Carl Vondrick is a Professor in the Department of Computer Science at Columbia University. His research focuses on creating robust and versatile perception systems that leverage video and interaction with the natural world, with applications in 3D reconstruction, visual question answering, and robot manipulation. Former research scientist at Google Visiting researcher at Cruise Education: PhD (2017) from MIT, advised by Antonio Torralba BS (2011) from UC Irvine, advised by Deva Ramanan His research explores multimodal approaches for cross-task and cross-modal transfer, scene dynamics, audiovisual perception, interpretable models, and spatial awareness systems. The lab emphasizes zero-shot generalization and neuro-symbolic methods while addressing safety and robustness in AI systems. Key publication trends include: 2025: Video generation for robotics 2024: Differentiable rendering and cross-modal reasoning 2023: Robust perception and 3D modeling Scientific Awards: 2024 PAMI Young Researcher Award 2021 NSF CAREER Award Teaching Roles: Teaching Computer Vision II (2021-2025), Computer Vision I (2018-2019), and Representation Learning (2020-2022). Advising: Advises 8 current PhD students and has mentored 5 graduated students now at institutions like MBZUAI and UMD. The lab recruits 1-2 PhD students annually through Columbia’s PhD program. Grants and Collaborations: Funded by NSF, DARPA, Toyota Research Institute, Amazon Research, and Google.
Christian Theobalt is a Professor of Computer Science at Saarland University and Scientific Director of the Visual Computing and Artificial Intelligence Department at the Max Planck Institute for Informatics . He leads the Saarbruecken Center for Visual Computing as a strategic partnership between Google and MPI. PhD in Computer Science (2005) from MPI-INF/Saarland University Postdoctoral Researcher at MPI (2005-2007) Visiting Assistant Professor at Stanford (2007-2009) His research focuses on the intersection of Computer Graphics, Computer Vision, and Artificial Intelligence , with specializations in: 3D/4D Human Reconstruction Neural Rendering Performance Capture Geometric Deep Learning Volumetric Video Quantum Visual Computing Recent article trends show emphasis on: Quantum computing applications in visual reconstruction Neural rendering with radiance fields Human motion capture from egocentric views Gesture-language interaction modeling Multi-modal scene understanding Real-time free-viewpoint rendering Scientific Awards : Fellow of EUROGRAPHICS (2022) CVPR Best Student Paper Honorable Mention (2020) ERC Consolidator Grant (2017) Karl Heinz Beckurts Award (2017) Busy Beaver Teaching Award (2016) ERC Starting Grant (2013) Advising over 50 students and researchers including: Current researchers: Viktor Rudnev, Linjie Lyu, Mohit Mendiratta Postdocs: Kwang In Kim, Kiran Varanasi Alumni: Franziska Mueller (Google), Dushyant Mehta (Qualcomm), Ayush Tewari (MIT) Grants include ERC grants, Google Glass Research Award, and multiple industry partnerships. His lab maintains cutting-edge facilities with: Multi-camera capture systems Quantum annealing infrastructure HDR radiance field technology GPU clusters for AI research Time-of-flight imaging systems Event camera arrays
Prof. Niki Kilbertus is an Assistant Professor at the Technical University of Munich (TUM) in the Department of Informatics, and Group Leader at Helmholtz AI. His research focuses on causal machine learning, ethical AI systems, and applications in healthcare, climate science, and dynamical systems. He earned his PhD from the University of Cambridge (2020) and has held positions at DeepMind, Google, and Amazon during his studies. His research interests include causal discovery, fairness in AI, counterfactual reasoning, and integrating physics-based constraints into neural networks. Key contributions include foundational work on fair machine learning (e.g., avoiding discrimination through causal models) and developing methods for causal inference in complex systems like healthcare and climate modeling. Recent work emphasizes generative models for causal interventions, robust treatment effect estimation, and physically consistent neural differential equations. He leads a large interdisciplinary group with over 20 students and postdocs working on projects funded by Helmholtz Association, ERC, and industry collaborations. Notable awards include the Leopoldina Prize for Young Scientists (2024) and membership in the Junge Akademie. His lab maintains active partnerships with ELLIS, MCML, and the Zuse Institute Berlin.
Prof. Kai S. Exner is a Professor of Theoretical Inorganic Chemistry at the University of Duisburg-Essen's Faculty of Chemistry and a member of the Zentrum für Medizinische Biotechnologie (ZMB). His research focuses on electrocatalysis , particularly optimizing electrode materials for energy applications such as batteries, electrolyzers, and fuel cells. He employs computational methods like ab initio calculations and microkinetic modeling to bridge theoretical insights with experimental and industrial applications, emphasizing sustainable catalyst design without relying on noble metals. His work integrates basic research with applied medical biotechnology through ZMB collaborations, though his primary affiliation lies in the Faculty of Chemistry. Exner has pioneered concepts like the electrochemical-step asymmetry index and free-energy span model, which are critical for screening electrocatalysts. His research group, 'Theoretical Inorganic Chemistry,' actively explores mechanisms behind oxygen and chlorine evolution reactions, emphasizing selectivity control and reaction pathway complexity. Exner received the Gottschalk-Diederich-Baedeker-Preis (2024) for advancing the energy transition through foundational electrocatalysis research. He leads Aktuelles Projekt funded by third-party grants and collaborates with facilities like the Analytics Core Facility Essen (ACE) and Imaging Center Campus Essen (ICCE). His advisory role focuses on guiding theoretical and computational approaches in electrochemistry, and he has established a reputation for interdisciplinary research connecting computational chemistry with practical energy solutions.
Professor Thomas Bein is affiliated with the Department of Chemistry at Ludwig-Maximilians-Universität München (LMU) , where he leads the Functional Nanosystems research group. His work focuses on synthesizing and characterizing nanostructured materials with applications in energy, catalysis, and biomedical delivery. Mesoporous nanoparticles for drug delivery Semiconductor nano-morphologies for photovoltaics Photoelectrochemical water splitting Metal-organic frameworks (MOFs) Electroactive networks His research emphasizes atomic-scale control of material architectures using self-assembly, hydrogen bonding, and covalent interactions, enabling precise tuning of electronic, optical, and catalytic properties. A review of his recent publications reveals cutting-edge investigations into covalent organic frameworks (COFs), perovskite-inspired solar materials, and functional nanoparticle systems. Key trends include optimizing energy conversion efficiency, enhancing stability in optoelectronic devices, and exploring bio-compatible nanocarriers for targeted therapies. Professor Bein’s group actively contributes to interdisciplinary projects at the intersection of chemistry, physics, and biomedical engineering, with ongoing collaborations in solar energy, sustainable materials, and nanomedicine.
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.
Jonas Fischer is the head of the Explainable Machine Learning group at the Max Planck Institute for Informatics, Department of Computer Vision and Machine Learning. His research focuses on interpreting complex machine learning models, particularly in genomics and healthcare, aiming to enhance robustness and alignment with human decision-making. Prior to his role at MPI, he was a postdoctoral fellow at Harvard University's Department of Biostatistics, where he worked on interpretable models for gene regulatory systems in cancer. Education: PhD in Computer Science from Saarland University (2022), with a thesis titled More than the sum of its parts , exploring the intersection of pattern mining and deep learning. He has contributed to advancing methods in neural network pruning, federated learning, and low-dimensional embeddings (e.g., dtSNE, Mercat). His work bridges computational biology, data mining, and machine learning, with applications in DNA methylation analysis, graph-based differential networks, and biomedical informatics. Key research areas include: (1) Explainable AI and neural network interpretability, (2) Biomedical applications of machine learning (e.g., gene regulatory networks, cancer genomics), (3) Low-dimensional embeddings and visualization techniques, (4) Federated learning for privacy-preserving collaborative models, and (5) Pattern mining for error analysis in NLP and classification tasks. Publications span top venues like NeurIPS, ICLR, Bioinformatics, and Genome Biology. His group develops tools such as BONOBO for omics data integration and node2vec2rank for scalable graph analysis. He actively collaborates with biomedical researchers to address challenges in data-driven healthcare and precision medicine.
Andrea Tagliasacchi is an Associate Professor in the School of Computing Science at Simon Fraser University (SFU), where he holds the Visual Computing Research Chair. He is also a part-time (20%) Staff Research Scientist at Google DeepMind in Toronto and holds an associate professor (status only) appointment in the Department of Computer Science at the University of Toronto. Education: PhD in Computing Science – Simon Fraser University (NSERC Alexander Graham Bell Fellow) Postdoctoral Research – École Polytechnique Fédérale de Lausanne (EPFL) MSc in Computer Science – Politecnico di Milano (Gold Medalist) His research lies at the intersection of computer vision, computer graphics, and machine learning, with a focus on 3D visual perception. Key areas include neural radiance fields (NeRF), 3D Gaussian splatting, inverse rendering, and geometric deep learning, with applications in robotics, augmented reality, and autonomous systems. His work emphasizes robust and efficient scene understanding and reconstruction from visual data. His recent publications, appearing in top venues like CVPR, SIGGRAPH, NeurIPS, and ECCV, demonstrate a strong emphasis on neural fields, 3D reconstruction, and generative modeling. Trends include improving rendering efficiency, enhancing robustness to noise and distractors, and enabling controllable and 3D-aware generation. His group has made significant contributions to Gaussian splatting, NeRF optimization, and diffusion-based 3D/4D synthesis. Scientific Awards: 2024 CVPR Best Paper Award (Honorable Mention) 2020 CVPR Best Student Paper Award 2015 SGP Best Paper Award NSERC Alexander Graham Bell Canada Graduate Scholarship MITACS Best Paper Award (SIGGRAPH Asia 2009) NSF Best Poster Award (SGP 2012) He has advised numerous PhD and MSc students, many of whom are now researchers at leading institutions and companies. His research has been supported through collaborations with Google, Intel, and academic partners. He serves the community as a Senior Area Chair for CVPR 2025, Associate Editor for IEEE TPAMI (2024–2026), Guest Editor for IEEE TPAMI on 3D GenAI, and Program Chair for 3DV 2024. He leads a vibrant research lab at SFU focused on pushing the boundaries of 3D scene understanding with machine learning.
Dr. Moran Lazar is a Senior Lecturer at the Coller School of Management, Tel Aviv University, specializing in the early foundations of entrepreneurship and innovation with emphasis on new venture team formation, ideation processes, and organizational innovation leadership. Her educational background includes: PhD in behavioral science and management from the Technion - Israel Institute of Technology Research fellow at the Robert H. Smith School of Business, University of Maryland Research fellow at INSEAD Dr. Lazar integrates organizational behavior and strategy perspectives to investigate entrepreneurship micro-foundations, utilizing diverse methodologies including entrepreneurship competitions, hackathons, accelerators, educational programs, and crowdfunding platforms. Her work examines how individuals and teams generate, evaluate, and develop entrepreneurial ideas through behavioral lenses. Her publication trends reveal consistent contributions to top management journals focusing on team dynamics in nascent ventures, with recent works analyzing attachment theory in idea evaluation, relationship-business balance in team composition, and comprehensive frameworks for entrepreneurial team formation across multiple contexts including accelerators and international delegations. Dr. Lazar actively consults for global companies and facilitates innovation processes for international delegations from Europe, the United States, East Asia, and the United Arab Emirates, while sharing insights through her TEDx talk on entrepreneurial team formation.
Prof. Laura Leal-Taixé is a Professor at the Technical University of Munich (TUM) in the Department of Informatics, leading the Dynamic Vision and Learning group. She holds the Rudolf Mößbauer Tenure Track Assistant Professorship, promoted to W3 Associate Professorship in 2022. Her research focuses on computer vision and machine learning, particularly video analysis, multi-object tracking, and autonomous driving applications. Education: B.Sc./M.Sc. in Telecommunications Engineering (Technical University of Catalonia, UPC) Ph.D. in Information Processing (Leibniz University of Hannover, Germany) Postdoctoral Research at ETH Zürich (Switzerland) and TUM Research Interests: Laura’s work addresses challenges in video analysis, including motion analysis, semantic segmentation, and integrating social dynamics into urban traffic modeling. Her project socialMaps , funded by the Sofja Kovalevskaja Award, explores decoupling vehicle and pedestrian traffic using dynamic maps. Her research combines optimization techniques, deep learning, and sensor data for real-world applications like autonomous systems. Recent Trends: Her publications highlight advancements in multi-object tracking, 3D LiDAR segmentation, and trajectory forecasting, emphasizing neural networks and geometric approaches. Collaborations with industry and academia underscore her work’s practical impact. Awards: 2017 Sofja Kovalevskaja Award (€1.65M, Humboldt Foundation) 2017 DAAD Australia-German Joint Research Grant Travel grants from Women in CV, CVPR Doctoral Consortium, and Vodafone Foundation Labs & Projects: Leads the Dynamic Vision and Learning group at TUM, focusing on vision-based AI for autonomous systems and environmental monitoring. Active in developing datasets like DynamicEarthNet for semantic change analysis.
Prof. Dr. Jörg E. Drewes is a Full Professor and Chair at the Research Institute for Urban Water Management, Technical University of Munich (TUM), Germany. He also serves as Academic Program Director for Environmental Engineering at TUM and is a co-founder of Waterloop Solutions GmbH. His work spans advanced water treatment technologies, wastewater reuse, and environmental health surveillance. Affiliations : TUM, Colorado School of Mines, King Abdullah University of Science and Technology, UNSW Water Research Centre Research focuses on advanced oxidation processes , membrane fouling mitigation , micropollutant removal , and wastewater epidemiology for public health. His team develops integrated systems for water-energy-food nexus applications and graphene oxide-based treatment solutions. Recent publications address PFAS remediation , UVC-LED pre-treatment for biofouling control, and GIS-based wastewater surveillance models . Awards include the Bayerische Staatsmedaille (2023) and William Dunbar Medal (2022). 2023 : Bayerische Staatsmedaille 2022 : William Dunbar Medal 2018 : IWA Fellow He leads the Nexus@TUM initiative and contributes to EU water resilience strategies. Collaborations include projects in Germany, China, India, and Spain, focusing on climate-resilient water systems and resource recovery .
Prof. Dr. Thomas Brinkhoff is Chair of the Institute Board and Chair of Geoinformatics at Oldenburg University of Applied Sciences. He leads the Institute for Applied Photogrammetry and Geoinformatics (IAPG) and contributes to institutions like the Association for the Promotion of Geoinformatics in Northern Germany (GiN e.V.) and the Oldenburg Research and Development Institute for Computer Science (OFFIS e.V.). Education: Diploma in Computer Science (Informatik), Universität Bremen (1990) Doctorate in Computer Science (Dr. rer. nat.), Ludwig Maximilian University of Munich (1994) Brinkhoff's research spans geodatabase systems, spatiotemporal data processing, geosensor analytics, and location-based services. His work addresses Volunteered Geographic Information (VGI), web-based geospatial visualization, and mobile data integration, with applications in traffic management and forensic science. Recent projects include ProSaDi (Digital Provenance and Collection Research) and contributions to the Laboratory for optical 3D metrology . He has served on program committees for ACM SIGSPATIAL (2002-2019), AGILE conferences (2010-2025), and editorial boards of journals like GeoInformatica and TGIS. Notable Lectures: 2024: Forensic applications of tachograph data 2023: Geoinformatics in homicide investigations 2022: Spatiotemporal analysis for sustainability projects 2015: Open geodata standards at FOSSGIS 2014: Mobile sensor data processing
PD Dr. Christian Zillinger is a researcher at the Karlsruhe Institute of Technology (KIT), specifically within the Department of Mathematics. He leads the Junior Research Group "Stability and Instability in Fluids and Materials" (AP6) as part of the CRC 1173. His office is located at Kollegiengebäude Mathematik (20.30), room 2.024 in Karlsruhe, Germany. Dr. Zillinger obtained his PhD under the supervision of Herbert Koch at the University of Bonn. Following his doctorate, he served as an assistant professor (NTT) at the University of Southern California and was a postdoctoral fellow at BCAM (Basque Center for Applied Mathematics). He recently completed his habilitation thesis titled "On Mixing and Resonances in Fluid Systems" at KIT in 2023. Dr. Zillinger's research focuses on partial differential equations motivated by physical problems, particularly in fluid dynamics and material sciences. His work encompasses several key areas: Mixing as a (de)stabilizing mechanism in fluids and inviscid damping Cascades of resonances and instabilities in fluids and plasmas Convex integration and microstructures in materials, including rigidity and flexibility phenomena Magnetic fluids and magnetohydrodynamics Partial dissipation in the Boussinesq equations His recent publications demonstrate a strong focus on stability and instability phenomena in fluid systems, with particular attention to mathematical analysis of PDEs governing fluid behavior. He has made significant contributions to understanding echo chains, resonance phenomena, and damping mechanisms in various fluid models. His work bridges theoretical mathematics with applications in physics and materials science, often employing advanced analytical techniques to address challenging problems in nonlinear PDEs. Dr. Zillinger actively teaches courses at KIT, including "Klassische Methoden für partielle Differentialgleichungen" (Classical Methods for Partial Differential Equations), "Introduction to convex integration," "Introduction to Kinetic Equations," and seminars on microstructure in materials and fluid dynamics. He leads the Junior Research Group "Stability and Instability in Fluids and Materials" which is part of the Collaborative Research Centre (CRC) 1173 at KIT, focusing on wave phenomena. This research group investigates mathematical aspects of stability and instability in physical systems, with applications to fluid dynamics and material science.
Hans Beck serves as Professor of Greek History at the University of Münster (Westfälische Wilhelms-Universität) since 2018, with an additional appointment as Adjunct Professor in the Faculty of Arts at McGill University. His academic career includes previous positions as Professor of Ancient History and Director of Classical Studies at McGill University (2005-2018), Heisenberg Fellow at Goethe-Universität Frankfurt (2004-2005), and Research Assistant at the University of Cologne (1997-2004). Beck earned his academic training through doctoral studies at the Universities of Erlangen, Canterbury, and Cambridge (1989-1996), followed by a fellowship at the Center for Hellenic Studies in Washington, DC (2001-2002). His educational background reflects a strong international foundation in classical studies. His research spans multiple interconnected fields within ancient history, with particular emphasis on the history and culture of ancient Greece, historical geography of Greece, environmental studies of the ancient Greek world, political culture of the Roman Republic, and ancient historiography. Beck's work consistently explores themes of localism, federalism, and political structures across ancient societies, with notable contributions to understanding Greek city-states, regional identities, and comparative political systems. His approach often bridges geographical, historical, and cultural perspectives to examine how ancient communities organized themselves politically and maintained regional identities within larger frameworks. Analyzing his recent publications reveals a sustained focus on local political structures within broader contexts, particularly examining how Greek city-states maintained autonomy while participating in federal leagues. His work increasingly incorporates comparative approaches, connecting Greek political structures with those of Rome and even ancient China, reflecting his editorial work on cross-cultural studies. Beck demonstrates particular expertise in analyzing how physical landscapes shaped political organization and how religious practices reinforced regional identities. Fellow of the Royal Society of Canada (2018) Anneliese Maier Research Award from Alexander von Humboldt Foundation (2014) Heisenberg Fellowship from Deutsche Forschungsgemeinschaft (2004) Doctoral scholarship from German Academic Exchange Service (1995) Doctoral scholarship from Hanns Seidel Foundation (1994) Beck has supervised numerous doctoral students including Jordan Christopher (2022), Chandra Giroux (2021), Wentian Fu (2020), Rebecca Robinson (2017), Alex McAuley (2015), and François Gauthier (2015), covering diverse topics from ancient Qin and Macedon to cult practices in ancient empires. His academic leadership extends to directing research projects B3-49 'Belonging in/to Lakonia' and B3-40 'Localism and Religion in Ancient Greece' within the Excellence Cluster focusing on 'Religious Diversity and Legal-Political Unity.' As head of the project 'Belonging in/to Lakonia' and 'Localism and Religion in Ancient Greece,' Beck leads interdisciplinary research teams examining archaeological and historical evidence from the Sanctuary of Apollo at Amyklai and its surroundings. His work integrates textual analysis with material culture studies, creating comprehensive approaches to understanding ancient regional identities and religious practices. Beck's leadership in these projects demonstrates his commitment to bridging traditional disciplinary boundaries in classical studies.
Prof. Dr. Claudia Peus is a full Professor of Research and Science Management at the Technical University of Munich (TUM) School of Management , serving since May 2011. She holds executive roles as Founding Director of the TUM Institute for LifeLong Learning (TUM IL3) since December 2019 and Executive Vice President for Talent Management and Diversity since October 2017. Her career spans visiting positions at MIT's Sloan School of Management and Harvard University, alongside her habilitation (2011) and PhD (2005) from LMU Munich. Current affiliations: TUM School of Management, TUM IL3, RWI – Leibniz Institute for Economic Research Research focuses: Leadership development in the digital age, diversity in organizations, ethical leadership, and research organization management Recent research trends analyze digital leadership dynamics, gender-decoded recruitment practices, robotic leadership interfaces, and neurophysiological mechanisms in leadership behavior. Her 2025 work on moral careers and 2024 resource-based absorption theory highlight evolving themes in organizational psychology. Scientific honors include: Highly Cited Research Award, Leadership Quarterly (2016) Emerald Citations of Excellence (2016) Best Teaching Award, TUM School of Management (2014) Academy of Management Symposium Award (2010) Bayerische Landesbank Wissenschaftspreis (2006) Prof. Peus advises organizations on diversity and talent management. She was recognized as one of Germany's Most Inspiring Women (2020) and leads projects like FührMINT, ForGenderCare, and the TUM Neurophysiological Leadership Lab (NeLeLab).
