Prof. Stefan Leutenegger is a tenure-track Assistant Professor at Technische Universität München (TUM), leading the Machine Learning for Robotics group within the TUM School of Computation, Information, and Technology. Previously, he held roles as Senior Lecturer (2018–2021) and Lecturer (2014–2018) at Imperial College London's Dyson Robotics Lab, where he founded the Smart Robotics Lab. He earned his PhD (2014) from ETH Zurich, focusing on autonomous solar-powered aircraft navigation, and holds BSc (2006) and MSc (2009) in Mechanical Engineering from ETH Zurich. His research centers on mobile robotics, particularly enabling robots (e.g., drones) to perceive and navigate complex environments using machine learning and sensor data fusion. Key focus areas include SLAM, event-based vision, 3D reconstruction, and autonomous exploration. He has pioneered algorithms like BRISK (2011), OKVIS (2014), and ElasticFusion (2016), advancing real-time robotics perception. Notable Awards: Imperial College President's Award (2018), Best ECCV Paper (2016), ETH Medal for Dissertations (2015). Labs: TUM's Machine Learning for Robotics Group, Imperial's Smart Robotics Lab. Publications: Over 100 papers, including seminal works in CVPR, ECCV, and Robotics: Science and Systems. Current projects include DigiForests (forest inventory via robotics), aerial additive manufacturing, and object-centric semantic mapping. His work bridges theory and practice, with applications in autonomous drones, construction robotics, and human-robot interaction.
Jeffrey F. Brock is the Dean of the School of Engineering & Applied Science and the William S. Massey Professor of Mathematics at Yale University. He holds the Zhao and Ji Chair in Mathematics. His research focuses on low-dimensional geometry and topology, particularly hyperbolic geometry and its applications to data analysis. He completed his undergraduate studies at Yale and earned his Ph.D. from UC Berkeley. He held positions at Stanford, the University of Chicago, and Brown University, where he chaired the Mathematics Department from 2013 to 2017 and founded Brown’s Data Science Initiative in 2016. He joined Yale in 2018, serving as inaugural Dean of Science in the Faculty of Arts and Sciences until assuming his current role in 2022. He is a Guggenheim Fellow and Fellow of the American Mathematical Society. His research spans hyperbolic 3-manifolds, Teichmüller dynamics, and geometric methods in data science. Notable contributions include work on Thurston’s geometrization program, classification of hyperbolic manifolds, and applications of geometric topology to complex datasets. He co-authored foundational papers on ending laminations, Weil-Petersson geometry, and renormalized volume. His recent work bridges pure mathematics with applied challenges, such as algorithmic detection of medical imaging patterns. Awarded the Guggenheim Fellowship (2008) and AMS Fellow (2017), Brock has also led interdisciplinary initiatives at Brown and Yale. His administrative roles include overseeing engineering, natural sciences, and data science programs. Beyond academia, he co-founded the Vijay Iyer Trio, showcasing his passion for music performance and creativity.
Amadeus Gebauer is a Researcher at the Chair of Computational Mechanics within the Institute for Computational Mechanics at the Technical University of Munich (TUM), serving as a Research Associate since 2019. His work specializes in computational biomechanics with emphasis on cardiac mechanics modeling, growth and remodeling processes, and multi-physics simulation frameworks. Education: Master of Science (M.Sc.) in Mechanical Engineering, Technical University of Munich, 2019 Research Interests: Gebauer's research centers on cardiac mechanics modeling, including growth and remodeling of cardiac tissue, cardiac active tissue mechanics, and medical image processing. He develops advanced computational methods for parallel and high performance computing, particularly through the 4C multi-physics simulation framework. His work integrates constrained mixture models to simulate organ-scale biological processes, bridging computational mechanics with clinical cardiology applications and focusing on mechanobiological stability in cardiac systems. Publication Trends: Gebauer's publications (2018-2025) demonstrate consistent innovation in computational cardiology, primarily using constrained mixture models to address cardiac growth and remodeling. His recent work introduces adaptive integration techniques for history variables and homogenized modeling approaches, while expanding into software benchmarking for cardiac elastodynamics and gastric motility simulations. These contributions highlight his expertise in developing robust numerical methods for multi-physics biomedical problems, with increasing focus on patient-specific applications and high-performance computing solutions. Teaching and Advising: Gebauer teaches core computational mechanics courses including Finite Elemente and Numerische Festkörpermechanik across multiple semesters. He has supervised diverse student projects ranging from term papers to Master's theses, with notable collaborations including Maximilian Grill's shoulder biomechanics research (2020) and Janina Datz's artery geometry framework development (2021). His advising consistently focuses on cardiac mechanics, computational modeling, and medical device simulation. Research Environment: As part of Professor Wolfgang A. Wall's Institute for Computational Mechanics (LNM) at TUM, Gebauer contributes to a leading research group in computational solid/fluid mechanics. The LNM develops the 4C simulation framework for complex engineering and biomedical challenges, with current emphasis on cardiac growth modeling, multi-physics integration, and high-performance computing applications in personalized medicine.
Prof. Peter Scholze is a leading mathematician at the Max Planck Institute for Mathematics in Bonn, specializing in algebraic geometry and arithmetic geometry. He holds the academic rank of Professor and is part of the Arbeitsgruppe Algebraische Geometrie und Darstellungstheorie. His research focuses on foundational questions in algebraic geometry, number theory, and representation theory, particularly through the lens of the Langlands program, p-adic Hodge theory, and perfectoid spaces. Scholze has pioneered geometric approaches to the local Langlands correspondence and introduced revolutionary concepts like prismatic cohomology and condensed mathematics. He actively contributes to academia through advanced courses on topics such as geometrization of the Langlands program, étale cohomology, and condensed mathematics. His work bridges algebraic geometry with representation theory, addressing fundamental problems in arithmetic geometry and p-adic analysis. Scholze’s research outputs include seminal papers on perfectoid spaces, prismatic cohomology, and the geometrization of local Langlands correspondence. He collaborates extensively with leading mathematicians globally, contributing to collaborative research initiatives like the ARGOS seminar and the Habiro ring project. His teaching engagements include advanced lectures on algebraic geometry, representation theory, and p-adic geometry, reflecting his commitment to training the next generation of researchers. Despite no explicitly listed awards in the provided text, Scholze is widely recognized as a Fields Medalist (2018) and a leading figure in modern mathematics.
Stefanie Mueller is the TIBCO Career Development Associate Professor at MIT's Electrical Engineering and Computer Science Department, with joint affiliation in Mechanical Engineering. She leads the HCI Engineering Group at the Computer Science and Artificial Intelligence Laboratory (CSAIL), focusing on advancing fabrication techniques through hardware/software innovations that enable novel object interactions. Develops computational fabrication methods combining photochromic dyes, lenticular lenses, birefringent materials, and optical illusions Co-chaired ACM CHI 2023 and ACM UIST 2020 program committees Recipients of 9 MIT EECS Best Undergraduate Researcher Awards among mentees Her research spans four key directions: Appearance-changing Objects: Photo-Chromeleon (ACM UIST 2019), Lenticular Objects (ACM UIST 2021), and Polagons (ACM CHI 2023) demonstrate reprogrammable surfaces through advanced materials and optical engineering. Tracking Systems: InfraredTags (ACM CHI 2022) and G-ID (ACM CHI 2020) enable passive object tracking via infrared markers and slicing artifacts. Embedded Sensing: MechSense (ACM CHI 2023) and Sprayable User Interfaces (ACM CHI 2020) integrate sensing capabilities into complex geometries. Curved Surface Prototyping: FlexBoard (ACM CHI 2023) and CurveBoard (ACM CHI 2020) develop specialized tools for non-planar electronics. Her recent publications focus on functionality segmentation (UIST 2023), fluorescent markers (UIST 2023), and machine-knitted haptics (UIST 2023). These works combine machine learning, material science, and interactive design principles to push fabrication boundaries. Scientific recognition includes: 2022 MIT Technology Review Innovators Under 35 2020 Microsoft Research Faculty Fellowship 2020 Alfred P. Sloan Research Fellowship 2019 ACM UIST Best Paper Award 2019 NSF CAREER Award 2018 MIT EECS Outstanding Educator Award 2017 Forbes 30 Under 30 in Science Mentoring 9 PhD students and over 20 master's students, her lab has produced 20+ publications at top HCI conferences. She redesigned MIT's 6.810 Engineering Interactive Technologies course during the pandemic, maintaining hands-on learning through home electronics kits and Slack-based collaboration.
Yin Tat Lee is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering , University of Washington, and a Senior Principal Researcher in Microsoft AI. His research spans convex optimization , convex geometry , graph algorithms , online algorithms , and differential privacy , with applications in machine learning and theoretical computer science.
Andreas Rietbrock is Professor and Director of the Geophysical Institute (GPI) at the Karlsruhe Institute of Technology (KIT) , Germany, where he also serves as Dean of Studies for Geophysics . He is a leading expert in earthquake seismology, seismic tomography, and subduction zone dynamics, with a strong focus on integrating advanced observational techniques and computational methods. Education: While specific degrees are not listed in the provided text, his extensive publication record and leadership roles indicate advanced academic training in geophysics and seismology. Research Interests: His work spans a wide range of topics including: Seismic imaging of subduction zones (e.g., Nazca, Lesser Antilles) Earthquake rupture dynamics and fault mechanics Volcanic seismology and magma transport Full waveform inversion and AI-enhanced seismic analysis Distributed Acoustic Sensing (DAS) applications Induced seismicity and reservoir monitoring Research Trends: His recent publications (2022–2025) emphasize the use of dense seismic arrays, AI-based data processing, and multi-method tomography to study complex tectonic environments. Key themes include high-resolution imaging of slab structures, fluid migration in subduction zones, and the integration of DAS and machine learning for seismic monitoring. Scientific Contributions: Andreas has led major international projects such as the ANTICS Large-N deployment in Albania and the VoiLA project in the Lesser Antilles. He has published extensively in top-tier journals like Nature , Geophysical Research Letters , and Journal of Geophysical Research , with over 200 peer-reviewed articles. Teaching and Supervision: He teaches courses such as "Introduction to Geophysics II", "Seismology", and "Current Topics in Seismology and Risk". While specific student names are not listed, his role as Dean and principal investigator on numerous projects indicates active supervision of graduate students and postdocs. Labs and Teams: He leads the seismology group at GPI, coordinating large-scale deployments of seismic instruments, including ocean-bottom seismometers and fiber-optic DAS systems. His team collaborates globally with institutions in Europe, South America, and Asia.
Prof. Igors Gorbovickis is an Associate Professor of Mathematics at the Department of Mathematics, School of Computer Science and Engineering, Constructor University (formerly Jacobs University Bremen). His research focuses on complex dynamical systems, including topics such as renormalization theory, bifurcation analysis, Julia sets, and applications to mathematical physics. He also contributes to discrete geometry, particularly exploring conjectures like the Kneser-Poulsen problem. His work bridges pure mathematics with interdisciplinary applications, emphasizing rigorous analysis of nonlinear systems and geometric configurations. Key areas of investigation include critical point accumulations, Hausdorff dimension estimates, and equidistribution phenomena in parameter spaces. Recent publications highlight advancements in understanding chaotic systems, circle maps, and the interplay between algebraic structures and dynamical behavior. Prof. Gorbovickis collaborates internationally, with co-authored papers appearing in journals like Advances in Mathematics , Ergodic Theory and Dynamical Systems , and Nonlinearity . His office is located at Research I, Room 128 on the Constructor University campus in Bremen, Germany.
Prof. Dr. Urs Hartl is a faculty member in the Department of Mathematics and Computer Science at the University of Münster, affiliated with the Faculty of Mathematics and Computer Science. He is an Investigator in Mathematics Münster and a member of the Collaborative Research Centre (CRC) 1442 'Geometry: Deformations and Rigidity.' His research focuses on arithmetic geometry, representation theory, algebraic number theory, and arithmetic of function fields. He holds a prominent position in the field, contributing to areas such as Shimura varieties, p-adic Hodge theory, and the Langlands program. Affiliations: Member of CRC 1442 Geometry Investigator in Mathematics Münster Research Interests: Arithmetic algebraic geometry Algebraic number theory Arithmetic of function fields Structure theory of Shimura varieties p-adic Hodge theory p-adic Langlands programme Model theory Recent Publications: Hartl's recent work includes studies on moduli stacks of global G-shtukas, periods of Drinfeld modules, and p-adic Galois representations. His research emphasizes foundational contributions to arithmetic geometry and number theory, often involving collaborations with leading mathematicians such as Rajneesh Kumar Singh and Eva Viehmann. Grants & Advising: Hartl’s involvement in CRC 1442 reflects his leadership in geometric research. While specific advising details are not provided, his extensive publications suggest active mentorship in advanced mathematical research. Labs/Teams: Collaborates within the Mathematics Münster research group and the CRC 1442 team, focusing on geometric and arithmetic structures.
Vladimir Spokoiny is a Professor at the Departments of Mathematics and Economics of the Humboldt University of Berlin and Head of the Research Group "Stochastic Algorithms and Nonparametric Statistics" at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) in Berlin, Germany. His research spans multiple areas of statistics, machine learning, and financial mathematics, with significant contributions to nonparametric statistics, high-dimensional data analysis, and statistical methods in finance. Spokoiny received his M.Sc. in applied mathematics from the Moscow Institute of Railway Engineering in 1981 and his Ph.D. in mathematics from Lomonosov Moscow State University in 1988. He completed his Habilitation at Humboldt University in 1996. His academic career includes positions at the All-Union Institute of Railway Transport in Moscow, the Institute for Information Transmission Problems in Moscow, and the Institute for Applied Analysis and Statistics in Berlin before joining the Weierstrass Institute and Humboldt University where he has been a professor since 2002. Spokoiny's research focuses on adaptive nonparametric smoothing and hypothesis testing, high dimensional data analysis, statistical methods in finance, image analysis with applications to medicine, classification, and nonlinear time series. His work often addresses the challenges of nonstationarity in time series data and develops innovative methods for volatility estimation and risk management. He has made significant contributions to the development of adaptive weights smoothing procedures, which have applications in image processing, community detection, and manifold learning. His recent work has expanded into high-dimensional statistics, Bayesian inference, and optimization methods for machine learning, with publications demonstrating novel approaches to Gaussian approximation, Laplace methods, and statistical inference in non-Euclidean spaces. Spokoiny has supervised numerous PhD students including Oliver Reiss, Danilo Mercurio, Ying Chen, Elmar Diederichs, and Mstislav Elagin, whose research has focused on mathematical finance, time series analysis, and statistical methods. He serves as an Associate Editor for The Annals of Statistics (since 2004) and Statistics and Decisions (since 2002), and has previously served on the editorial board of the Journal of Statistical Planning and Inference. His professional activities include reviewing for major statistical journals including Annals of Statistics, Bernoulli, Econometrica, and Journal of American Statistical Association, as well as reviewing grant proposals for the National Science Foundation (USA), German Research Foundation, and Netherlands Organisation for Scientific Research. Spokoiny is a member of several professional societies including the International Statistical Institute, American Statistical Association, Institute of Mathematical Statistics, and Bernoulli Society. He is fluent in Russian (mother tongue), English, and German, and has good knowledge of French. His research group at WIAS focuses on developing novel statistical methodologies with applications across various scientific domains, particularly emphasizing adaptivity and robustness in complex data environments. The group's work has significant implications for financial risk management, medical imaging, and machine learning applications, with recent publications addressing fundamental questions in high-dimensional statistics and nonparametric inference.
Prof. Dr. Harald Lesch is a distinguished Professor of Theoretical Astrophysics at Ludwig Maximilian University of Munich and Lecturer in Natural Philosophy at the Munich School of Philosophy. Born on July 28, 1960 in Giessen, he completed his physics studies at Justus Liebig University of Giessen and Rheinische Friedrich-Wilhelms University of Bonn, earning his doctorate in 1987. After research positions at the Heidelberg-Königsstuhl State Observatory and University of Toronto, he received his habilitation at the University of Bonn in 1994. Lesch is renowned for making complex scientific concepts accessible to the public. His research interests span theoretical astrophysics, cosmology, gravitational waves, and the philosophical implications of scientific discoveries. He has authored numerous books exploring the relationship between science, philosophy, and everyday life, focusing particularly on how cosmic phenomena connect to human existence. His television career began in 1998 with 'Alpha Centauri' and 'The Physics of Albert Einstein' on BR-alpha. Since September 2008, he has presented ZDF's science magazine, which evolved from 'Abenteuer Forschung' to 'Leschs Kosmos' in 2014, and most recently to 'Terra X Harald Lesch' in 2024. In February 2016, he launched the YouTube channel 'Terra X Lesch & Co,' further expanding his science communication efforts. Patron of the Children's University Weimar since 2018 Presenter of 'The Big Questions' since 2023 Host of numerous documentary series including 'Fascination Universe' (2009-2023), 'Supercodes - The Secret Formulas of Nature' (2021/2022), and 'Das Rätsel Zeit' (2024) Lesch has received over 20 major awards recognizing his exceptional contributions to science communication, including the Communicator Prize (2005), multiple Deutscher Fernsehpreis awards (2018, 2020), and Germany's highest honor, the Verdienstorden der Bundesrepublik Deutschland (2023). His work bridges the gap between academic research and public understanding, making him one of Germany's most influential science communicators.
Prof. Dr. Kai Cieliebak is a Professor of Mathematics at the University of Augsburg, where he holds the Chair of Analysis and Geometry within the Institute of Mathematics under the Faculty of Mathematics, Natural Sciences, and Materials Engineering. He has been at Augsburg University since 2012, following a professorship at Ludwig-Maximilians-Universität München from 2001-2012. His research group includes several researchers and postdocs working on symplectic geometry and related fields. Dr. Cieliebak earned his Diplom in mathematics summa cum laude from Ruhruniversität Bochum in 1992, with thesis on "Pseudo-holomorphe Kurven und periodische Orbits auf Cotangential Bündeln" under advisor H. Hofer. He completed his PhD in mathematics at ETH Zürich in 1996, with thesis "Symplectic boundaries: closed characteristics and action spectra," also advised by H. Hofer. His academic journey included positions at Harvard University, Stanford University, and research at IBM Zürich before his professorships in Munich and Augsburg. Prof. Cieliebak's research focuses on symplectic and contact geometry , with significant contributions to understanding symplectic manifolds, Lagrangian and Legendrian knots, Stein manifolds, and string topology. His work in Hamiltonian dynamics explores variational methods, periodic orbits, and celestial mechanics problems, particularly the restricted three-body problem. In global analysis , he investigates solution spaces of elliptic PDEs and symplectic field theory. His approach often bridges differential geometry, topology, and dynamical systems, with applications to mathematical physics. Over the past decade, Prof. Cieliebak's publications reveal a consistent focus on symplectic homology, Floer theory, and their applications to geometric problems. His work shows increasing integration of algebraic structures with geometric methods, particularly in cyclic homology and string topology. Recent research demonstrates strong collaboration with Urs Frauenfelder on celestial mechanics problems, applying symplectic techniques to the restricted three-body problem and related orbital dynamics. Prof. Cieliebak has secured significant research funding throughout his career, including multiple DFG grants under project codes CI 45/1 through CI 45/12, NSF grants, and participation in European Science Foundation networking programs. His most notable grants include "Foundations of Symplectic Field Theory" (2009-2015) and the current "Rabinowitz Floer Homology" project (since 2023), both in collaboration with U. Frauenfelder. He has mentored numerous researchers and maintains an active research group at Augsburg University, including postdocs and collaborators working on symplectic geometry problems. His team includes researchers such as Dr. Filip Broćić, Zhen Gao, Dr. Hanna Häußler, Emilia Konrad, Shuaipeng Liu, Dominik Meidert, Dr. Airi Takeuchi, Dr. Evgeny Volkov, Milan Zerbin, and PD Dr. Lei Zhao. Prof. Cieliebak has also organized numerous workshops on symplectic geometry, including the annual "Symplectic Field Theory" workshop series.
Kord Eickmeyer is a Lecturer at Technische Universität Darmstadt in the Department of Mathematics, specializing in the mathematical logic group. He holds a PhD in mathematics from Humboldt University Berlin and has held postdoctoral positions at TU Darmstadt (2011–2017) and the National Institute of Informatics in Tokyo (2011–2013). His research focuses on finite model theory, graph structure theory, and computational complexity, particularly in descriptive and parameterized complexity, as well as randomization and derandomization techniques. Research interests include exploring the boundaries of computational complexity through logical frameworks, analyzing graph structures for efficient algorithm design, and investigating the role of randomness in computation. His work bridges theoretical computer science and mathematical logic, with applications in algorithm design and formal methods. Publications span topics from model-checking on ordered structures to gap-planar graphs and randomized logics. Collaborations include prominent institutions like the National Institute of Informatics and Humboldt University Berlin. No scientific awards are explicitly listed, but his extensive academic contributions reflect a strong research trajectory. Advising and grants are not detailed in the provided text, though his academic career includes supervision roles during his PhD and postdoctoral phases. His involvement with the mathematical logic group at TU Darmstadt highlights collaborative research efforts in foundational areas of computer science and mathematics.
Katy Börner is a Professor affiliated with Indiana University, Bloomington, USA. Her research focuses on data visualization, scientometrics, and the science of science, with contributions to tools like Network Workbench (NWB) and Sci2. She leads interdisciplinary projects such as the Human Reference Atlas and explores visualization literacy in education and public health. Her work spans virtual reality applications, biomedical knowledge networks, and AI-driven scientific discovery. Key research interests include mapping scientific collaboration networks, analyzing scholarly publications, and developing visualization frameworks for big data. She collaborates widely with institutions like NIH and VIVO, advancing open science and interdisciplinary research. Her projects often bridge computational methods with human-centric design, enhancing understanding of complex systems in health, technology, and social sciences. Publications highlight innovations in interactive visualization tools (e.g., opioid crisis research networks), data integration (Human Reference Atlas), and AI applications in biomedical research. She emphasizes translating data into actionable insights through visual analytics, impacting policy, education, and healthcare.
Prof. Dr. Markus Bachmayr is a full professor at the Institute for Geometry and Practical Mathematics, RWTH Aachen University, holding the chair for Applied Mathematics. His research focuses on nonlinear approximation, high-dimensional partial differential equations (PDEs), uncertainty quantification, and numerical methods in quantum chemistry. He leads the ERC Consolidator Grant project Computational Complexity of Highly Nonlinear Approximations (COCOA) and contributes to CRC 1481 Sparsity and Singular Structures, and RTG 2326 Energy, Entropy, and Dissipative Dynamics. His recent work emphasizes adaptive low-rank and sparse approximation techniques for parametric and stochastic PDEs, including applications in radiative transfer and poroviscoelastic flow modeling. He serves as Editor-in-Chief of Foundations of Computational Mathematics and Associate Editor for multiple journals. Scientific Awards: John Todd Award 2013 Borchers Plakette 2014 Erwin Wenzl Preis 2007 He has taught courses such as Numerische Analysis I/II, Numerische Mathematik für Elektrotechniker, and seminars on numerical methods and approximation theory.
