Find Academic Supervisors

Jürgen SingerView profile

Professor

• Visual Computing
• Computer Graphics
• Computer Vision
• +7 more

Jürgen Singer is a Professor of Visual Computing at Harz University of Applied Sciences, coordinating the Media Informatics degree program. His academic career spans over two decades, including prior roles as Professor of Computer Graphics, Animation, and Virtual Reality (2006-2015) and senior research positions at institutions like MIT and the University of Texas. Education: PhD in Mathematics (1995), University of Houston Diploma in Theoretical Physics (1988), Friedrich-Alexander University Erlangen-Nuremberg Research Interests focus on visual computing, encompassing image processing, computer graphics, virtual reality, and machine learning. He explores applications in game development, 3D rendering, and web technologies, particularly emphasizing procedural generation, AI integration, and real-time visualization. Teaching Contributions include core courses in Java programming, software tools (Git, Docker, Jenkins), mathematics for computer graphics, and advanced topics like concurrency and distributed programming. His supervised theses reflect ongoing innovation in DevOps, metaverse content creation, and accessibility in UI design. Scientific Awards are not explicitly mentioned in the provided text. Labs & Teams: While specific lab details aren't provided, his work with student theses indicates collaboration in media informatics, game development, and visualization research groups.

Katherine ParsonsView profile

Assistant Professor

• Digital Art
• Virtual Reality
• Augmented Reality
• +12 more

Katherine Parsons is an Assistant Professor of Digital Art at Seaver College, Pepperdine University, and an instructor at Art Center College of Design. She holds an M.F.A. in Media Arts from UCLA and is actively engaged in both academic and artistic practices centered on digital media, virtual reality, and new media art. She is the co-founder of FLOAT, a VR/AR art studio, and founder of FEMMEBIT, a platform celebrating women and gender-diverse artists in video and new media. M.F.A., UCLA Design Media Arts (2015) M.A., CSU-Northridge, Digital Art and Video (2013) B.F.A., Montana State University, Fine Arts/Graphic Design (2005) Her research and artistic practice focus on human connection, grief, environmental systems, and the integration of technology in expressive forms. She explores these themes through immersive media, live cinema, and interactive installations. Her work bridges art, technology, and emotional experience, often involving community engagement and feminist perspectives. Her recent creative output includes VR projects such as Screensavers VR , Irrational Exuberance , and 3VR: Liminal Realities , exhibited at venues like SFMOMA, SXSW, and Slamdance. These works reflect a strong trend in immersive storytelling, digital preservation, and the emotional potential of virtual environments. She frequently collaborates with musicians and directors, including Mark Pellington and Silversun Pickups. 160/90 Scholarship, UCLA Research Apprenticeship in Digital Humanities, UCLA and the Hammer CFPRT Scholar, UCLA Library Special Collections Deans Council, UCLA School of Arts and Architecture Shed Scholarship, CSU-Northridge ADDY Awards: One Gold, two Silver, four Bronze Katherine Parsons has mentored students through university courses and workshops at SXSW and Pepperdine. She has curated exhibitions such as Pepperdine Artist Talks and FEMMEBIT , and has been involved in community-based initiatives like Primal U and Outer Echoes . While specific grant details are not listed, her residencies and project funding suggest ongoing support for her interdisciplinary work. She is actively involved in artist collectives and labs, including VOIDLAB at UCLA, a feminist collective for women and gender-diverse individuals in arts and technology. Her studio practice includes collaborations with FLOAT, FEMMEBIT, and Machine Project, emphasizing experimental media, projection mapping, and community-driven art events.

• Computer Graphics
• Digital Cultural Heritage
• 3D Visualization
• +5 more

Imanol Muñoz Pandiella is a teaching staff member at the Faculty of Informatics of Barcelona (FIB), Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Science (CS). He plays a key role in supervising Final Degree Projects across programs such as Computer Engineering and Data Science and Engineering. University: Universitat Politècnica de Catalunya School: Faculty of Informatics of Barcelona Department: Department of Computer Science Role: Lecturer in Computer Science His research and teaching focus on applied computer science in digital cultural heritage, particularly 3D modeling, visualization, virtual reconstruction, and interactive systems. Projects under his supervision demonstrate a strong emphasis on developing practical tools for heritage preservation, including segmentation, lighting simulation, texture generation, and web-based 3D viewers. The recent publications reflect a consistent trend in leveraging computer graphics and visualization technologies for cultural heritage applications. These works integrate techniques from image processing, rendering, simulation, and human-computer interaction, often targeting open-access, real-world deployment in digital museums and conservation efforts. While no formal scientific awards are listed in the provided content, his sustained mentorship and project supervision indicate a significant academic contribution. He has advised numerous undergraduate students on their final degree projects, contributing to both education and applied research. Martin Vall Oliveira Jeremy Comino Raigon Roc Salvador Andreazini Ramon Ribas Domingo Max Vives Ribera Neus Mayol Alcaraz Javier Castano Mansillas Bernat Borras Civil Roberto Amat Alins Pau Matas Albiol Miriam Mendez Serrano Albert Barreiro Diaz Pau Nunez Amoros He collaborates closely with researchers such as Carlos Andújar Gran, Óscar Argudo Medrano, and Pere Pau Vázquez Alcocer, indicating integration within a specialized research group focused on graphics and heritage visualization. The lab environment appears to emphasize interdisciplinary projects combining computer science with cultural preservation goals.

• Computer Graphics
• Machine Learning
• Data Analysis
• +7 more

Prof. Dr. Volker Ahlers is a Professor in the Department of Computer Science at Hochschule Hannover – University of Applied Sciences and Arts . He serves as the International Coordinator for the department and is a member of the Senate Commission for Research . His academic career spans over two decades, with prior appointments at Goethe University Hospital, WiSenT GmbH, and the University of Potsdam. Education : PhD in Physics (University of Potsdam, 2001), M.Sc. in Physics (Georg August University Göttingen, 1998) Research Interests : Focus on Computer Graphics , Machine Learning , Data Analysis , Information Visualization , and Urban Logistics . His work bridges network security and smart city applications. Grants : Led projects funded by BMBF (EKiKo-KI, GLACIER, USEfUL), BMDV (5GAPS), and DAAD collaborations. Professional Roles : Conference chair (IDAACS 2023, ASIM 2018), reviewer for journals like PLOS ONE and Bioinformatics , and member of accreditation agencies.

Andrei C. JalbaView profile

Assistant Professor

• Computer Graphics
• Visualization
• Visual Analytics
• +6 more

Andrei C. Jalba is an Assistant Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e), specializing in Visualization and Visual Analytics. His research spans computer graphics, geometric processing, and visualization techniques with significant applications in medical imaging, simulation systems, and real-time graphics. Research Expertise Dr. Jalba's research fingerprint reveals strong specialization in curve skeletonization (95%), diffusion tensor analysis, point cloud processing (64%), and graphics hardware acceleration (59%). His work focuses on developing advanced algorithms for skeletonization, regularization techniques, and geometric processing with applications across multiple domains. His research intersects computer vision, medical diagnostics, and computational fluid dynamics, demonstrating practical implementations in MRI data processing, fire safety simulations, and interactive visualization systems. The integration of physics-based approaches with computational techniques represents a significant thread throughout his publication history. Publication Trends Dr. Jalba's recent publications show a clear progression from fundamental geometric algorithms to practical applications in medical imaging and real-time systems. His 2023 work on volumetric light transport demonstrates continued innovation in rendering techniques, while his 2021 eye tracking research shows expansion into AI applications. The consistent theme across his work is the development of efficient computational methods for complex visualization problems. Academic Contributions Teaching: Computer Graphics (since 2012), Seminar Visualization (since 2015), Simulation in Computer Graphics (since 2015) Supervision: 48 research projects across visualization and computer graphics topics Research Output: 68 publications with over 1,100 citations according to Scopus His work contributes to UN Sustainable Development Goals through applications in medical diagnostics, safety engineering, and computational science, though specific goals are not detailed in the available information.

Daniel RuijtersView profile

Professor

• Medical Imaging
• Image-Guided Therapy
• Data-Driven Healthcare
• +3 more

Daniel Ruijters is a part-time Full Professor in the Electronic Systems department at Eindhoven University of Technology (TU/e), specializing in data-driven value-based healthcare for image-guided therapy. His research develops intelligent systems that optimize data utilization in minimally invasive treatments, translating population datasets to individual patient care. He simultaneously serves as a Principal Scientist at Philips Healthcare, where he has worked since 2001, developing clinical prototypes for image-guided interventions. Education Engineering degree from University of Technology Aachen, Germany (2001) Master's research at École Nationale Supérieure des Télécommunications (ENST), ParisTech, France PhD from TU/e and KU Leuven (2010) on multi-modal image fusion Research Focus Ruijters' work integrates medical imaging, deep learning, and computational modeling to advance image-guided interventions. His research spans GPU-accelerated image processing, angiography-based diagnostics, computational fluid dynamics for vascular analysis, and AI-driven detection systems for neurovascular procedures. This includes developing real-time tracking methods and personalized treatment approaches using large-scale clinical datasets. Projects & Initiatives He leads the PERSEUS project (2023-2029) focusing on patient-centered healthcare optimization through data science. His work contributes to UN Sustainable Development Goals through improved medical technology accessibility. Academic Contributions Ruijters teaches courses in DSP fundamentals, medical image analysis, and signal processing. His 90+ publications demonstrate consistent output since 2003, with recent emphasis on deep learning applications in angiography and computational hemodynamics.

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

Jan Lemeire is an active researcher at Vrije Universiteit Brussel (VUB), affiliated with the Department of Electronics and Informatics within the Faculty of Engineering. Based in Brussels, Belgium at Pleinlaan 2, he maintains an active research profile with an h-index of 10 and 581 citations according to Scopus data. His research interests span multiple domains including GPU computing, machine learning, embedded systems, and their applications in diverse fields from biomedical engineering to forensic science. His work demonstrates strong interdisciplinary connections, bridging computer science with practical applications in health technology, crime analysis, and industrial systems. Analysis of his recent publications reveals a consistent focus on computational efficiency, with particular emphasis on GPU acceleration, embedded AI deployment, and machine learning applications. His work shows evolution from hardware-focused research toward more applied domains including healthcare technology and crime pattern analysis. Dr. Lemeire actively participates in multiple research projects including NSIS2: PRISMA network (2024-2029), IOF3016: GEAR (2021-2025), and Tech4Health (2024-2025), demonstrating sustained research funding and collaborative work across disciplines. His academic activities include supervision of graduate students, as evidenced by his role as advisor for the 2017 Master's thesis on GPU-accelerated holography, and regular participation in major conferences including the Conference on Uncertainty in Artificial Intelligence and the International Symposium on Embedded Multicore Systems. Dr. Lemeire maintains an active research laboratory focused on computational methods, with particular strengths in parallel processing techniques and their application to real-world problems across multiple domains including healthcare, industrial systems, and forensic science.

David BlinderView profile

Professor

• Optics
• Signal Processing
• Computer Science
• +7 more

David Blinder is a Professor at the Vrije Universiteit Brussel (VUB) in the Department of Electronics and Informatics (ETRO), where he maintains a dual affiliation with the imec research institute. He concurrently holds a JSPS International Research Fellow position at Chiba University, leveraging over a decade of cross-institutional expertise in optics, signal processing, and computer science to advance computational holography and photonics. His research program centers on signal processing in photonics and holography, with emphasis on numerical diffraction, time-frequency analysis, data compression, and computational imaging. As lead editor of the JPEG Pleno Holography standard, he drives innovation in holographic data representation and transmission. His work integrates optical setups, holographic displays, and high-performance computing to solve complex problems in 3D visualization and inverse methods. Recent publications demonstrate a cohesive trajectory toward efficient computational frameworks for holographic systems, with recurring themes in numerical diffraction algorithms, polygon-based hologram generation, and asymmetric point-spread function optimization. These advances directly enable next-generation holographic displays and computational imaging applications across medical visualization and augmented reality. Blinder's contributions have been recognized through significant honors: Editor's Pick award (October 2024) Editor's Pick award (September 2024) Suzuki-Okada Memorial prize (June 2024) OSA Outstanding Reviewer recognition (2018) He has mentored master's students including A. Ouahabi (2015, Motion Estimation for Dynamic Holography) and F. Suarez Groen (2017, GPU-optimized Computer-Generated Holography). His research is sustained by major grants: FWOAL1100: Advanced dynamic computer-generated holography (2024-2026) FWOAL1101: Computational Incoherent holographic plenoptic camera (2024-2027) FWOTM1099: Chirplet-based diffraction framework (2022-2027) Tech4Health: Future health technologies (2024-2025) As a core member of VUB's ETRO department and imec, Blinder leads interdisciplinary teams in projects like GEAR and Tech4Health, developing holographic visualization systems for medical applications while advancing fundamental optical computing methodologies.

Simon KentView profile

Associate Professor

• Digital Education
• Machine Learning
• Distributed Computing
• +4 more

Dr Simon Kent serves as an Honorary Reader in the Department of Computer Science within Brunel University London's College of Engineering, Design and Physical Sciences, while currently working at the University of Nottingham. Previously, he held the position of Director of Learning and Teaching in Brunel's Computer Science Department, leveraging his dual background in academia and financial services software architecture to bridge industry-academia gaps. His educational qualifications include a PhD in Artificial Intelligence focused on robot path planning and a Postgraduate Certificate in Learning and Teaching Higher Education. Kent is recognized as a Fellow of the Higher Education Academy and maintains membership in the British Computer Society. Research interests span digital education analytics, machine learning, distributed/cloud computing, and software engineering pedagogy. Kent pioneers industry-aligned educational innovations, notably implementing the UK's first large-scale BYOD digital examination system at Brunel and analyzing assessment data to enhance student outcomes. His work consistently applies computational techniques like genetic programming to cross-disciplinary challenges in healthcare, defense, and finance. Publication trends reveal an evolution from foundational AI work in the 1990s (oral cancer diagnosis, missile systems) through distributed computing applications in the 2000s (video rendering, diabetes monitoring) toward contemporary digital education research. Key thematic threads include real-world problem solving, industry collaboration, and translating technical innovation into educational impact. Scientific recognition includes: Fellow of the Higher Education Academy Member of the British Computer Society As an educator, Kent directs the Level 2 Group Project (CS2001) simulating commercial software development environments and mentors across undergraduate/master's programs. He secured significant research funding including a Sucden UK collaboration for distributed order matching systems and Diabetes UK proposals for diabetic teenager monitoring applications, emphasizing practical industry partnerships. Affiliated with Brunel's CIKM and CSSB research groups, Kent continues advancing digital assessment methodologies while exploring IoT applications for home energy optimization through appliance collaboration networks.

ROBERTO PIERDICCAView profile

Researcher

• Geomatics
• Remote Sensing
• Cultural Heritage Documentation
• +5 more

Roberto Pierdicca is a Researcher in Geomatics (scientific sector CEAR-04/A) at the Department of Civil, Building and Architectural Engineering, College of Engineering, Università Politecnica delle Marche (UNIVPM) in Ancona, Italy. His academic career focuses on the intersection of geospatial technologies, artificial intelligence, and cultural heritage documentation, with a strong emphasis on practical applications in environmental monitoring and preservation. Dr. Pierdicca's research interests center around advanced geomatics techniques including LiDAR technology, UAV-based remote sensing, and 3D modeling for cultural heritage preservation and environmental applications. His work demonstrates a strong interdisciplinary approach, bridging geospatial sciences with computer vision, machine learning, and environmental engineering to develop innovative solutions for complex documentation and monitoring challenges. Analysis of his publication record from 2023-2025 reveals a clear research trajectory focused on integrating artificial intelligence with traditional geomatics techniques. His work spans multiple domains including cultural heritage documentation (particularly for sites in Syria, Uzbekistan, and Italy), environmental monitoring (floodplains, vegetation recovery, olive groves), and forestry management. A notable trend is the increasing sophistication of AI applications in his work, moving from basic classification to complex generative models and context-aware systems. Dr. Pierdicca is actively involved in multiple research projects that combine geospatial data acquisition with advanced computational methods. His work frequently appears in interdisciplinary contexts, suggesting strong collaborations across engineering, computer science, and cultural heritage disciplines. The practical applications of his research are evident in numerous case studies addressing real-world challenges in heritage preservation, environmental monitoring, and precision agriculture.

• Image Processing
• Artificial Intelligence
• Synthetic Aperture Radar Imaging
• +5 more

Loïc Denis is a Professor at Université Jean Monnet Saint-Etienne, teaching at TELECOM Saint-Etienne (Graduate School in electrical engineering and computer science) and conducting research at the Laboratoire Hubert Curien, a joint lab between the University and the CNRS. His research focuses on image restoration and reconstruction with applications spanning from microscopy and optical metrology to SAR imaging and astronomy. Denis's research interests center on image processing and artificial intelligence, with particular expertise in Synthetic Aperture Radar (SAR) imaging, exoplanet detection and characterization, digital holography, and Earth observation. His work bridges theoretical developments in image restoration with practical applications in remote sensing, astronomy, and biomedical imaging. He has developed innovative algorithms like PACO for exoplanet detection and MERLIN for SAR despeckling that have significantly advanced these fields. His recent publications demonstrate a strong focus on deep learning approaches for SAR image processing, particularly in multitemporal speckle reduction, polarimetric SAR despeckling, and SAR tomography. His astronomical work centers on high-contrast imaging techniques for exoplanet detection and characterization, with significant contributions to angular and spectral differential imaging. The interdisciplinary nature of his research connects computer vision, signal processing, and domain-specific applications across multiple scientific fields. IEEE GRSS Symposium Prize Paper Award 2021 for 'Exploiting multi-temporal information for improved speckle reduction of Sentinel-1 SAR images by deep learning' IEEE Geoscience and Remote Sensing Society 2016 Transactions Prize Paper Award for 'NL-SAR: A Unified Nonlocal Framework for Resolution-Preserving (Pol)(In)SAR Denoising' Denis has advised numerous PhD students including Emanuele Dalsasso, Olivier Flasseur, and Sylvain Lobry, whose work has received multiple awards. He has led significant research projects including DIAGHOLO (2018-2023), RESSOURCES (2017-2018), and DETECTION (2015-2018). His research is supported by various grants from the Auvergne-Rhône-Alpes Region, ANR, and CNRS. At the Laboratoire Hubert Curien, he collaborates with colleagues across multiple disciplines to advance image processing techniques for diverse applications.

Uwe Freiherr von LukasView profile

Professor

• Maritime Graphics
• Underwater Image Processing
• Machine Learning for Computer Vision
• +4 more

Prof. Dr.-Ing. Uwe Freiherr von Lukas is Professor of Maritime Graphics at the University of Rostock , Faculty of Computer Science and Electrical Engineering, and heads the Rostock site of the Fraunhofer Institute for Computer Graphics Research IGD . Since 2010 he has also been Honorary Professor for Virtual Product Development and is a member of the Interdisciplinary Faculty’s Department of Maritime Systems. Education: Diplom in Computer Science, TU Darmstadt (1994) Doctorate (Promotion), University of Rostock Research Focus: His research concentrates on three pillars: Machine Learning for automated image and video analysis with a strong emphasis on underwater imagery , interactive visualization and immersive analytics of large-scale maritime data , and technology-oriented networks for innovation transfer and regional development . These topics converge in applications such as digital twins for the Baltic Sea, VR-based maritime training, and AI-driven ecosystem monitoring. Scientific Output & Trends: Recent publications (2022-2025) reveal an intensified integration of deep learning and computer vision techniques to solve domain-specific challenges in marine and environmental sciences. Studies range from transformer-based seagrass segmentation and unsupervised clustering of ROV imagery to digital-twin frameworks for ocean research, reflecting a clear trend toward AI-supported, data-centric maritime analytics . Professional Service & Networks: Board member, Subsea Monitoring Network e.V. Speaker, BMBF Future Cluster “Ocean Technology Campus Rostock” Managing Director, competence network “OceanTechnologies@Fraunhofer” Member of advisory boards of Society for Maritime Technology, Maritime Future Advisory Board Mecklenburg-Vorpommern, and others Labs & Teams: At Fraunhofer IGD Rostock he leads the Maritime Graphics group, coordinating more than thirty collaborative R&D projects that bridge computer graphics, VR/AR, and maritime engineering. The group operates state-of-the-art VR laboratories, underwater vision testbeds, and high-performance visualization facilities serving both academic and industrial partners.

• Computer Graphics
• Physically Based Animation
• Motion Capture
• +4 more

Paul G. Kry is an Associate Professor in the School of Computer Science at McGill University, where he leads the Computer Animation and Interaction Capture Laboratory. His research focuses on physically based animation, computer graphics, and human motor control, with applications in video games, movies, training simulations, ergonomics, and robotics. He teaches graduate and undergraduate courses including COMP 557 (Fundamentals of Computer Graphics) and COMP 559 (Fundamentals of Computer Animation). Dr. Kry's research interests center on computer graphics, physically based animation, skin deformations of articulated characters, motion capture, interaction, and physically based modeling of humans and animals. He investigates human and animal motor control (locomotion, grasping, manipulation) in combination with the physics of rigid objects, deformation, and contact. His work emphasizes the combination of real-world measurements, approximate models, and physically based simulation, with additional interests in machine learning, numerical methods, and audio. His recent publications demonstrate strong trends in physically based animation, with focus areas including adaptive simulation techniques, real-to-sim calibration, constraint-based physics, neural network applications in graphics, and motion control policies. His work spans both theoretical foundations and practical applications, often bridging the gap between computer graphics and robotics. BEST PAPER at Graphics Interface, 2023 BEST STUDENT PRESENTATION at ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, 2019 BEST PAPER at Computational Aesthetics / Expressive, 2016 Dr. Kry actively supervises numerous PhD and MSc students, with many graduates going on to positions at leading companies including Ubisoft, Google, Facebook, and Autodesk. He has served on program committees for major conferences including ACM SIGGRAPH, Symposium on Computer Animation, and Graphics Interface. His lab maintains specialized equipment including a 24-camera motion capture system, force plates, consumer DSLR cameras, high-speed cameras, data gloves, quadrotor robots, and various pressure sensors.

Geb W. ThomasView profile

Professor

• Human-Computer Interaction
• Robotics
• Virtual Reality
• +4 more

Dr. Geb W. Thomas is a Professor in the Department of Industrial and Systems Engineering at the University of Iowa , with a joint appointment in Orthopedics and Rehabilitation . He also serves as a Researcher at the Iowa Initiative for Artificial Intelligence . PhD, Industrial Engineering, Penn State University (1996) MS, Industrial Engineering, Penn State University (1995) BS, Physics, State University of New York (1991) Dr. Thomas specializes in Human-Computer Interface , Robotics , Virtual Reality , and Human Factors , focusing on applications in Orthopedic Surgery and Environmental Monitoring . His work bridges AI with surgical skill assessment and sensor network design for workplace safety. The 15 most recent publications highlight his leadership in Medical Simulation , including Fluoroscopy-based skill assessment , VR surgical training platforms , and Low-cost sensor networks for noise/ozone monitoring. Key trends include AI integration in orthopedic education and physics-informed environmental exposure modeling. Scientific Awards : Phi Kappa Phi - Engineering Honor Society Human Factors and Ergonomics Society Institute of Industrial Engineering His research involves Multidisciplinary Collaboration between engineering, medicine, and public health, with a focus on Simulation-Based Training and Autonomous Systems . He leads projects at the intersection of Medical Robotics and Occupational Safety .

• Biocomplexity
• Biophysics
• Computational Biology
• +6 more

Julius Bier Kirkegaard is a Tenure Track Assistant Professor at the University of Copenhagen, holding dual appointments at the Niels Bohr Institute (Biocomplexity section) and the Department of Computer Science (Image Analysis, Computational Modelling and Geometry group). His work bridges theoretical physics, computational biology, and computer science, focusing on complex biological systems through quantitative approaches. Dr. Kirkegaard's research spans multiple interconnected areas in biocomplexity and biophysics. His primary interests include: Biological transport networks and their optimization Chemotaxis and cellular gradient sensing mechanisms Computational modeling of biological structures (particularly plant venation networks) Image analysis techniques for biological systems Network topology in chemical reaction systems Deep learning applications in medical imaging Analysis of Dr. Kirkegaard's recent publications reveals a strong interdisciplinary approach combining physics, biology, and computational methods. His work often focuses on how biological systems optimize information processing and transport under physical constraints. A significant theme is the study of network structures in biological contexts, from leaf venation to cellular receptor organization. His more recent work increasingly incorporates machine learning techniques, particularly deep learning, for analyzing complex biological systems and medical imaging data. Dr. Kirkegaard maintains active collaborations across multiple institutions, as evidenced by his diverse publication record spanning physics, biology, and computer science journals. His research appears to be supported by various grants, though specific funding sources aren't detailed in the provided information. Based at the University of Copenhagen, Dr. Kirkegaard works within the Biocomplexity and Biophysics research environment at the Niels Bohr Institute, which provides a collaborative setting for interdisciplinary research at the interface of physics and biology.