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Christian TheobaltView profile

Professor

• Computer Science
• Artificial Intelligence
• Computer Vision
• +5 more

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

Michael CarbinView profile

Assistant Professor

• Programming Systems
• Approximate Computing
• Probabilistic Programming
• +4 more

Michael Carbin is the Jamieson Career Development Assistant Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT) and leads the MIT Programming Systems Group. His research focuses on programming systems that address system uncertainty to enhance performance, energy efficiency, and resilience, particularly in environments involving neural networks , approximate computing , and unreliable hardware . His work spans probabilistic programming , quantum computing , and machine learning systems . Articles highlight contributions in pruning neural networks , quantum data structures , and compiler optimization , reflecting trends in deep learning , formal verification , and language-driven systems . Scientific Awards : MIT Frank E. Perkins Award (2020) Sloan Research Fellowship (2020) Facebook Research Award (2019) NSF CAREER Award (2018) Best Paper Awards at OOPSLA (2013, 2014) He has advised numerous graduate students and postdocs including Eric Atkinson, Cambridge Yang, and Charles Yuan, and served on program committees for conferences like POPL, OOPSLA, and ICLR. His group collaborates with institutions such as MIT CSAIL and explores applications in quantum algorithms and probabilistic inference .

• Computer Science
• Software Engineering
• Artificial Intelligence
• +5 more

Dongwoo Kim is a researcher affiliated with Hanyang University, ERICA Campus (Department of Electronics and Communication Engineering) and has previously collaborated with institutions like POSTECH , Chungnam National University , and Microsoft . His work spans interdisciplinary domains in Computer Science and Engineering . Hanyang University, ERICA Campus - Department of Electronics and Communication Engineering POSTECH - Power Analog Electronics & Semiconductor Devices Lab Microsoft Chungnam National University Kim's research focuses on formal verification of automotive control software, deep learning applications in environmental monitoring, 3D modeling for indoor positioning, and machine learning for signal processing. His recent publications highlight advancements in graph neural networks (GNNs), including analyzing oversmoothing and gradient dynamics, as well as developing geometric vision-language models with domain-agnostic encoders. His 15 most recent articles (2023-2025) address topics like: Optimizing hybrid electric vehicle engine performance 3D modeling for indoor localization GNN training stability UAV-based environmental monitoring Algorithm difficulty prediction for programming problems Millimeter-wave antenna design Kim collaborates with researchers in software engineering , signal processing , and environmental science domains. His work intersects formal methods , applied machine learning , and embedded systems research.

• Artificial Intelligence
• Human-Computer Interaction
• Computer Vision
• +4 more

Prof. Dr. Julius Schöning is a Professor at the Faculty of Engineering and Computer Science , Osnabrück University of Applied Sciences. His research focuses on Artificial Intelligence , Human-Computer Interaction , and Computer Vision within agricultural contexts. 2019–Present: Professor, Hochschule Osnabrück 2018–2019: System Architect, ZF Friedrichshafen AG 2014–2018: Researcher, University of Osnabrück 2009–2013: Project Lead/System Engineer, CLAAS Harsewinkel Education: M.Sc. in Intelligent Embedded Microsystems (Freiburg), B.Eng. in Mechatronics (DHBW Stuttgart) His research spans smart agriculture , quantum NLP , and explainable AI systems , with recent work on vibrotactile warning systems, AI compliance frameworks, and hybrid dataset applications in farming. Publications emphasize interdisciplinary approaches bridging technology and agricultural practice . Scientific honors include: DAAD Stipendium for conference participation Best Paper Award (2018) IEEE GHTC Student Paper Contest Winner (2016) Sonderpreis für gute Lehre (2017) Finalist/Falling Walls Lab (2015)

• Computer Science
• Artificial Intelligence
• Machine Learning
• +12 more

Hao Liu is a researcher affiliated with institutions like Chinese Academy of Sciences , Beihang University , and Stanford University . His work spans Computer Science , Artificial Intelligence , and Robotics . Key affiliations: National Space Science Center (Beijing), School of Astronautics (Beihang), Key Laboratory of Pervasive Computing (Tsinghua) Research interests include Machine Learning , Image Processing , Graph Neural Networks , and Wireless Communication Optimization His recent publications focus on: Advanced control systems for fuzzy models Medical imaging via hyperspectral analysis Transformer-based approaches in NLP and vision Quantum-safe and edge computing protocols

• Technology Assessment
• Ethics of Technology
• Philosophy of Technology
• +5 more

Armin Grunwald serves as Head of the Institute for Technology Assessment and Systems Analysis (ITAS) at Karlsruhe Institute of Technology (KIT) and Head of the Office of Technology Assessment at the German Bundestag (TAB). Since 2007, he has held the Chair of Philosophy and Ethics of Technology at KIT's Institute of Philosophy, building on his previous professorship at the University of Freiburg (1999-2007). His leadership positions include membership in the German Ethics Council, the National Advisory Board for Repository Search, and the Science-Policy Advisory Board of ETH Zürich. Grunwald's research focuses on the theory and practice of technology assessment, ethics of technology, sustainability concepts, and digital transformation. His work explores humanity's relationship with technology, particularly examining how digitalization challenges human self-understanding and autonomy. He investigates philosophical questions surrounding artificial intelligence, anthropocentrism in the Anthropocene, and the ethical dimensions of technological progress. His extensive publication record demonstrates consistent scholarly output across multiple disciplines. Recent work shows increasing focus on AI ethics, the philosophical implications of digital transformation, and technology assessment methodologies for addressing grand societal challenges. His publications span philosophical analyses, empirical studies on technology implementation, and policy-relevant assessments for governmental bodies. Grunwald has supervised numerous doctoral students across interdisciplinary fields including energy transition, AI governance, urban sustainability, and technology ethics. His leadership extends to directing major research initiatives through ITAS, which serves as Germany's parliamentary technology assessment body providing scientific advice to the Bundestag on emerging technologies and their societal implications.

Mikel SanzView profile

Researcher

• Quantum Computing
• Quantum Algorithms
• Quantum Technologies
• +5 more

Mikel Sanz is a Ramón y Cajal Researcher and Ikerbasque Fellow at the University of the Basque Country (UPV/EHU) in Bilbao, Spain. His research focuses on quantum computing, quantum algorithms, quantum technologies, and quantum metrology. His research interests include: Quantum Computing and Quantum Algorithms Quantum Metrology and Quantum Sensing Digital-Analog Quantum Computing Quantum Machine Learning Quantum Simulation Quantum Error Correction and Mitigation Dr. Sanz's recent publications demonstrate a strong focus on practical applications of quantum computing across various domains. His work spans quantum hardware design, quantum algorithm development, quantum machine learning applications, and quantum metrology techniques. He has made significant contributions to digital-analog quantum computing approaches, quantum kernel methods, and quantum-enhanced sensing technologies. His scientific awards include being selected as a Ramón y Cajal Researcher, a prestigious research position in Spain for experienced researchers, and an Ikerbasque Fellow, which is awarded by the Basque Foundation for Science to attract top researchers to the Basque Country. Dr. Sanz has collaborated extensively with researchers across multiple institutions, contributing to a wide range of quantum information science projects. His work often bridges theoretical quantum information concepts with practical implementations, particularly in superconducting quantum computing platforms. He is actively involved in advancing quantum technologies through his research group at UPV/EHU, focusing on developing novel quantum algorithms and exploring applications of quantum computing in various scientific and industrial domains.

Tommaso CalarcoView profile

Professor

• Quantum Computing
• Quantum Control
• Quantum Technology
• +3 more

Prof. Dr. Tommaso Calarco is the Director of the Institute of Quantum Control at Forschungszentrum Jülich, a leading research center in Germany. He is a key figure in the European quantum technology landscape, having significantly contributed to the coordination of quantum research and the development of the EU Quantum Flagship initiative. His research is centered on quantum control and the technological realization of quantum computing systems. He explores the manipulation of quantum systems, including atoms and semiconductor-based qubits such as those using NV centers in diamond, with a vision towards building practical and scalable quantum computers. Prof. Calarco emphasizes the critical role of national and international collaboration in advancing quantum technology. He anticipates that error-corrected quantum computers will emerge within the next decade, enabling complex, industry-relevant applications. His work bridges fundamental quantum mechanics with future technological applications. He has been inspired by pioneers like Peter Zoller and values the ability to unite diverse scientific communities. Outside of his scientific endeavors, he maintains a deep connection to music, holding a bachelor's degree in classical music and performing Renaissance madrigals, which he credits with helping him maintain mental well-being.

• Computer Architecture
• Hardware Design
• Signal Processing
• +7 more

Prof. Dr.-Ing. Holger Blume serves as Vice President for Research and Transfer at Leibniz University Hannover while maintaining his academic position as Professor in the Architectures and Systems Section within the Faculty of Electrical Engineering and Computer Science. He holds multiple leadership positions including Chairperson of the Research Commission and Central Ethics Committee, Executive Board member of eNIFE (Leibniz Research Initiative for Neurosciences), and membership in both the Laboratory of Nano and Quantum Engineering and L3S Research Centre. His research interests span computer architecture, hardware design, signal processing, AI accelerators, hearing aid technology, and biomedical engineering. His work bridges theoretical computer science with practical applications in automotive systems, medical devices, and quantum engineering. Professor Blume's research demonstrates strong interdisciplinary connections between electrical engineering, computer science, and biomedical applications, with particular emphasis on hardware-oriented solutions for real-world problems. Analysis of his recent publications (2023-2025) reveals a strong focus on hardware acceleration for AI and signal processing applications, particularly in automotive radar/LiDAR systems and hearing aid technology. His work shows consistent innovation in RISC-V processor design, specialized hardware for mathematical functions, and biomedical applications of engineering principles. The research demonstrates a clear trajectory toward energy-efficient, specialized computing architectures for specific application domains. As Vice President for Research and Transfer, Professor Blume oversees significant research initiatives at Leibniz University Hannover, which hosts multiple Clusters of Excellence including PhoenixD (Photonics, Optics, and Engineering), QuantumFrontiers, and Hearing4all. The university participates in numerous collaborative research centers and junior research groups funded by DFG, BMBF, and EU programs. Professor Blume is actively involved in multiple research facilities including the Laboratory of Nano and Quantum Engineering and the L3S Research Centre. His work connects with Leibniz University's research focuses on optical technologies, quantum optics and gravitational physics, and biomedical research and technology. His leadership positions indicate strong involvement in shaping the research strategy and ethical framework of the university's scientific endeavors.

Ana LucicView profile

Assistant Professor

• Interpretable Machine Learning
• Artificial Intelligence
• Earth System Science
• +3 more

Ana Lucic is an Assistant Professor in Artificial Intelligence at the University of Amsterdam , with a joint appointment between the Institute for Logic, Language and Computation and the Informatics Institute . Her research focuses on interpretable machine learning applications for scientific discovery and societal impact. Formerly at Microsoft Research AI for Science and Partnership on AI PhD in Explainable Machine Learning from University of Amsterdam (2022) BSc/MSc in Mathematics from McMaster University Research Highlights: Develops mechanistic interpretability methods for deep learning architectures. Created Aurora , a foundation model for Earth system forecasting outperforming traditional operational models in air quality prediction and tropical cyclone tracking. Pioneers Clifford-Steerable CNNs for geophysical data analysis. Actively hiring PhD students for AI transparency research . Collaborative Networks: Contributions to ELLIS Summer School and ICML workshops . Collaborates with Microsoft Research AI for Science team on climate-related ML projects. Involved in organizing TerraBytes workshop at ICML 2025. Recent Advancements: Key role in publishing Aurora model in Nature (2025), demonstrating superior performance in Earth system forecasting. Supervises Ege Erdogan , new PhD student focused on mechanistic interpretability. Actively contributes to open-source AI development through GitHub repositories and technical discussions.

• Wireless Sensor Networks
• Low-Power Communication
• Backscatter
• +6 more

Ambuj Varshney is a researcher specializing in low-power wireless communication, visible light networking, and embedded systems. His work explores tunnel diodes for non-contact sensing, backscatter technologies, and edge-based language models. Key contributions include AudioCast for audio-broadcast connectivity, TunnelSense for tunnel diode sensing, and PiXelGen for mixed-reality cameras. Core Research Areas: Wireless Sensor Networks, Backscatter, Tunnel Diodes, IoT, Embedded Systems Recent Trends: Integration of large language models (LLMs) in edge devices, visible light communication, low-power AR networking

Rishabh DabralView profile

Researcher

• 3D Computer Vision
• Computer Graphics
• Multi-Modal Interactions
• +6 more

Rishabh Dabral is a Research Group Leader at the Max Planck Institute for Informatics since August 2024, leading the "3D Visual Intelligence" group. He is also affiliated with the Research Training Group on Neuro-Explicit Models of Language, Vision, and Action at Saarland University. Expertise: 3D computer vision, computer graphics, human-object interaction modeling, and motion synthesis. Leadership: Conducts cutting-edge research on 3D human performance capture and physical plausibility in motion. His research focuses on: 3D human pose estimation under gravity constraints Multi-modal gesture synthesis using neural architectures Quantum auto-encoding for 3D representations Wearable robotics informed by human behavior Temporal dynamics in human-object interaction Recent publications at top venues like SIGGRAPH , CVPR , and ICCV demonstrate his work on: Music-driven motion synthesis Egocentric motion capture systems Reactive two-person interaction models Diffusion-based gesture generation Object-aware motion prediction Wearable robotic limb design

Björn MöllerView profile

Researcher

• Machine Learning
• Computer Vision
• Signal Processing
• +3 more

Björn Möller, a researcher at the Department of Signal Processing and Machine Learning within the Faculty of Electrical Engineering, Information Technology, and Physics at Technical University of Braunschweig, specializes in machine learning and computer vision applications. His academic journey includes a diploma in Business Information Systems from TU Dresden (2012–2019), with a focus on Business Intelligence. Research Interests His work bridges deep learning with practical applications in two distinct domains: Advancing microscopy techniques through low-resolution data-driven super-resolution models Optimizing viticulture operations via object detection and yield prognosis systems His publications demonstrate expertise in algorithm development for both scientific imaging and agricultural technology. Publication Trends Research spans atomic-scale imaging (2024, 2023) and agricultural AI (2019, 2021). Notably, he explores how transformer architectures and super-resolution methods can solve domain-specific challenges in microscopy and vineyard management. Contact Information Email: bjoern.moeller@tu-braunschweig.de Location: Schleinitzstraße 22 (Room 302), Braunschweig Phone: +49 (0) 531 391 - 2446

Fuyuan ZhangView profile

Researcher

• Artificial Intelligence
• Cybersecurity
• Formal Methods
• +7 more

Fuyuan Zhang is a Postdoctoral Researcher at the Max Planck Institute for Software Systems, specializing in advanced software testing methodologies and formal verification techniques. His research focuses on improving the reliability and security of AI systems, quantum computing frameworks, and concurrent systems through innovative testing criteria, adversarial attacks, and compositional reasoning. Key areas of expertise include: Large Language Model (LLM) testing and validation Quantum program analysis and security Adversarial machine learning and neural network robustness Formal verification of concurrent and cyber-physical systems Automated bug detection in complex software systems His work bridges theoretical foundations with practical applications, addressing critical challenges in AI safety, quantum software reliability, and system-wide security certification.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +7 more

Sio Kei Im is an active researcher with a focus on computer science, machine learning, and human-computer interaction. His recent work spans multiple domains including image processing, quantum computing, and virtual reality. Publications address advanced data augmentation (LogicMix), multi-modal quantum watermarking (MMQW), and efficient neural decoding algorithms (TRHyper). Research interests include time series optimization, dialogue summarization, and haptics in VR environments. Collaborations with experts in linguistics, electrical engineering, and software development indicate interdisciplinary expertise. Key contributions involve adaptive algorithms for AI model protection, speaker recognition systems, and real-time 3D rendering techniques.