (2009-2012): IMPRS program at MPS, Katlenburg-Lindau Postdoctoral Research Fellow (2013-2019): University of Leeds (School of Applied Mathematics) and MPS Current roles since 2022: Research Coordinator at MPS Research Focus : Investigates dynamo processes, zonal winds, and satellite measurement correlations with planetary interiors. Recent work emphasizes Hot Jupiter atmospheres and gravity dynamics of gas giants like Jupiter. Publications : Focused on exoplanet magnetism, zonal wind mechanisms, and computational models of planetary convection. Key contributions include studies on KELT-9b's magnetic fields and Jupiter's gravity moments. Awards : None explicitly mentioned in the provided texts. Labs & Teams : Active within the Planetary Science Department at MPS, contributing to interdisciplinary research on solar system and exoplanetary dynamics.

Chris KöcherView profile

Researcher

• Algorithms
• Theory & Logic
• Programming Languages
• +9 more

Chris Köcher is a Researcher at the Max Planck Institute for Software Systems (MPI-SWS) in Kaiserslautern, Germany. His work focuses on theoretical computer science, with a strong emphasis on formal methods, automata theory, and verification of complex systems. He leads research in areas such as algorithms, programming languages, cyber-physical systems, and security. His research bridges foundational theory and practical applications, addressing challenges in distributed systems, mobile systems, and privacy-preserving technologies. His research interests span formal language theory, verification of concurrent systems, and the analysis of storage mechanisms in automata. Notably, he has contributed to the study of queue automata, multi-pushdown systems, and the decidability of reachability problems in lossy systems. His work often intersects with theoretical computer science and algebraic structures, exploring topics like monoids and trace languages. Chris’s publications reflect a deep engagement with foundational questions in computer science, including the verification of cooperating multi-pushdown systems, the complexity of semilinear set separability, and the formal analysis of hard attention mechanisms in transformers. His research has implications for improving the reliability and security of software systems through rigorous mathematical foundations. He is affiliated with MPI-SWS, a leading research institution in software systems, and contributes to the institute’s mission to advance theoretical and applied research in computer science. His work is supported by collaborations within the institute and the broader academic community.

• Time Series Analysis
• Blockchain Technologies
• Business Process Management
• +8 more

Roman Vaculín is a Researcher at IBM Research, focusing on interdisciplinary domains where artificial intelligence, blockchain technologies, and data-centric workflows converge. His work spans automated machine learning, time series analysis, and secure computation via cryptographic methods like homomorphic encryption. Affiliation: IBM Research Key research areas: Time Series Analysis, Blockchain, AI Explainability, Business Process Management Across his publications, Vaculín explores: Time Series Modeling: Developing robust frameworks like TsSHAP and end-to-end architectures for forecasting and imputation. Blockchain Applications: Designing trusted AI systems, secure multi-party computation, and verifiable simulations. Automated Machine Learning: Creating toolkits for industrial AI explainability and automation. Privacy-preserving Techniques: Optimizing encrypted inference and secure decision tree protocols. His methodology often integrates formal verification with practical implementations, emphasizing efficiency and interpretability in complex systems. While no formal awards or students are documented in the provided data, his collaborative publications with institutions like IBM Research and academic partners highlight his role in advancing applied AI research.

• Computer Science
• Electrical Engineering
• Robotics
• +7 more

Pengfei Li is a prolific researcher affiliated with multiple academic institutions, including Harbin Medical University, Yale University, Beihang University, Zhejiang University, and others. His work spans interdisciplinary domains such as machine learning, robotics, remote sensing, and biomedical engineering. Research interests focus on Machine learning and deep learning for industrial and medical applications Signal processing and sensor technologies Remote sensing and geospatial data analysis Robotic control systems and exoskeleton design Code search and software engineering optimization His recent publications highlight trends in FPGA-based real-time systems, multimodal machine learning, and AI-driven diagnostics. While awards and student advising details are absent in the provided data, his contributions to IEEE journals and conferences underscore his expertise in algorithm design and applied informatics.

Leonidas GuibasView profile

Professor

• Computer Vision
• Computer Graphics
• Machine Learning
• +5 more

Leonidas Guibas is the Paul Pigott Professor of Computer Science at Stanford University, leading the Geometric Computation group. He is a Hans Fischer Senior Fellow at the Technical University of Munich (TUM), associated with the Visual Computing Focus Group under Prof. Matthias Nießner. His research bridges computer vision, graphics, and machine learning, focusing on 3D data processing, geometric modeling, and sensor networks. Guibas holds prestigious awards including the Vannevar Bush Fellowship and ACM Allen Newell Award, and is a member of the US National Academy of Engineering and American Academy of Arts and Sciences. Education: Ph.D. from Stanford University under Donald Knuth, with prior appointments at Xerox PARC, MIT, and international institutions. His work emphasizes algorithms for sensing, reasoning, and acting in physical environments, with contributions to robotics, computational geometry, and discrete algorithms. Research interests span 3D vision (e.g., generative models for shape synthesis), deep learning architectures for spatiotemporal data, and multimodal sensor integration. Recent projects include object pose estimation, functional relationship learning in scenes, and deformation-aware 3D model retrieval. Publications highlight advancements in 3D reconstruction, point cloud analysis, and geometric deep learning. His TUM fellowship supported work on digital twins and visual computing, emphasizing high-fidelity environmental modeling. Awards also include IEEE and ACM Fellowships, underscoring his impact on theoretical and applied computer science.

Benjamin BrossView profile

Part-Time Lecturer

• Video Coding
• Signal Processing
• Machine Learning
• +3 more

Benjamin Bross is a part-time lecturer at HTW University of Applied Sciences Berlin and heads the Video Coding Systems group at Fraunhofer Heinrich Hertz Institute. He specializes in video coding standards, including HEVC (H.265) and VVC (H.266), contributing to their development and standardization. His work emphasizes open-source implementations like VVenC and VVdeC, deployed in broadcast and streaming systems. Education: Dipl.-Ing. in Electrical Engineering (RWTH Aachen University, 2008). Active in ITU-T VCEG and ISO/IEC MPEG since 2010, leading core experiments and editing key standards. Recognized with IEEE Best Paper (2013), SMPTE Merit (2014), and an Emmy (2017) for HEVC contributions. Research focuses on advanced compression techniques, machine learning integration, and real-time encoding. His team develops VVC tools for 4K/UHD, low-latency streaming, and adaptive bitrate systems. Recent work includes optimizing partitioning strategies and reducing encoding complexity in VVC implementations. Awards highlight his impact on video technology: IEEE Consumer Electronics Best Paper (2013), SMPTE Journal Certificate (2014), and an Emmy for HEVC (2017). Teaching emphasizes practical coding standards and their applications in multimedia systems.

• Wireless Communication
• Machine Learning
• Internet of Things (IoT)
• +3 more

Aderemi Aaron-Anthony Atayero is an academic affiliated with the Department of Electrical Engineering and Information Engineering at Covenant University, Nigeria. His research focuses on telecommunications, wireless communication systems, IoT applications, and machine learning, with a strong emphasis on path loss modeling, signal processing, and smart city technologies. He has contributed to over 30 publications since 2005, collaborating extensively with researchers like Segun I. Popoola, Sanjay Misra, and Simon K. Hinga. His work spans theoretical and applied domains, including 5G mmWave models, botnet detection in IoT networks, and smart city infrastructure. Notable projects include the development of a low-intensity light imaging probe for medical applications and a cellular RSS dataset for roaming analysis. His research has practical implications for urban communication systems, healthcare technology, and cybersecurity.

• Nuclear Physics
• Nuclear Astrophysics
• Detector Development
• +3 more

Dr. Andreas Wagner is a leading researcher at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR), serving as Head of the Nuclear Physics Division and Head of the Radiation Source ELBE. His work focuses on applied nuclear physics, including nuclear astrophysics, detector development, and radiation technology. He leads the R3B collaboration at GSI/FAIR and chairs the Helmholtz portfolio initiative for Detector Technologies and Systems. His research spans nuclear data applications, materials science using positron annihilation spectroscopy, and medical physics applications in proton therapy verification. Dr. Wagner collaborates internationally, with projects at HZDR, GSI, and TU Dresden. He has contributed to advanced experimental facilities like the ELBE Linac and the Radiation Source ELBE. Teaching activities include courses on nuclear astrophysics, particle accelerators, and detector technologies at TU Dresden. His work bridges fundamental physics with applied technologies, emphasizing interdisciplinary research in energy, materials, and medical physics.

Armin IskeView profile

Professor

• Numerical Approximation
• Applied Mathematics
• Kernel Methods
• +4 more

Prof. Dr. Armin Iske is a Full Professor of Numerical Approximation at the University of Hamburg's Department of Mathematics, within the Faculty of Mathematics, Computer Science and Natural Sciences. He holds a PhD from the University of Göttingen (1994) and habilitation from TU Munich (2002). His research focuses on numerical approximation, kernel-based methods, computational fluid dynamics, and medical imaging. He has held academic positions globally, including visiting roles at ANU (Australia) and the University of Leicester (UK). Research interests include scattered data approximation, adaptive particle methods for flow simulation, and high-dimensional data analysis. He has authored 118+ publications, including works on kernel interpolation, medical imaging reconstruction, and machine learning applications. He serves on editorial boards for journals like Advances in Computational Mathematics and Sampling Theory . His contributions span interdisciplinary projects, such as SFB/TRR 181 on energy transfer in atmosphere and ocean, and collaborations in nanotechnology for brain interfaces. His work bridges theoretical mathematics with practical applications in engineering and biosciences.

Giovanni CiottiView profile

Researcher

• Manuscript Studies
• Digital Humanities
• Material Analysis
• +3 more

Dr. Giovanni Ciotti is an academic affiliated with the University of Bologna and the Cluster of Excellence 'Understanding Written Artefacts' (UWA) at the University of Hamburg. He serves as Project Lead for the initiative 'Towards a Comprehensive Approach to the Study of South Indian Palm-Leaf Manuscripts' (2020–2025). His research focuses on material analysis of manuscripts, digital palaeography, and the intersection of technology with traditional textual studies. He has contributed to projects such as the Palm Leaf Manuscript Profiling Initiative (PLMPI) and the NETamil network exploring Tamil intellectual exchange networks. His work integrates scientific methods like FTIR spectroscopy and chemometrics with humanities research, addressing questions of provenance, conservation, and textual transmission. He has collaborated on initiatives like the High Performance Lab and Data Linking Lab, applying advanced technologies to cultural heritage preservation. Dr. Ciotti has published extensively on topics including manuscript materiality, digital encoding strategies for Indic texts, and interdisciplinary approaches to South Asian literary traditions. His research also engages with the technical aspects of manuscript production, such as binding techniques and paratextual analysis.

Volker RothView profile

Professor

• Computer Science
• Information Security
• Applied Cryptography
• +5 more

Volker Roth is a Professor in Computer Science at Freie Universität Berlin, heading the Secure Identity Research Group since 2009. He has held positions as Senior Researcher at FXPAL (Palo Alto), Visiting Professor at the Peter Kiewit Institute (University of Nebraska at Omaha), CTO of OGM Laboratories (Omaha), Senior Researcher and Deputy Department Head at Fraunhofer Gesellschaft, and Postdoc at ICSI (Berkeley). He earned his Dr.-Ing. and Dipl.-Inform. from Technische Hochschule Darmstadt. Education: Dr.-Ing. (PhD), Dipl.-Inform. (M.Sc.) in Computer Science from TU Darmstadt His research focuses on privacy and security in information systems , emphasizing the psychological acceptability of security mechanisms . Key themes include applied cryptography , human-computer authentication , and usable security . He designs security mechanisms that are simple but effective and function without a common root of trust. His recent work analyzes email encryption adoption over 27 years (81M+ emails) and explores cryptocurrency wallet usability , touch authentication , and shoulder surfing defenses . He has developed privacy-preserving data collection pipelines and contributed to standards in key management, email security, and mobile authentication. Scientific awards include: Best Paper at MobileHCI 2016 Honorary Mention at CHI 2021 INI-GraphicsNet Best System Paper Award 2006 Best Student Paper at NSDI 2004 Volker Roth teaches computer science and leads research in secure identity systems. His consultation hours are Tuesdays at 18h via Webex, with contact details available on his personal page .

• Human-Computer Interaction (HCI)
• Machine Learning
• Cognitive Science
• +3 more

Kyoungwon Seo is a Professor affiliated with Hanyang University, actively contributing to interdisciplinary research spanning Human-Computer Interaction (HCI), Machine Learning, and Cognitive Science. His work focuses on applying advanced technologies like VR, EEG analysis, and large language models to address challenges in healthcare diagnostics, education, and workplace design. Co-founded the Imagine Lab at Hanyang University, exploring innovative HCI applications. Expertise in gamification strategies for manufacturing workforce behavior modification. Pioneer in developing EEG-SSVEP based machine learning models for early detection of Mild Cognitive Impairment (MCI). His research bridges theoretical foundations in decision theory (e.g., ambiguity models) with applied work in educational technology, including AI-enhanced learning platforms and chatbot systems for career counseling and critical thinking assessment.

• Theoretical Physics
• Quantum Materials
• Condensed Matter Physics
• +3 more

Zihong Liu is a Research Fellow affiliated with the Chair of Theoretical Physics I at the University of Würzburg. His research focuses on theoretical physics, quantum materials, and computational physics, contributing to advancements in condensed matter systems and astrophysical phenomena. Located at Hubland Süd, Geb. M1 in Würzburg, his work integrates interdisciplinary approaches across theoretical and experimental domains. Key areas of interest include the study of quantum materials' properties and computational modeling of physical systems. While specific publications are not detailed here, his contributions align with the department's broader research in theoretical physics and applied computational methods. He collaborates within the Theoretical Physics I research group and contributes to teaching and seminar activities at the university. Zihong Liu's academic background and educational details are not explicitly documented in the provided text, but his role indicates active engagement in cutting-edge research within his field. His current affiliation emphasizes the university's commitment to advancing theoretical and applied physics through collaborative projects and innovative methodologies.

Uwe CzarnetzkiView profile

Professor

• Plasma Physics
• Low-Temperature Plasmas
• Atomic Physics
• +4 more

Prof. Uwe Czarnetzki is a Professor of Experimental Physics at Ruhr University Bochum, serving as Dean of the Faculty of Physics and Astronomy since 2008. His expertise lies in plasma physics, focusing on low-temperature plasmas, diagnostic techniques like laser spectroscopy, and plasma dynamics modeling. He holds a professorship since 2001 and has led roles such as Managing Director of the Institute for Experimental Physics (2004–2006). Education: 1979–1985: Diploma in Physics, University of Essen 1986–1991: PhD in Physics, University of Essen 1993–1999: Habilitation in Experimental Physics, University of Essen Research Interests: Investigations into plasma heating mechanisms (e.g., helicon waves, stochastic heating), particle transport, and electric field measurements. Key methods include laser spectroscopy and Thomson scattering. Current topics include micro-discharges at atmospheric pressure and nonlinear plasma oscillations. His work bridges experimental studies with computational modeling. Awards & Affiliations: JSPS-AvH Fellowship (1992–1993, Kyushu University) Editorial Board Member: Journal of Physics D and Japanese Journal of Applied Physics Member: Scientific Advisory Board of Leibniz Institute for Plasma Science and Technology Leadership & Roles: Deputy Speaker of Research Training Group 1051 (2005–2009), Chairman of the International Center of Excellence in Plasma Science (2006–2008). Active in German Physical Society, Institute of Physics, and Humboldt Club Germany.

• Machine Learning
• Neural Networks
• Numerical Analysis
• +3 more

Shokhrukh Ibragimov is a Researcher at the Department of Mathematics and Computer Science, University of Münster. He is affiliated with the Applied Mathematics Münster: Institute for Analysis and Numerical Analysis. His research focuses on machine learning, particularly neural networks and optimization challenges in high-dimensional spaces. Collaborating with prominent figures like Arnulf Jentzen, he investigates topics such as the curse of dimensionality, gradient descent convergence, and the behavior of local minima in neural network training. His work bridges theoretical analysis and computational methods, contributing to advancements in deep learning and numerical analysis. Research interests include the mathematical foundations of neural networks, numerical approximations for high-dimensional problems, and the theoretical underpinnings of optimization algorithms in machine learning. His recent publications address critical gaps in understanding neural network limitations and the effectiveness of gradient-based methods.