جستجوی استاد راهنمای دانشگاهی

• Medical Image Analysis
• Computer-Aided Detection
• Endoscopy
• +۴ مورد دیگر

Joost A. van der Putten is a Researcher at Eindhoven University of Technology's Electrical Engineering department, affiliated with the Center for Care & Cure Technology Eindhoven and specializing in Video Coding & Architectures. His work bridges electrical engineering and medical applications through advanced AI development. His research expertise spans critical areas in medical AI: Computer-Aided Detection systems for gastrointestinal conditions Neural network applications in endoscopic imaging Early cancer detection in Barrett's esophagus Foundation models for medical image analysis Real-world implementation of AI in clinical settings Van der Putten's recent publications reveal a strategic focus on developing robust AI solutions that address practical challenges in endoscopic imaging, particularly improving detection accuracy under varying real-world conditions while optimizing human-AI interaction through thoughtful interface design. His work demonstrates strong translational potential from laboratory to clinical practice. His notable recognition includes: Second place in the GIANA challenge for Angiodysplasia detection (2017) He actively contributes to major research initiatives including XL-ARGOS (through June 2025) focused on automatic recognition of esophageal irregularities, and PATIENCE 2 (completed November 2023) developing patient-centric healthcare technologies. His research has garnered significant media attention, particularly regarding algorithms that detect early-stage esophageal cancer, potentially preventing invasive surgery and reducing mortality.

• Multi-modal Sensor Fusion
• Smart Surveillance
• 3D Reconstruction
• +۵ مورد دیگر

Egor Bondarau is an Associate Professor at Eindhoven University of Technology (TU/e), leading the Video Coding & Architectures group. His primary research focuses on multi-modal sensor fusion, smart surveillance systems, and photorealistic 3D reconstruction. He leads a research cluster on real-time data fusion from thermal, depth, laser, and RGB sensors, supervising five PhD students and multiple MSc students. Bondarau is a project leader in EU initiatives like PaSSANT, PS-CRIMSON, and APPS, addressing multi-camera surveillance challenges. Education: MSc in Robotics and Informatics from Belarus Polytechnic University (1997); PhD in Computer Science from TU/e (2009). Academic roles include teaching Computation I (BSc) and Computer Vision AI & 3D Data Analysis (MSc). Research interests span real-time computer vision, algorithm valorization (deployed at ST Microelectronics, ViNotion, etc.), and smart surveillance innovations. His work contributes to UN Sustainable Development Goals, particularly through traffic analysis and urban monitoring. Scientific Awards: ITEA Award of Excellence 2020, Best Lecturer EE Department 2017, ITEA 2024 Excellence Award. Advising & Grants: Supervised 21 academic works. Led 9 EU-funded projects, including SMART ITEA and Interreg initiatives. Labs/Teams: Coordinates TU/e’s internal multi-modal sensor fusion cluster and collaborates with global tech partners.

Iris Huijbenمشاهده پروفایل

پژوهشگر

• Representation Learning
• Sleep Medicine
• Medical Signal Processing
• +۳ مورد دیگر

Iris Huijben is a Researcher and Doctoral Candidate in the Signal Processing Systems group at Eindhoven University of Technology (TU/e). Her work bridges signal processing and deep learning in sleep medicine and fetal health monitoring. She holds an MSc in Electrical Engineering (cum laude, 2019) from TU/e and is pursuing a PhD under Prof. Ruud van Sloun, focusing on discrete representation learning for sleep recordings. Research Interests: Representation learning for biomedical signals, fetal health assessment using cardiotocograms, sleep stage analysis, and machine learning-driven data compression. Key Projects: Developed attention mechanisms for sleep stage classification, improved fetal health anomaly detection with contrastive predictive coding, and analyzed temporal dynamics of parasomnia awakenings. Collaborations: Research internship at Qualcomm AI Research (Amsterdam) on data compression. Publications highlight advancements in medical AI, including real-time fetal monitoring systems and sleep dynamics analysis. Awards include TU/e’s MSc Thesis Award 2020 for work on sub-Nyquist sampling in medical ultrasound.

Peter de Withمشاهده پروفایل

استاد

• Video Compression
• Image Analysis
• Healthcare Applications
• +۴ مورد دیگر

Peter de With is a Part-time Full Professor in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e), leading the Video Coding & Architectures Group. His expertise spans video compression, image analysis in healthcare, surveillance, and multimedia. He holds a PhD from Delft University of Technology (1992) and has held roles at Philips Research, the University of Mannheim, and Cyclomedia Technology. His research focuses on video/image signal processing, machine learning, and healthcare applications such as esophageal cancer detection. He is an IEEE Fellow and has authored over 400 papers, receiving multiple awards for his work. Research interests include video coding, medical imaging, and system innovations in health, surveillance, and automotive sectors. Key publications address challenges in medical instrument detection, 3D ultrasound, and multiview rendering. He collaborates with industry partners like Bosch Security and hospitals for oncology research. His work bridges academic innovation with real-world applications, emphasizing practical solutions in healthcare technology and multimedia systems. Awards include IEEE Fellow status and paper awards from CE Chester Sall, SPIE, and Elsevier. He chairs program committees for IEEE conferences and holds 30 patents. His contributions to video analysis and system design have driven advancements in safety, security, and healthcare technologies.

• Teachers
• Design
• Technology
• +۵ مورد دیگر

Susan McKenney is a Full Professor at the University of Twente, holding roles in both the Digital Society Institute and the ELAN Teacher Development program. Her research focuses on educational design, teacher development, and the integration of cutting-edge research into curricula. She has contributed significantly to methodologies in educational design research and the practical application of these theories in classroom settings. Her expertise spans teachers' professional growth, curriculum design, and the use of technology to enhance learning. Key areas of research include collaborative learning environments, the role of conversational agents in education, and the impact of contextual learning materials derived from real-world scientific research. Dr. McKenney has been honored with the AECT Outstanding Book Award (2013) and has delivered numerous invited talks on educational design frameworks, teacher reflection tools, and scaling educational innovations. Her work emphasizes bridging research and practice through partnerships with schools and educational institutions. Her recent articles highlight advancements in AI-driven educational tools, boundary-crossing collaborations in citizen science projects, and the evaluation of digital transformation initiatives in schools. She actively contributes to professional development programs, focusing on leadership in teacher design teams and reflective practices.

Vinod Nigadeمشاهده پروفایل

استاد مهمان

• Deep Learning
• Edge Computing
• Video Analytics
• +۵ مورد دیگر

Vinod Nigade is a Visiting Professor in the Department of Computer Science at Vrije Universiteit Amsterdam (VU). His research focuses on edge computing, deep learning systems, and network security. He holds a PhD in Computer Science from VU, defended in 2023 with his thesis Latency-Critical Inference Serving for Deep Learning . Key research areas include: Dynamic edge networks and latency-optimized inference systems IoT communication protocols and battery-free device synchronization Neural intrusion detection in programmable networks Distributed deep learning architectures Collaborations span academia-industry projects involving real-time systems, network programmability, and cybersecurity. His work addresses challenges in timely video analytics, service-level objectives in edge computing, and scalable exploit detection in distributed environments. Publications emphasize practical solutions for latency-critical applications, with contributions to ACM, IEEE, and other top venues. Current research trends include accelerating IoT discovery protocols and enhancing network security through AI-driven systems.

Antonios Liapisمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Procedural Content Generation
• Computational Creativity
• +۵ مورد دیگر

Antonios Liapis is an Associate Professor at the Institute of Digital Games, University of Malta. He completed his PhD in September 2014 under the supervision of Georgios N. Yannakakis at the IT University of Copenhagen. His academic journey includes an M.Sc. in Information Technology from the same institution and a 5-year Diploma in Electrical and Computer Engineering from the National Technical University of Athens. Dr. Liapis has held various academic positions at the University of Malta: Post-doctoral Researcher (2014-2015), Lecturer (2015-2020), Senior Lecturer (2020-2022), and currently Associate Professor (2022-present). He has served as General Chair for multiple international conferences including FDG (2020), GALA (2019), and EvoMusArt (2018-2019). He is an Associate Editor of the IEEE Transactions on Games and a member of the Games Technical Committee of the IEEE Computational Intelligence Society. His research focuses on Artificial Intelligence as an autonomous creator and as a facilitator of human creativity. Key areas include computationally intelligent tools for game design and computational creators that blend semantics, visuals, sound, plot, and level structure to create various game genres including horror, adventure, shooter, and dungeon crawler games. His work has resulted in over 150 peer-reviewed publications and several research awards. Dr. Liapis has secured multiple research grants from the European Commission, including projects on AI-powered robotic material recovery, virtual reality aided design, and learning science through coding and play. His notable project series "Data Adventures" demonstrates the use of open data from Wikipedia, DBpedia, Wikimedia Commons, and OpenStreetMap to automatically generate adventure games with complete plots, characters, items, and locations. His scientific contributions have been recognized with several awards including Best Paper Awards at major conferences, Best Reviewer Award, and Runner-Up Best Student Paper Award. Dr. Liapis has also co-organized 16 workshops in diverse conferences throughout his career. Research interests include: Artificial Intelligence for creative applications Procedural Content Generation in games Computational Creativity systems Machine Learning for game design Affective Computing in virtual environments Human-AI collaboration in creative processes His recent work shows a strong trend toward integrating Large Language Models with game design, exploring quality diversity algorithms for creative applications, and advancing affect modeling for improved player experience. The research spans computer science, artificial intelligence, game studies, and human-computer interaction, with practical applications in education, entertainment, and design.