جستجوی استاد راهنمای دانشگاهی

Julie Dethier is a Research Fellow at the University of Liège, affiliated with the Faculty of Applied Sciences and Montefiore Institute. Her research bridges cellular neuroscience and network dynamics, with focus on pathological rhythms in Parkinson's disease and brain-machine interface development. She completed her Ph.D. in 2015 under Prof. Sepulchre's supervision. Her academic journey includes: Ph.D. in Systems and Modeling (2015), University of Liège with Princeton University research stay (2014-2015) Master of Science in Bioengineering (2011), Stanford University (Brains in Silicon lab) Master of Applied Sciences in Biomedical Engineering (2010, summa cum laude), University of Liège Bachelor of Applied Sciences (2008, summa cum laude), University of Liège Dr. Dethier investigates how cellular feedback mechanisms generate pathological beta oscillations in basal ganglia circuits, disrupting motor function in Parkinson's disease. Her computational approaches model the transition from unicellular rhythms to network-level oscillations, with implications for deep-brain stimulation therapies. She integrates electrophysiological data with dynamical systems theory to explain robustness and modulation in neural circuits. Her publication record demonstrates evolving expertise from brain-machine interface hardware (2011-2012) to fundamental neural mechanism studies (2013-2015). Key themes include spiking neural network decoders, cellular feedback loops, and pathological oscillation generation. Work spans computational modeling, neuromorphic engineering, and translational neuroscience with applications in neuroprosthetics. Major recognitions include: WBI excellence grant for Princeton research (2014) LEAR Foundation Fellowship for Cambridge research (2013) Audience Award at ULg thesis competition (2013) IEEE EMBS Best Poster Award (2011) Fulbright Honorary Fellowship and Rotary International Fellowship (2010) Funded by competitive F.R.S.-FNRS and international fellowships, her research involved cross-institutional collaboration with Princeton, Cambridge, and Stanford teams. While no formal advisees are listed, her publications reflect mentorship through co-supervised projects and conference presentations. Current work extends her doctoral thesis on multiscale neural dynamics. She maintains active ties with the Systems and Modeling Research Unit at Liège, Brains in Silicon lab at Stanford, and participates in Benelux neuroscience networks through the Montefiore Institute.

• Computational Neuroscience
• Neural Oscillations
• Brain-Machine Interfaces
• +۲ مورد دیگر

Pieter Simoens is an Assistant Professor at Ghent University and affiliated with the imec research institute. He works at the intersection of distributed artificial intelligence, edge computing, and collective intelligence, with a focus on AI applications for resource-constrained environments and robotic systems. His research explores innovative approaches to machine learning deployment in heterogeneous infrastructures, task planning for IoT-integrated robotics, and modeling collective decision-making processes. He has contributed to frameworks like DIANNE for distributed deep learning and developed methods for cognitive modeling in reinforcement learning scenarios. With over 100 publications, his recent work spans adaptive neural networks, privacy-preserving surveillance, UAV hyperspectral data analysis, and computational fairness in AI systems. He leads research initiatives within the Internet Technology and Data Science Lab (IDLab) and contributes to educational programs in software engineering and applied machine learning. Responsible for courses on software engineering, mobile development, system design, and applied machine learning Active in edge computing and neuromorphic algorithms research Develops AI solutions for robotics, surveillance, and industrial IoT applications

• Distributed Artificial Intelligence
• Edge Computing
• Algorithms for Neuromorphic Computing
• +۲ مورد دیگر

Dick Botteldooren is a full Professor of Acoustics at Ghent University, Belgium, leading the WAVES (Wireless, Acoustics, Environment & Expert Systems) research unit. He serves as I-INCE vice-president for Europe and Africa and previously held leadership roles as Editor-in-Chief of Acta Acustica (2004-2013) and president of the Belgian Acoustical Society (until 2018). His educational background includes: MSc in Electronic Engineering (1986, Ghent University) PhD in Applied Science (1990, Ghent University) Professor Botteldooren's research spans acoustic modeling, noise mapping, environmental sensor networks, computational intelligence, and human-inspired machine listening. His work integrates biomonitoring (particularly EEG), health impact assessment of sound, urban sound planning, and soundscape design with strong policy implications. Recent focus areas include AI-driven analysis of animal vocalizations and therapeutic soundscape design for dementia care. Analysis of his 2021-2025 publications reveals three dominant trends: (1) Machine learning applications in bioacoustics (especially broiler chicken vocalization monitoring for welfare assessment), (2) EEG-based attention detection systems using spiking neural networks and cross-modal transfer, and (3) Soundscape augmentation for dementia care through auditory processing-driven environmental interventions. His work consistently bridges computational methods with real-world acoustic challenges. His scientific recognition includes: Fellow of the Acoustical Society of America Professor Botteldooren has advised national and international health councils and noise policymakers, translating research into practice. His work has received sustained funding from the Belgian National Fund for Scientific Research and other international bodies, supporting both fundamental acoustics research and applied policy development. The WAVES research unit under his leadership conducts interdisciplinary work combining wireless sensor networks, computational intelligence, and human-centered acoustics, with active projects in urban noise monitoring, bioacoustic surveillance, and neuroacoustic applications.

• Acoustic Modeling
• Noise Mapping
• Environmental Sensor Networks
• +۸ مورد دیگر

Joni Dambre is a full-time tenured Professor at Ghent University leading the AIRO research group within the Internet Technology and Data Science Lab (IDLab). She transitioned from digital hardware research to machine learning in 2008 after earning her MSc and PhD in Electrical and Computer Science Engineering from Ghent University. Her educational background includes: MSc in Electrical Engineering from Ghent University PhD in Computer Science Engineering from Ghent University Professor Dambre's research spans machine learning, deep learning, embedded AI implementations, robotics, and brain-inspired unconventional computing. Her work uniquely bridges theoretical foundations with practical applications, evidenced by her team's competitive success in Kaggle competitions. Key thrusts include photonic reservoir computing, sign language technology development, and human-AI interaction studies, with emphasis on both hardware-efficient implementations and societal impacts. Recent publications (2023-2025) reveal strong interdisciplinary convergence, merging machine learning with photonics for unconventional computing architectures while advancing sign language translation through projects like SignON. A notable trend involves expanding from technical implementations to human-centric AI research, including studies on human alignment with large language models and societal implications of AI deployment. No major scientific awards were mentioned in the provided text. Although specific student names were not listed, Professor Dambre leads the AIRO group and serves as principal investigator for significant projects including SignON and cREAtIve, indicating active research supervision and substantial grant funding from both academic and industry sources. The AIRO research group maintains a dual focus on foundational theory and real-world applications, with active projects spanning photonic neural networks for telecommunications, sign language recognition systems, and robotics platforms. Their work demonstrates consistent innovation in translating brain-inspired computing concepts into practical solutions while maintaining strong industry partnerships and competitive performance in applied machine learning challenges.

• Machine Learning
• Deep Learning
• Embedded AI
• +۵ مورد دیگر

Alessio Franci is Lecturer in Electrical Engineering and Computer Science at the University of Liege, where he co-founded the ULiege Neuroengineering Lab. His research bridges mathematics, neuroscience and engineering through brain-inspired computing paradigms. Funded by a WEL-T Starting Grant, his work develops neuromorphic controllers and biomorphic systems for robotics and intelligent sensing. Research explores: neurocomputational principles of decision-making; neuromodulation in adaptive systems; and degenerate coding in neural circuits. Publications apply nonlinear dynamics to opinion formation, neural coding, and neuromorphic hardware design, demonstrating consistent innovation in theoretical frameworks. Honors include the WEL-T Starting Grant supporting his investigations into neuronal degeneracy and physiological mechanisms. Current work emphasizes real-world applications in robotics through spiking neural controllers and embodied neuromodulation strategies.

• Neuromorphic Engineering
• Computational Neuroscience
• Brain-Inspired Computing
• +۲ مورد دیگر