Beat Signer is Professor of Computer Science at Vrije Universiteit Brussel (VUB) and Director of the Web & Information System Engineering (WISE) laboratory. His research focuses on cross-media information spaces and architectures (CISA) spanning interactive paper, dynamic data physicalisation, and tangible holograms. His educational background includes a Computer Science degree from ETH Zurich, where he completed his PhD thesis on fundamental concepts for interactive paper and cross-media information spaces in 2005. Key research areas include: Cross-media document formats and resource-selector-link (RSL) hypermedia metamodel Context-sensitive adaptation and cross-media transclusion Multimodal interfaces (Mudra, iGesture) and tangible computing Internet of Things interoperability and semantic middleware Recent publications (2023-2025) reveal strong trends in dynamic data physicalisation hardware, FAIR positioning systems (OpenHPS), end-user IoT development (eSPACE), and next-generation human-information interaction paradigms. His work increasingly integrates Solid protocols for decentralized data and explores thermal dimensions in tangible holograms. As Principal Investigator, he leads multiple EU-funded projects including OpenHPS, TangHo, and eSPACE. His team has developed influential frameworks like MindXpres for cross-media presentations and CMT for context modeling. He supervises 13 doctoral researchers including Dr. Maxim Van de Wynckel and Dr. Audrey Sanctorum, focusing on cross-media applications in education, IoT, and data visualization. His WISE laboratory develops innovative solutions bridging digital and physical information spaces through projects like ArtVis for collaborative data exploration and TangHo for physically augmented virtual objects.
Dr. Michael Tangermann is an Associate Professor at Radboud University and Principal Investigator at the Donders Institute for Brain, Cognition and Behaviour. He leads the Data-Driven NeuroTechnology Lab, focusing on developing machine learning algorithms for neural and behavioral data analysis. His work integrates brain-computer interfaces (BCI), closed-loop neurotechnologies, and deep brain stimulation (DBS) to address clinical and non-clinical challenges. Education: PhD in Computer Science (2007, University of Tübingen) and Diplom in Computer Science (2000, University of Tübingen). Former positions include Head of the Brain State Decoding Lab (University of Freiburg, 2013–2020) and Substitute Professor for Autonomous Intelligent Systems (2019–2020). Research interests span machine learning for time-series analysis, neurotechnological applications (e.g., BCI for communication/rehabilitation, adaptive DBS), and translational neuroscience. His lab collaborates with institutions like the University Medical Center Freiburg and MindAffect. Publications (H-index: 40) emphasize decoding brain states, optimizing BCI paradigms, and developing open-source tools like the Dareplane platform. Teaching includes advanced BCI courses and digital signal processing at the graduate level.
Frederik Görlitz is a researcher specializing in advanced optical microscopy techniques at the University of Freiburg's Institute for Microsystem Technology (IMTEK), part of the Faculty of Engineering. He holds a PhD from Imperial College London and conducted postdoctoral research at UC Berkeley's Advanced Bioimaging Center. His work focuses on super-resolution microscopy (STED, STORM, SIM), light sheet microscopy, and fluorescence lifetime imaging (FLIM), with applications in biomedical imaging and microscopy instrumentation development. Education: BSc in Physics, Heidelberg University (GER) PhD in Biophotonics, Imperial College London (UK) Research Interests: Development of modular, cost-effective microscopy platforms Optimization of lattice light sheets and super-resolution techniques Integration of machine learning for automated microscopy workflows Biomedical applications in kidney cell signaling and drug receptor analysis Recent Research Trends: His work emphasizes open-source microscopy solutions (e.g., openFrame platform) and high-throughput imaging tools for biological studies. Recent articles highlight advancements in optical autofocus systems, FRET-based signaling visualization, and dSTORM applications in glomerular disease analysis. Labs/Teams: Part of the Bio- und Nanophotonik group led by Prof. Alexander Rohrbach at IMTEK, collaborating with FAIM (Freiburg Center for Data Driven Modelling and Simulation) on interdisciplinary projects.
Adam Chlipala is the Arthur J. Conner (1888) Professor of Computer Science at the Massachusetts Institute of Technology (MIT), where he is a faculty member in the Department of Electrical Engineering and Computer Science (EECS), the Computer Science and Artificial Intelligence Laboratory (CSAIL), and leads the Programming Languages & Verification Group. He has been a faculty member at MIT since 2011, following a postdoctoral position at Harvard University. PhD in Computer Science, UC Berkeley (2007) BS in Computer Science, Carnegie Mellon University (2003) His research lies at the intersection of programming languages and formal methods, with a strong emphasis on using the Coq proof assistant to build verified compilers, cryptographic systems, and hardware-software stacks. His work spans from high-level language design to gate-level hardware verification, aiming for end-to-end correctness proofs. Recent efforts focus on high-performance parallel computing systems with full formal assurance. The 15 most recent publications highlight a consistent trend in verified compilation, cryptographic security, hardware verification, and tensor/ML program optimization. His work increasingly integrates software and hardware verification, emphasizing modular, extensible frameworks and end-to-end correctness. Key themes include side-channel resistance, automated proof techniques, and practical deployment of formally verified systems. Advisory Board Member, BlueRock Systems (formerly BedRock Systems) Member, DARPA Information Science and Technology (ISAT) Study Group (2018–2022) Advisory Board Member, SiFive Former Advisor, krypt.co (acquired by Akamai) Chlipala has advised numerous PhD and Master’s students and regularly teaches core MIT courses such as 6.009 (Fundamentals of Programming), 6.042 (Mathematics for Computer Science), and 6.822/6.5120 (Formal Reasoning About Programs). He is the author of the widely used textbook Certified Programming with Dependent Types and co-developer of the FRAP (Formal Reasoning About Programs) educational materials. He is also the founder of Nectry, a startup based on Ur/Web and UPO, aiming to democratize enterprise application development through AI-assisted, type-safe programming. His research group develops tools and frameworks for modular verification, verified compilation, and formal analysis of complex digital systems. The work is deeply collaborative, involving students, industry partners, and open-source contributions via GitHub. Projects like Fiat Cryptography have been deployed in major web browsers, demonstrating real-world impact.
Fabio A. Cruz Sanchez serves as a Lecturer at the School of Systems and Innovation Engineering and a researcher at the ERPI Laboratory, University of Lorraine. His expertise lies in distributed recycling of plastics for 3D printing, circular economy applications in additive manufacturing, and development of open hardware platforms, with active contributions to innovation spaces like Fablabs and Third Places. His academic credentials include a Mechanical Engineering degree from Universidad Nacional de Colombia, a Master 2 in Innovation Management, and a Doctorate in Industrial Engineering, all from the University of Lorraine. Dr. Cruz's research spans Circular Economy, Additive Manufacturing, and Plastic Recycling, investigating technical-social dimensions of distributed recycling systems. He develops multi-scale evaluation frameworks for circular initiatives while examining open hardware integration and community-driven innovation in Fablabs. Analysis of his 2021-2024 publications reveals consistent focus on polymer recycling for additive manufacturing, including material extrusion techniques for HDPE/PET blends, life cycle assessments of filament production, and vibration damping optimization in printed structures. His work bridges engineering with socio-technical analysis of social innovation labs and open innovation ecosystems. He coordinates the ERASMUS+ project "TechTraPlastiCE" strengthening circular economy value chains for plastics in Latin America, and actively participates in the "Green Fablab" initiative connected to Nancy's territorial dynamics through the Lorraine Fab Living Lab platform.
Thomas P. Kersten is a Professor at HafenCity University Hamburg within the School of Geodesy and Geoinformatics , leading the Photogrammetry & Laser Scanning laboratory. His work bridges geomatics , 3D imaging , and cultural heritage preservation through cutting-edge UAV photogrammetry , terrestrial laser scanning , and virtual reality applications. Research interests focus on: Accuracy validation of photogrammetric and LiDAR systems Low-cost 3D sensor development (e.g., Raspberry Pi-based systems) Virtual Reality for cultural heritage sites (e.g., Al Zubarah Fortress, Michaelsen House) Historical building documentation using 4D modeling Mobile mapping for archaeological and urban contexts Article trends reveal expertise in UAV-based cadastral surveying , smartphone photogrammetry validation, and multi-sensor 3D reconstruction of archaeological and architectural sites. He leads fieldwork in Portugal, Qatar, and Germany while fostering academic collaboration through conference editorship (DGPF, ISPRS workshops).
Dominique Devriese is an Associate Professor at the Department of Computer Science , Faculty of Engineering Science , KU Leuven . They serve as a promotor for multiple research projects focused on type theory, formal verification, and secure software systems. Faculty: Engineering Science Department: Computer Science Academic Rank: Associate Professor Their research explores multimodal dependent type theory , parametricity , logical frameworks like Agda, and secure compilation principles. Projects include formalizing RISC-V security guarantees, developing BiSikkel for multimode logic, and advancing substitution algorithms for type systems. Recent work demonstrates trends in formal methods , programming language theory , and hardware-supported security , with a strong emphasis on mathematical foundations and tool implementation. PhD Student Supervision: Joris Ceulemans Collaborations: Andreas Nuyts, Loes Deferme Active in academic governance, Dominique is a member of the Council of the Faculty of Engineering Science and POC Computerwetenschappen.
Vikram Adve is the Donald B. Gillies Professor of Computer Science at the University of Illinois at Urbana-Champaign, with appointments in both the Computer Science Department and the Center for Digital Agriculture. He co-founded and co-leads the Center for Digital Agriculture and serves as the director of AIFARMS, a $20M National Artificial Intelligence Research Institute funded by USDA NIFA and NSF. Adve has been a professor at UIUC since August 2011 and previously served as Interim Head of the Computer Science Department from 2017 to 2019. Adve received his Ph.D. in Computer Science from the University of Wisconsin-Madison in 1993. His academic journey has been marked by significant contributions to compiler infrastructure and computer systems research, culminating in his current distinguished professorship at one of the world's leading computer science departments. Adve's research spans multiple cutting-edge domains in computer systems. His work on the LLVM Compiler Infrastructure has revolutionized how software is compiled and optimized across diverse hardware platforms. Currently, his research focuses on three primary thrusts: Digital Agriculture and AI : Through the Center for Digital Agriculture and AIFARMS Institute, he's developing AI solutions for agricultural challenges, including the CropWizard system for generative AI in farming Edge Computing : His HPVM, ApproxHPVM, and ApproxTuner projects address the programming challenges of heterogeneous computing at the network edge Compiler Innovation : His Hydride and MISAAL projects use program synthesis to automatically build compilers for complex hardware architectures His work bridges theoretical compiler research with practical applications in agriculture, autonomous systems, and distributed computing. Adve's publication record demonstrates a consistent trajectory from foundational compiler research to applied AI systems. Early work focused on memory safety (SAFECode), deterministic parallel programming (DPJ), and the LLVM infrastructure. More recently, his publications reflect a strategic pivot toward agricultural AI and edge computing, with significant contributions to generative AI applications, compiler techniques for heterogeneous systems, and multimodal data processing for precision agriculture. His work maintains strong theoretical foundations while addressing real-world challenges in resource-constrained environments. Adve's scientific recognition includes numerous prestigious awards: ACM Software System Award (2012) for LLVM ACM Fellowship (2014) NSF CAREER Award (2001) Multiple best paper awards at top conferences including PLDI 2005, SOSP 2007, and CGO 2004 (retrospective) University Scholar designation at UIUC (2015) Donald B. Gillies Professorship (2018) Distinguished Alumnus Award from IIT Bombay (2023) As an advisor, Adve has mentored numerous successful students, including Chris Lattner (co-creator of LLVM), Robert Bocchino (ACM SIGPLAN Outstanding Dissertation Award winner), and John Criswell (ACM Doctoral Dissertation Award Honorable Mention). His research group has secured significant funding from diverse sources including USDA NIFA, NSF, Intel Corporation, Amazon-Illinois AICE Center, and the state of Illinois through the Discovery Partners Institute. Current projects include the $20M AIFARMS institute and multiple edge computing initiatives focused on agricultural robotics and distributed AR/VR systems. Adve leads the Programming Languages, Systems, and Networking research group at UIUC, which maintains strong connections with industry partners. His group's work on LLVM has had widespread industry impact, with applications in Apple's iOS ecosystem, Android, NVIDIA GPUs, and numerous other commercial products. The group's current focus on agricultural AI through the Center for Digital Agriculture represents a strategic expansion into domain-specific applications of systems research.
PerMagnus Lindborg is a composer, sound artist, and researcher in sound perception with over 150 scholarly publications, compositions, and media artworks. Currently serving as Associate Professor at City University of Hong Kong's School of Creative Media, he teaches sound, music, research skills, and perception while coordinating research degrees. PhD: KTH Stockholm (2015) DEA: Paris (2003) IRCAM: Paris (1999) BMus: Oslo His research focuses on sound perception , sonification , spatial audio , multi-sensory environments , and data-driven art . He pioneered low-cost spatial audio solutions through the Open Ambisonics Toolkit and explores sensory heritage documentation via soundscapes and smellscape analysis in Hong Kong. Recent publications demonstrate trends in climate data sonification , neural audio processing , and immersive sound design . His work intersects computer music , psychoacoustics , and environmental art . Scientific Awards : Best New Director (World Film Carnival, Cannes Short Film Festival, ISA Awards - 2020) First Prize (Stavanger Symphony Orchestra Prize - 2002) Fellowships: The Arctic Circle (2023), SCM Team Research (2020-25), TBA The Current (2016) As principal investigator for Multi-Modal Hong Kong (GRF 2023-25) and Data Art for Climate Action (2020-23), he supervises PhD students in areas like multi-sensory cultural heritage , deep learning audio processing , and virtual reality sound design . He co-founded the SoundLab and DACA Conference .
Dr. Lewys Jones is an Associate Professor in the Department of Physics at Trinity College Dublin . His research focuses on advancing Scanning Transmission Electron Microscopy (STEM) techniques for atomic-scale materials characterization, particularly in low-dose imaging, detector optimization, and 3D tomography. Key Research Areas: Aberration-Corrected Microscopy, Atomic-Resolution Imaging, Nanomaterials Analysis, and Machine Learning for Image Enhancement Instrumentation Expertise: Detector Calibration, Probe Drift Compensation, Low-Voltage Imaging, and Digital Pulse Read-Out Systems His work has resulted in multiple peer-reviewed publications (2013-2024) with a focus on electron microscopy innovations and nanostructured materials . Notable scientific awards include the Royal Society & SFI University Research Fellowship (2019) and the International Federation of Societies for Microscopy 'Young Scientist Award' (2014). He has contributed to open-access resources and educational tools for STEM data analysis, including the 'Smart Align' software.
Elmar Rueckert is a Professor at the Cyber-Physical-Systems Institute of Montanuniversität Leoben in Austria. He previously held research roles at Graz University of Technology and Technical University of Darmstadt, focusing on robotics and machine learning. PhD in Computer Science (2014), Graz University of Technology Senior Researcher and Research Group Leader, TU Darmstadt (4 years) Assistant position (3 years) at TU Darmstadt Research interests span robotics , deep reinforcement learning , SLAM algorithms , and cyber-physical systems . His work addresses challenges in autonomous navigation, tactile response prediction, and open-source robotics platforms. Recent publications highlight applications of reinforcement learning in mobile robot navigation, SLAM failure analysis in indoor environments, and ROS-based mobile robot development. Key themes include autonomous systems , machine learning robustness , and real-time decision-making .
Prof. Dr. Carsten Trinitis is a full professor at the Chair of Computer Architecture & Parallel Systems within the TUM School of Computation, Information and Technology. Specializing in high-performance computer architecture with a unique focus on spaceflight applications and informatics ethics, he leads the 'Gesellschaft für Informatik und Ethik' (Society for Informatics and Ethics). Ph.D. in Electrical Engineering from TUM (1998) Industry experience before returning to academia Former Assistant Professor in History of Science (2002-2010) at Universität der Bundeswehr München Full Professor of Distributed Computing at University of Bedfordshire (2010-2014) His research spans three major domains: High-Performance Computing: Focused on microprocessor architectures, hardware-oriented optimizations, and co-design approaches. Recent work includes GPU power capping strategies and Data Distribution Service (DDS) middleware enhancements. Space Systems: Pioneering computer architectures for nanosatellites with projects like MOVE-II mission and MicroPython-based satellite control systems. Digital Ethics: Through his 'Gewissensbits' initiative, he explores ethical decision-making frameworks for technology and contributes to the German Informatics Society's ethical guidelines. Key publication trends show interdisciplinary work connecting: HPC systems and edge AI applications FPGA-based verification and RISC-V processors Time series analysis at petascale performance Hardware-software co-design for extreme environments Continued emphasis on ethical computing frameworks Scientific Recognition: TeachInf Award for Outstanding Teaching (2023) Hans Meuer Award for Best Paper (2020) ZARM Master Thesis Awards (2016, 2017) Prof. Trinitis leads multiple research projects including: SEANERGYS (EuroHPC) - Energy-efficient computing systems PlasmaPEPS - Plasma physics simulation environments OpenCUBE - Open computing frameworks for space MUNIQC-ATOMS - Quantum computing integration
Lorenzo Teppati Lose' is a Fixed-term Researcher at the Polytechnic University of Turin , affiliated with the Department of Architecture and Design (DAD) . He specializes in Geomatics within the domain of Civil Engineering and Architecture (CEAR-04/A - Scientific Disciplinary Sector). Research Interests : 360° cameras, 3D modeling, Digital cultural heritage, Emergency mapping, Geospatial data, Laser scanner, Photogrammetry, SLAM-based modeling, UAV photogrammetry ERC Skills : PE8_3 (Civil engineering, architecture), SH5_12 (Cultural digitization), PE6_8 (Computer graphics), PE10_14 (Remote sensing), PE2_17 (Metrology) His research focuses on photogrammetry and SLAM systems for cultural heritage documentation , with a strong emphasis on UAV technology , direct georeferencing , and 3D modeling . He has developed methodologies for metric surveys using 360° images and cloud platforms , and tested LiDAR sensors for heritage digitization . The trends in his 15 most recent articles highlight expertise in SLAM validation , UAV photogrammetry , HBIM (Historical BIM), and low-cost 3D tools for heritage documentation . His work bridges terrestrial and aerial surveying , with applications in underwater photogrammetry (POSER platform) and emergency mapping (e.g., flood analysis in Limone Piemonte). Scientific Awards : Quality of research activity (2019, 2018) - Doctoral School, Polytechnic University of Turin Best Poster Award SIFET2017 (2017) - Italian Society of Photogrammetry and Topography He serves as a Course Lecturer and Collaborator for modules on Geomatics , Point Clouds , and HBIM in degree programs related to Architecture for Sustainability and Heritage Conservation . His leadership in commercial research projects includes 3D metric surveys of cultural sites in Assisi and the development of a white paper on digital surveying for heritage protection .
Dr. Alexander Heinlein is an Assistant Professor in the Numerical Analysis group at the Delft Institute of Applied Mathematics (DIAM), Faculty of Electrical Engineering, Mathematics & Computer Science (EEMCS), Delft University of Technology (TU Delft). His work bridges scientific computing and machine learning through scientific machine learning (SciML) , focusing on domain decomposition methods and multiscale approaches for solving complex partial differential equations on modern hardware like GPUs. Research interests include: Developing high-performance computing algorithms for nonlinear PDEs with applications in fluid-structure interaction and photonic crystals Advancing physics-aware machine learning techniques for groundwater heat transport and post-burn contraction prediction Creating parallel preconditioners like FROSch for challenging problems in computational mechanics Building hybrid numerical-ML frameworks with domain decomposition for multi-physics applications His recent publications highlight a 128-235x speedup in biomedical simulations through deep operator networks , and keynote presentations on geometric challenges in machine learning-based surrogate models at international conferences like CASML 2024. Scientific awards include: 2025 NWO Open Technology Programme grant for the RAPID-Wind project on offshore wind turbine foundations Students and collaborations involve: Yuhuang Meng (PhD candidate, 2024) Jing Zhao (co-supervisor) Prof. Jun Zou (Chinese University of Hong Kong collaboration, 2024) He leads software development for COMSOL and Trilinos extensions while maintaining open-source reproducibility standards.
Dr. Sam Bizley is a researcher affiliated with the University of Reading, known for contributions to biomedical engineering, microbiology, and pharmacology. Their work focuses on innovative drug delivery systems, low-cost diagnostic tools, and polymer science applications. Key research areas include transdermal drug delivery in veterinary contexts , 3D-printed microfluidic devices for antibiotic susceptibility testing , and hydrogen-bonded multilayer coatings for biomedical use . These studies often integrate interdisciplinary approaches. Recent publications highlight collaborations in developing portable diagnostic equipment (e.g., MicroMI ) and advancing point-of-care testing for mastitis. Their work bridges materials science, microbiology, and practical clinical solutions.
