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Israel NelkenView profile

Professor

• Auditory Neuroscience
• Neurophysiology
• Sensory Processing
• +3 more

Prof. Israel Nelken is a Full Professor at the Hebrew University of Jerusalem, affiliated with the Edmond and Lily Safra Center for Brain Sciences. His research focuses on auditory neurophysiology, specifically the neural mechanisms underlying sound processing, perception-action loops, and statistical learning in audition. He has contributed significantly to understanding how the brain detects deviant sounds and encodes complex auditory information across multiple temporal and spectral scales. Affiliations: Hebrew University of Jerusalem, Edmond and Lily Safra Center for Brain Sciences Roles: Full Professor, Principal Investigator of the Israel Nelken Lab Research Interests Prof. Nelken’s work explores the transformation of sensory signals into meaningful representations in the auditory system. Key areas include: Neuronal responses to complex sounds and their behavioral relevance Stimulus-specific adaptation (SSA) and prediction error detection Integration of auditory information across cortical and subcortical regions Role of auditory cortex in rhythmic motor synchronization and statistical learning Key Contributions His studies on deviance detection in auditory cortex have advanced our understanding of mismatch negativity (MMN) and predictive coding. Recent work highlights rats’ ability to synchronize movements with auditory rhythms, challenging assumptions about species-specific musicality. He has also developed innovative tools like the Rat Interactive Foraging Facility (RIFF) to study neural-behavioral interactions in real-time. Awards & Honors Rector’s Prize for Excellence in Research and Teaching (2015) Landau Prize for Sciences and Research (2015) Michael Bruno Memorial Award (2008) ERC Advanced Grant (2013) Grants & Collaborations Recipient of prestigious grants including the ERC Advanced Grant for studying auditory processing in natural environments. Active collaborations include work on cortical dynamics in Alzheimer’s models and computational frameworks for attentional blink phenomena. Labs & Teams Leads the Israel Nelken Lab, which integrates electrophysiology, computational modeling, and behavioral experiments to dissect auditory processing. The lab collaborates widely, contributing to projects like the dense cortical microcircuit simulations for understanding surprise responses.

• Analytical Chemistry
• Biophysics
• Environmental Chemistry
• +4 more

Mark Bier is a Research Professor and Director of the Center for Molecular Analysis in the Department of Chemistry at Carnegie Mellon University (CMU). He holds a Ph.D. from Purdue University (1988) and has been affiliated with CMU since 1996, progressing from Assistant to Associate Research Professor before becoming a Research Professor in 2010. His work focuses on mass spectrometry instrumentation development, including superconducting tunnel junction (STJ) cryodetection for heavy ion analysis and environmental applications like water quality monitoring. Research interests include nanoparticle analysis (e.g., Au clusters, viral particles), biomacromolecular complexes, and advancements in mass spectrometry detectors. Notable contributions include co-inventing the linear quadrupole ion trap (1995), now widely used, and developing the Virtual Mass Spectrometry Laboratory (VMSL) for education. He leads a dynamic research group with over 30 publications since 2000, addressing topics from environmental chemistry to bioanalytical methods. Awards include recognition for his patent on the linear ion trap. His lab collaborates on projects like the CO₂ Fence art installation to raise climate awareness and develops portable MIMS probes for fieldwork. Teaching includes courses on mass spectrometry fundamentals and instrumental analysis. Key achievements: Highest molecular weight mass spectra for polystyrene (2.2 MDa) and bacteriophage HK97 (13 MDa), STJ-based viral particle detection, and real-time biomolecule monitoring via micro-reactors. His work bridges academia and industry, with applications in virology, polymer science, and environmental protection.

Jiyoon YiView profile

Assistant Professor

• AI-enabled Food Safety
• Microbial Systems Engineering
• Machine Learning in Agriculture
• +3 more

Dr. Jiyoon Yi is an Assistant Professor in the Department of Biosystems and Agricultural Engineering (BAE) at Michigan State University's College of Engineering. Her research focuses on AI-driven solutions for sustainable food systems, integrating biosystems engineering with data science to address microbiological challenges. She holds a Ph.D. in Food Science from UC Davis (2021), and dual B.S. degrees in Mathematics and Food Science & Engineering from Ewha Womans University (2014). Key research areas: Rapid pathogen detection via hyperspectral microscopy AI analysis of soil microbiome interactions Generative AI modeling of microbial stress responses Teaching: HEAT 401: Heat and Mass Transfer in Biosystems (undergraduate) BAE 890: Machine Learning for Biosystems Engineering (graduate) Her lab employs both wet-lab and dry-lab approaches, with recent work emphasizing domain adaptation in imaging, attention-based AI for microbiome analysis, and computational simulations of microbial behavior. Current studies include developing antimicrobial coatings for food contact surfaces and optimizing sanitizer distribution in agricultural processing systems. Notable Contributions: Pioneering AI-enabled frameworks for real-time pathogen detection, including label-free cell analysis and adversarial domain adaptation across imaging modalities. Her work bridges gaps between computational methods and practical food safety applications, with applications in both food/health and agriculture domains.

• Educational Technology
• Computer Graphics
• Multimedia Systems
• +4 more

Alfredo Pina Calafi is a Professor at the Public University of Navarra's Department of Statistics, Computer Science and Mathematics. His work focuses on educational technology, computer graphics, and multimedia systems, with significant contributions to e-learning and technology integration in education. He is actively involved in curriculum adaptation to the European Higher Education Area (EHEA) and has pioneered projects like the Virtual Classroom initiative recognized with the 3rd Prize in National Awards for Educational Innovation (2005). His research spans augmented reality applications for linguistic heritage preservation, educational robotics in primary education, and interactive digital solutions for science learning. Education: PhD in Computer Science (University of Zaragoza, 2001) Key Projects: ALFA T_GAME (teaching materials exchange for computer graphics), VideoPlanet (planetarium visualization systems), and mobile emergency decision-making systems for Pamplona's bull run Research interests emphasize bridging technology and education through innovative tools. Over 25 years of academic contributions include directing three doctoral theses and co-authoring books on educational robotics and digital narratives. He has coordinated major educational adaptation projects and led teams developing virtual environments and intelligent systems for diverse applications. Notable collaborations include work with institutions like the European Center for Soft Computing and participation in international congresses on artificial intelligence and educational informatics. His work consistently integrates pedagogical theory with cutting-edge technological solutions.

Marc Erich LatoschikView profile

Professor

• Virtual Reality (VR)
• Augmented Reality (AR)
• Human-Computer Interaction
• +5 more

Prof. Marc Erich Latoschik is the head of the Human-Computer Interaction (HCI) Chair at the University of Würzburg. His research focuses on immersive technologies, VR/AR applications, and their psychological impacts. He holds a formal academic appointment as a Professor and has led major research initiatives in Germany, including the Embodiment Lab (Bavarian competence center for virtual embodiment) and projects like ViTras (VR therapy for obesity) and ILAST (VR rehabilitation for knee injuries). Education : Bachelor's/Master's in Mathematics and Computer Science (University of Paderborn) Studies at the New York Institute of Technology and Bielefeld University Research Interests : Latoschik’s work bridges computer science and cognitive sciences, emphasizing embodiment theory, time perception in VR, and social VR dynamics. His interdisciplinary approach combines AI, real-time systems, and 3D graphics to develop impactful technologies for therapy, training, and entertainment. Publications & Impact : He has authored over 160 peer-reviewed articles (e.g., in TVCG , IEEE VR ) and won awards for innovations like multimodal VR interfaces. His research is funded by DFG, BMBF, and EU agencies. Teaching & Service : Latoschik teaches courses on real-time systems, HCI principles, and scientific writing. He actively contributes to academic communities as a GI VR/AR SIG co-founder and reviewer for top conferences. Labs & Initiatives : His Embodiment Lab explores avatar embodiment, while projects like SIRIS and CaveUDK advance VR middleware and multimodal interfaces.

Les BowtellView profile

Associate Professor

• Renewable Energy
• Power Electronics
• Ultrasound Applications
• +12 more

Les Bowtell is an Associate Professor in Electronic Engineering at the University of Southern Queensland (UniSQ), where he also earned his BEng, MEng, and PhD. He has been a key academic in the School of Engineering, serving as the Electrical Discipline Lead from 2006 to 2023, and maintains interdisciplinary affiliations with the School of Surveying and Built Environment, School of Nursing and Midwifery, and the Centre for Agricultural Engineering. His research spans renewable energy, power electronics, ultrasound-based water treatment, biochar applications, and precision livestock farming. He has supervised numerous doctoral and master’s students on topics such as biomass gasification, methane mitigation in cattle, and environmental remediation using biochar. His work integrates engineering with agricultural and environmental sustainability, often focusing on practical, scalable solutions. Les Bowtell’s recent publications (2020–2024) reflect a strong trend in sustainable energy and environmental technologies, particularly in biomass valorization (e.g., wheat straw pellets), ultrasound-enhanced water treatment, and carbon-based adsorbents. His work frequently employs experimental and modeling approaches, including thermogravimetric analysis, CFD simulations, and pilot-scale reactor studies. He has collaborated extensively with researchers such as Raed A. Al-Juboori, Guangnan Chen, and Talal Yusaf. His scientific contributions are disseminated through high-impact journals in energy, environmental engineering, and water treatment. Les Bowtell is actively involved in research supervision and education innovation, having developed remote access laboratories and interactive emulators to enhance nursing education. He has no listed scientific awards in the provided text, but his prolific output and leadership roles indicate significant academic impact. He leads or contributes to research teams working on renewable energy systems, agricultural waste conversion, and sustainable water purification. His labs and projects often involve interdisciplinary collaboration across engineering, agriculture, and environmental science, aiming to develop scalable technologies for real-world implementation.

Frank HaußerView profile

Professor

• Numerical Mathematics
• Scientific Computing
• Mathematical Modeling
• +4 more

Prof. Dr. Frank Haußer is a Professor at Beuth University of Applied Sciences Berlin in the Department II Mathematics - Physics - Chemistry. He serves as the academic advisor for the Applied Mathematics program and teaches courses including Numerical Mathematics, Mathematical Methods of Digital Image Processing, and Computational Engineering. His consultation hours are held during semesters and by appointment, with availability both in-person and online. Haußer's research focuses on: Numerical mathematics and scientific computing Mathematical modeling with applications in MATLAB/Octave Machine learning for medical imaging and insect monitoring Digital image processing techniques for biomedical applications Partial differential equations and computational engineering methods He has authored a textbook on mathematical modeling with MATLAB/Octave and leads interdisciplinary projects at the intersection of mathematics and technology. Analysis of his 15 most recent publications shows strong emphasis on: Medical imaging algorithms (especially retinal OCT analysis) Nanostructure dynamics and material science Computational physics and finite element methods Machine learning applications in biology and medicine Advanced mathematical modeling techniques His work consistently bridges theoretical mathematics with practical engineering applications. Haußer actively supervises student research, including: Machine learning for insect classification and localization Medical image processing algorithms Computational methods in engineering Finite element analysis applications Optimization and simulation techniques He has guided over 30 bachelor's and master's theses since 2009. His research projects include: KInsekt (2020-2023): AI-based insect monitoring funded by BMUV BeCRF (2015-2017): Medical image quality validation funded by BMWi QM ROCT (2013-2015): Automated OCT quality management funded by IFAF These interdisciplinary collaborations involve institutions across Germany.

• Medical Physics
• Radiation Oncology
• Proton Therapy
• +5 more

Alexander Van Slyke serves as an Assistant Professor in the Department of Therapeutic Radiology at Yale School of Medicine, Yale University. His primary appointment focuses on medical physics research within the radiation oncology division, contributing to both clinical and preclinical radiation therapy advancements. His educational background includes: PhD in Biophysics from Cornell University (2019) BA in Physics and Mathematics from SUNY Geneseo (2012) Certificate in Medical Physics from University of Pennsylvania (2020) Medical Physics Residency at University of Maryland (2023) He holds board certification from the American Board of Radiology in Therapeutic Medical Physics (2024). Dr. Van Slyke's research centers on cutting-edge radiation therapy technologies and radiobiological mechanisms. His primary expertise spans FLASH radiotherapy (particularly proton FLASH), real-time electromagnetic surface tracking for motion management, oxygen dynamics monitoring during irradiation, and small animal radiation research. He employs advanced techniques like phosphorescence quenching for ultrafast oxygen sensing and develops optimization algorithms for treatment delivery. His work bridges medical physics innovation with radiobiological investigation to enhance radiation therapy precision. Analysis of his publications reveals a strong trajectory toward understanding ultra-high dose rate radiation effects, with recent work focusing on geometric validation of tracking systems (2025) and oxygen depletion dynamics during proton FLASH delivery. His research consistently integrates preclinical models with clinical translation, emphasizing motion management solutions and biological response characterization. Dr. Van Slyke actively contributes to departmental leadership as Acting Co-Chair of the C-RAD Optimization Committee and Chair of the Lung SBRT Planning Committee. His conference presentations at AAPM meetings demonstrate expertise in electromagnetic tracking feasibility, motion effect simulations for LATTICE therapy, and oxygen monitoring techniques. He operates within Yale's radiation oncology ecosystem, collaborating with medical physics and radiobiology teams to advance therapeutic radiology through technological innovation and radiobiological insight.

Kayhan KaplanView profile

Lecturer

• Visual Communication Design
• 3D Animation
• Cultural Heritage Conservation
• +3 more

Kayhan Kaplan is a Lecturer at the Department of Visual Communication Design, Faculty of Communication, Hasan Kalyoncu University. He holds a PhD in Landscape Architecture from Atatürk University and a 3D Animation certificate from New York Film Academy. PhD: Atatürk University, Landscape Architecture (2002) MS: New York Film Academy, 3D Animation (2012) BS: Atatürk University, Landscape Architecture (1991) His research focuses on 3D animation for historical reconstruction , cultural heritage visualization , and environmental impact analysis . Recent work includes digital modeling of ancient Antioch and conservation strategies for Turkish cultural sites. Collaborative studies span industrial visualization , forensic animation , and climate change mitigation in river basins. His publications demonstrate expertise in 3D rendering engines , animated narrative design , and ecological monitoring systems . Collaborations with environmental scientists and engineers highlight interdisciplinary applications of visual communication tools. As a full-time faculty member, he contributes to curriculum development in visual design and technology integration in communication. His work bridges digital humanities and scientific visualization through practical implementations in cultural and industrial contexts.

• Biomedical Engineering
• Medical Devices
• Artificial Intelligence in Control Systems
• +3 more

Phi Anh Phan is an Associate Professor in the Department of Clinical Neurosciences at the University of Oxford, specializing in biomedical engineering. Their work bridges hardware, software, and modeling to develop medical devices and robotic systems. Education: BE in Mechatronics, PhD in Artificial Intelligence and Control System Research focuses on non-invasive physiological monitoring and device development, particularly the InspiWave technology for lung function analysis. Key areas include respiratory physiology, AI-driven medical diagnostics, and biomedical signal processing. Recent publications highlight applications of the Inspired Sinewave Technique in neurocritical care, pulmonary blood flow estimation, and comparative studies with CT imaging. Trends emphasize computational modeling, animal studies, and clinical translation. Scientific Awards: Enterprise Fellow of the Royal Academy of Engineering Phan actively engages in technology commercialization, serving as a finalist in the OneStart life-science competition twice. Current efforts include spinning out InspiWave for intensive care and outpatient diagnostics.

Joan LasenbyView profile

Professor

• Image and Signal Analysis
• Motion Capture
• Geometric Algebra
• +4 more

Joan Lasenby is a Professor of Image and Signal Analysis at the Department of Engineering , University of Cambridge. She is affiliated with the Cambridge Mathematics of Information in Healthcare Hub (CMIH) . Research focuses on advanced motion capture, geometric algebra applications, and healthcare technology Key contributions to 3D reconstruction, camera pose estimation, and biomedical sensor fusion Recent work spans neonatal monitoring, protein structure modeling, and fluid dynamics simulations Her publications demonstrate strong expertise in combining geometric algebra with deep learning for diverse applications in computer vision, biomedicine, and physics simulations. As part of the Cambridge Engineering faculty, she contributes to interdisciplinary research at the intersection of mathematics, computer science, and healthcare technology.

Mirna Mihovilovic SkanataView profile

Assistant Professor

• Biophysics
• Neuroscience
• Neural Circuits
• +4 more

Mirna Mihovilovic Skanata is an Assistant Professor in the Department of Physics at Syracuse University, with a courtesy appointment in the Biology Department and affiliations to the BioInspired Institute and Interdisciplinary Graduate Neuroscience Concentration. She joined Syracuse in 2021 after postdoctoral work at New York University and a Ph.D. in Physics from Brown University. B.Sc. in Physics, University of Zagreb (2008) M.Sc. in Physics, Brown University (2009) Ph.D. in Physics, Brown University (2014) Her research focuses on understanding how physical principles shape neural function and behavior, particularly how neural circuits orchestrate decisions, learning, and locomotion in Drosophila larvae. She combines interdisciplinary approaches from physics, molecular biology, engineering, and computational neuroscience. Her recent publications highlight innovations in closed-loop two-photon imaging, behavioral variability analysis, and neural circuit dynamics. She has secured major grants from NIH and The McKnight Endowment Fund, and her lab’s work explores multisensory integration, neural pattern manipulation, and real-time behavioral simulations. NIH Maximizing Investigators’ Research (MIRA) Award (2023) McKnight Technological Innovations in Neuroscience Award (2022) Physics Department Teaching Award (2023) Physics Department Community Building and Social Justice Award (2024) She advises graduate and undergraduate students in her NeuroBioPhysics Lab, which emphasizes interdisciplinary collaboration and technology development for decoding neural computations. Her lab’s outreach initiatives include the "Sweet for hearts" behavioral arena project.

Kayhan AYARView profile

Assistant Professor

• Virtual Reality
• Information Security and Cryptology
• 3D Computer Graphics
• +3 more

Kayhan AYAR is an Assistant Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Computer Engineering. His expertise spans Virtual Reality, Information Security, Cryptology, and 3D Computer Graphics, with a focus on simulation-based educational technologies and haptic interaction systems. Doctorate: 2010–2020, Sakarya University (Thesis: 3D Image of MIG-MAG Welding Seam using Voxified Paraboloid) Master's: 2008–2010, Sakarya University (Thesis: DirectX-based 3D Game Engine Design) Bachelor's: 2000–2007, Sakarya University His research explores virtual welding simulators, voxelization techniques, and real-time haptic applications. Key publications include 15 recent articles (2010–2024) on topics like 3D modeling, neural networks in welding training, and VR-based security applications for energy infrastructure. He has contributed to international conferences and journals such as the Turkish Journal of Electrical Engineering and Computer Sciences and Journal of Materials Education . His work includes a 2014 patent for a virtual welding simulator and participation in TÜBİTAK-funded projects. Teaching responsibilities include courses in Game Programming, Data Structures, Computer Graphics, and Parallel/Distributed Systems, alongside advising graduation projects and specialization areas.

Bernhard HöfleView profile

Professor

• Geoinformatics
• 3D Point Cloud Analysis
• Environmental Monitoring
• +5 more

Prof. Dr. Bernhard Höfle is a Professor of Geoinformatics and 3D Geospatial Data Processing at the University of Heidelberg, where he leads the 3DGeo Research Group. His work focuses on computational methods for analyzing 3D/4D point clouds, with applications in environmental monitoring, natural hazard assessment, and vegetation studies. Research Interests: 3D/4D point cloud analysis for environmental observation Development of computational algorithms for geospatial data Integration of machine learning in remote sensing applications Virtual laser scanning simulations (VLS-4D) Real-time monitoring systems for critical infrastructure Digital Twin integration across scales Article Trends: His recent publications emphasize real-time 3D environmental monitoring, virtual simulation of dynamic scenes, multi-temporal analysis of natural processes, and machine learning applications for point cloud classification. They span from 2025 back to 2023 and cover diverse applications including rock glaciers, forest monitoring, building damage assessment, and bee activity tracking. Key Techniques: His work prominently features terrestrial laser scanning, UAV-based LiDAR, and open-source software development. He has contributed datasets like FOR-species20K and developed simulation frameworks such as HELIOS++.

Flemming Jannik Vind BjerrumView profile

Associate Clinical Professor

• Surgical Simulation
• Artificial Intelligence in Surgery
• Robotic Surgery Training
• +3 more

Flemming Jannik Vind Bjerrum holds a dual appointment as Clinical Associate Professor at the University of Copenhagen's Department of Clinical Medicine and as a surgeon at the Capital Region of Denmark, primarily affiliated with Amager and Hvidovre Hospital and Copenhagen Academy for Medical Education and Simulation. His work bridges clinical practice and academic research in surgical innovation. His research focuses on simulation-based training and competency assessment for minimally invasive and robotic surgery. Key areas include development of AI algorithms for surgical gesture annotation, virtual reality simulation modules, and evidence-based training protocols. His fingerprint analysis reveals dominant expertise in surgeon training , systematic reviews , laparoscopy , and simulation training , with significant contributions to surgical AI applications. Recent publications (2024-2025) show a strong trend toward artificial intelligence integration in surgical training and assessment, particularly in robotic surgery gesture analysis, bronchoscopy, and bowel preparation evaluation. Over 80 research outputs demonstrate consistent productivity, with 17 publications in 2024 alone indicating active current research. No scientific awards are publicly documented in the provided materials. His advising activities and grant funding are not explicitly detailed in available sources, though his leadership in multicenter trials (e.g., robotic cardiac surgery simulation assessment) suggests collaborative grant involvement. His work with the Copenhagen Academy for Medical Education and Simulation indicates institutional leadership in surgical education infrastructure. Bjerrum co-develops simulation technologies including virtual reality modules for canine surgery and AI-driven assessment tools, operating within interdisciplinary teams at Copenhagen Academy for Medical Education and Simulation. His research network shows extensive international collaboration, particularly in surgical AI standardization efforts.