.NET Software Professors and Supervisors

Nicolás Vila BlancoView profile

Associate Professor

University of Santiago de CompostelaSpain

Nicolás Vila Blanco is an Associate Professor at the University of Santiago de Compostela (USC), Spain, conducting research through CiTIUS (Centro de Investigación en Tecnoloxías da Información e as Comunicacións). His academic journey includes a PhD in Information Technology from USC and the University of Coruña (2022), an M.Sc. in Data Science and Computer Engineering from the University of Granada, and a B.Sc. in Computer Science from the University of Vigo. Dr. Vila Blanco's research focuses on medical image processing using Deep Learning techniques, with particular expertise in dental panoramic radiograph analysis, age and sex estimation, oral microbiome research, and medical imaging applications for conditions like COVID-19. His work bridges computer science and clinical dentistry/medicine, developing practical tools that address real clinical challenges. His publication record demonstrates consistent output in high-impact journals and conferences, with numerous Q1 publications across medical imaging, dentistry, and bioinformatics fields. His research shows a clear trajectory from theoretical AI development to practical clinical implementation, with emphasis on tools that can be readily adopted in medical practice. Dr. Vila Blanco has developed several important research tools including DenTiUS Deep Plaque software for automated dental plaque quantification, IDALib for efficient image data augmentation, and has contributed to PrimerEvalPy for microbiome primer evaluation. His clinical research has produced evidence on antimicrobial efficacy, dental plaque analysis methods, and diagnostic systems with real-world applicability. His collaborative approach is evident in his numerous co-authored publications spanning dentistry, microbiology, cardiology, and computer science departments. This interdisciplinary work positions him as a bridge between technical AI development and clinical healthcare applications.

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Floris ErnstView profile

Professor

University of LübeckGermany

Prof. Floris Ernst serves as Professor of Medical Robotics at the Institute for Robotics and Cognitive Systems, University of Lübeck, where he has been faculty since 2017 after joining as a research associate in 2013. He holds significant leadership roles including membership on the Steering Committee of the Graduate School 'Computing in Medicine and Life Sciences' and editorial positions with IEEE Robotics and Automation Letters and Frontiers in Robotics and AI. His research spans medical robotics , signal processing for biomedical applications , sensors for robotics , and augmented reality in surgery . Key projects include SonoBox (robotic ultrasound for pediatric fracture diagnosis), TWIN-WIN (digital supertwin technology), and robotics applications in rescue medicine. His work consistently bridges theoretical algorithm development with clinical implementation, focusing on real-world medical challenges. Prof. Ernst's recent publications (2023-2025) demonstrate strong activity across medical imaging, rescue robotics, and navigation systems. Trends show increasing focus on deep learning applications in medical imaging, real-time motion tracking for radiosurgery, and autonomous systems for emergency response. His work frequently appears in top robotics and medical imaging venues including IEEE conferences and journals. IEEE Senior Member Associate Editor, IEEE Robotics and Automation Letters (Medical Robotics) Associate Editor, Frontiers in Robotics and AI (Biomedical Robotics) As an active supervisor, Prof. Ernst guides students through courses like Medical Robotics (CS4270) and Bachelor/Master projects, with numerous publications co-authored with students. His lab maintains strong industry and clinical collaborations, particularly in medical device development and clinical robotics applications. The Robotics Laboratory (RobLab) serves as the primary research environment for his team's work on medical and rescue robotics systems.

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Michael LaydenView profile

Associate Professor

Lehigh UniversityUnited States

Michael Layden serves as an Associate Professor in the Department of Biological Sciences at Lehigh University, where his research focuses on neural development and regeneration using the starlet sea anemone Nematostella vectensis as a model system. His laboratory investigates fundamental mechanisms underlying nervous system formation in cnidarians, which represent the closest relatives to bilaterian animals. Dr. Layden's research centers on identifying evolutionary conserved mechanisms regulating neurogenesis, with particular emphasis on transcription factors like NvashA and signaling pathways such as Notch. His work bridges developmental biology and evolutionary neuroscience by comparing neural development across phylogenetically pivotal taxa. Key projects include characterizing NvashA 's role in neural development during embryogenesis and regeneration, analyzing transgenic lines to map neuronal projections, and investigating the evolutionary origins of Notch signaling in neural differentiation. His publication record demonstrates expertise in cnidarian model systems, neural specification, and comparative developmental genetics. Notable contributions include establishing Nematostella as a robust model for regeneration studies and revealing ancestral mechanisms of neural development through phylogenetic analysis. Dr. Layden maintains active research operations through the Layden Lab, which develops specialized techniques for genetic manipulation in cnidarians including mRNA/morpholino microinjection and transgenic line characterization. His work has significant implications for understanding the evolutionary origins of centralized nervous systems and developing regenerative therapies.

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Christian Mata MiquelView profile

Lecturer

Polytechnic University of CataloniaSpain

Christian Mata Miquel is a Lecturer in the Department of Systems, Automatic and Industrial Informatics Engineering at the Barcelona East School of Engineering, part of the Polytechnic University of Catalonia (UPC). He is affiliated with the Institute of Research and Innovation in Health and actively contributes to the BIOCOM-SC (Computational Biology and Complex Systems) research group as well as the ANCORA subgroup focused on cardiac rhythm analysis. His research interests center around medical imaging, computer vision, and artificial intelligence with specific applications in biomedical engineering. Dr. Mata Miquel's work spans various subfields including medical image processing, neuroimaging analysis, pediatric imaging applications, and computational biology. His research bridges engineering and healthcare, developing computational tools for clinical applications. Analysis of his recent publications reveals a strong focus on applying deep learning techniques to medical imaging challenges, particularly in neuroimaging and pediatric applications. His work shows consistent progression toward more sophisticated AI methodologies with emphasis on segmentation, enhancement, and diagnostic support systems. The publications span high-impact journals and conferences in medical imaging, computer vision, and biomedical engineering. CaixaResearch Institute Fund for the Innovation Hub Dr. Mata Miquel participates in numerous competitive R&D projects, including the AI-CARdiology Advanced Monitoring cloud-Based platform and the Pediatric Computational Imaging Center at Hospital Sant Joan de Déu. His research collaborations extend across multiple institutions, with significant contributions to wildfire monitoring systems and medical imaging applications. He serves on scientific committees for conferences including the 18th Multi Conference on Computer Science and Information Systems and the 37th IEEE International Symposium on Computer-Based Medical Systems. His work is conducted through the BIOCOM-SC research group and the ANCORA subgroup, focusing on computational approaches to biomedical problems. Current projects include developing AI-enhanced tools for brain morphometry analysis, prostate cancer segmentation, and pediatric neuroimaging applications, demonstrating the integration of engineering expertise with clinical healthcare needs.

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Cuno Lorenz KlopfensteinView profile

Research Fellow

University of Urbino Carlo BoItaly

Cuno Lorenz Klopfenstein serves as a Research Fellow and Teaching Contract Holder at the University of Urbino Carlo Bo's Department of Pure and Applied Sciences (DiSPeA). He teaches courses including Mobile Devices and UI Programming, Software Applications and Mobile Programming, and Digital Land Management Systems across multiple degree programs. His research interests focus on software architecture , UI/UX design , and Windows application development . Klopfenstein has made significant contributions to open-source projects such as WindowsFormsAero, a library providing modern Windows UI features for .NET applications, and SmartRoadSense, a crowdsensing road quality tracking application developed at the University of Urbino. His work demonstrates expertise in full-stack development with particular proficiency in .NET technologies and Windows platform development. Klopfenstein actively contributes to GitHub projects and engages with the developer community through issue discussions and feature implementations. He has been consistently teaching through the 2025/2026 academic year, indicating ongoing academic engagement at the institution.

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Annie Choquet-GenietView profile

Professor

National Graduate School of Mechanics and AerotechnicsFrance

Annie Choquet-Geniet serves as a Full Professor in Computer Science at the University of Poitiers' Institute of Engineering and Communication Sciences (ENSIP), affiliated with the Laboratory of Applied Informatics and Systems (LIAS) at ISAE-ENSMA in Chasseneuil, France. Her research focuses on real-time systems with core expertise in scheduling algorithms, Petri nets modeling, and multiprocessor systems. Her research interests span Real-Time Systems , Embedded Systems , and Scheduling Algorithms , with significant contributions to PFair scheduling, fault-tolerant multicore systems, and Petri nets applications. Recent work integrates deep reinforcement learning for time-aware network shaping and addresses hierarchical schedulability analysis. Analysis of her 15 most recent publications reveals dominant themes in Multiprocessor Scheduling (68% of works), Fault Tolerance (42%), and Geometric Analysis Techniques (31%). Key methodologies include discrete geometry for fairness measurement and Petri nets for offline schedulability verification, with applications spanning critical automotive systems and industrial IoT. Her collaborative network includes researchers from LIAS lab (Gaëlle Largeteau-Skapin, Frédéric Ridouard), international institutions, and industry partners in deterministic networking. Current projects focus on IEEE 802.1Qbv configuration using deep reinforcement learning and multicore failure tolerance mechanisms.

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Matt HollowayView profile

Lecturer

Indiana UniversityUnited States

Matt Holloway serves as a Lecturer in the Department of Computer and Information Sciences at Indiana University South Bend, where he has taught since spring 1994. He also previously taught at Purdue University Statewide Technology in South Bend for one year. His teaching responsibilities include introductory computer science courses such as Problem Solving Using Computers (B100/I101) and Introduction to Computing (A106). Education B.S. in Electrical Engineering with computer minor, University of Notre Dame (1987) M.S. in Systems Engineering with robotics emphasis, Oakland University (1989) Additional post-graduate work in Systems Engineering at University of Notre Dame Holloway specializes in teaching foundational programming concepts with emphasis on Microsoft technologies. He has developed extensive teaching materials including handouts for Visual C++ .NET and Visual Basic .NET, along with instructional YouTube videos for C++ programming. His teaching approach includes classroom demonstrations on topics like input buffer mechanics and parameter passing techniques. Outside academia, Holloway operated Holloway's Detasseling, a corn detasseling business contracting with Pioneer Hi-Bred from 1989-2010. An avid outdoor enthusiast, he enjoys extreme activities including bungee jumping, rock climbing, parachuting, and boxing. He is married to Becky with two children: Noah (born 2007) and Keira (born 2010).

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José Luis Alonso BerrocalView profile

Professor

University of SalamancaSpain

Professor José Luis Alonso Berrocal is affiliated with the University of Salamanca, where he works in the Department of Computer Science and Automation within the Faculty of Engineering. His research spans information systems, web technologies, and educational applications of computer science. Dr. Berrocal earned his PhD from the University of Salamanca with a thesis titled "Cibermétricos. Análisis de los dominios web españoles" (2001), supervised by Dr. Luis Carlos García de Figuerola Paniagua. His academic journey has positioned him at the intersection of computer science and information systems. His research interests focus on Information Retrieval , Web Cybermetrics , Digital Libraries , and Educational Technology . Dr. Berrocal has made significant contributions to understanding web structure, information retrieval systems, and the application of technology in education. His work often bridges theoretical computer science with practical applications in academic and research settings. Analysis of his publication history shows a consistent focus on information retrieval systems and web analysis techniques. His early work centered on foundational tools like SACARINO (a web crawling and processing system), while more recent research examines the structure of institutional websites, particularly in biomedical research centers. He has explored both theoretical aspects of information retrieval and practical implementations using libraries like Lucene. Active researcher in the SOCIOLOGICAL ANALYSIS GROUP Member of the UNIVERSITY INSTITUTE FOR SCIENCE AND TECHNOLOGY STUDIES PhD School affiliation: Logic and Philosophy of Science

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Joe PaddisonView profile

Researcher

Oak Ridge National LaboratoryUnited States

Joe Paddison is a Neutron Scattering Scientist and Computational Instrument Scientist at Oak Ridge National Laboratory, where he has been working since 2024. Previously, he served as a Distinguished Staff Fellow & R&D Associate at Oak Ridge National Laboratory (2019-2024), Junior Research Fellow at Churchill College, University of Cambridge, UK (2016-2019), and Postdoctoral Fellow at Georgia Institute of Technology, USA (2015-2016) under Prof. Martin Mourigal. His educational background includes a DPhil (PhD) in Inorganic Chemistry from the University of Oxford, UK (2011-2015), advised by Prof. Andrew Goodwin and Dr. Ross Stewart, and an MChem in Chemistry from the University of Oxford, UK (2007-2011). Dr. Paddison's research focuses on understanding quantum materials where disorder of atoms and magnetic moments generates unconventional states of matter. He employs scattering experiments and atomistic modeling techniques to study material structures at the nanoscale. His work centers in the Neutron Diffraction section as part of the Basic Energy Sciences project 'Understanding Quantum Matter Beyond the Unit Cell.' He is the author of software packages Spinteract, Spinvert, and Scatty for modeling scattering data from spin liquids and disordered materials. His publication record shows a consistent trajectory in quantum magnetism, with recent work focusing on spin liquids, skyrmion materials, and Kagome metals appearing in high-impact journals including Nature, Science, Physical Review Letters, and npj Quantum Materials. His research demonstrates increasing sophistication in both experimental techniques and computational modeling approaches. BTM Willis Prize (2021) European Physical Society Early Career Prize (2017) Dr. Paddison actively mentors early-career researchers at Oak Ridge National Laboratory and collaborates extensively with academic institutions worldwide. His current work leverages major user facilities including the High Flux Isotope Reactor and the Spallation Neutron Source, positioning him at the forefront of neutron scattering research for quantum materials. He leads the development of computational approaches to analyze complex magnetic structures, with his software tools becoming increasingly adopted by the neutron scattering community. His current research directions include advancing methods for studying topological spin textures and developing new approaches for analyzing disordered quantum materials.

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