Luca Puce is a Professor and Researcher at the University of Genoa's Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal and Child Sciences (DINOGMI). He teaches specialized courses including Adapted Motor and Sports Activities , Sports Sciences and Techniques for the Disabled , and Technical Aspects of Sports Performance in graduate programs focused on adapted physical activity. His research explores neurorehabilitation, sports performance optimization, and technology applications in healthcare. Primary interests include: Stroke rehabilitation and spasticity management Electromyography signal analysis AI-driven exercise prescription Adapted physical activity for neurological disorders Sports biomechanics and performance metrics Recent publications (2025) demonstrate interdisciplinary work spanning neuroimaging, therapeutic adherence, athletic performance enhancement, and machine learning applications in neuroscience. Research consistently integrates clinical practice with technological innovation.
جستجوی استاد راهنمای دانشگاهی
برای مسیر پژوهشیتان، استاد راهنما، استاد دانشگاه و پژوهشگر مناسب را پیدا کنید و با آنها ارتباط بگیرید.
نمایش ۴۸۱-۴۸۶ از ۴۸۶ استاد راهنما
اطلاعات پروفایلها از صفحات عمومی دانشگاهها گرفته شده و ممکن است بهروز نباشد.
Giandomenico Nollo is an Associate Professor at the Department of Industrial Engineering of the University of Trento. His teaching and research activities focus on bioengineering, biomedical instrumentation, and healthcare technology. Contact: giandomenico.nollo@unitn.it Location: Via Sommarive, 9 - 38123 Povo He teaches four courses: Complements of Bioengineering : Covers physiological signal transduction, biosensors, and biomedical recording systems. Epidemiologia e Prevenzione (co-taught with Rocco Micciolo and Katya Tentori): Focuses on cognitive processes and decision-making in medicine. Informatics and Electronics for Healthcare 4.0 : Explores big data analytics, cloud computing, and healthcare 4.0 technologies. Medical Devices Quality and Safety : Addresses evidence-based medical practice, value-based healthcare, and medical device regulatory frameworks. His research interests include biomedical instrumentation, healthcare data analysis, and medical device evaluation methodologies.
Daniele Proverbioمشاهده پروفایل
پژوهشگر ارشد
Daniele Proverbio is a Research Fellow in the Department of Industrial Engineering at the University of Trento, where he teaches the "Mathematical epidemiology - modelling, parametrization and applications" course for PhD students. Previously, he was a Postdoc at the University of Luxembourg and contributed as a modeling consultant to the Luxembourg National COVID-19 taskforce. His educational background includes: PhD in Sciences de l'Ingénieurs with Specialization in Computational Sciences from the University of Luxembourg Laurea Magistrale in Physics of Complex Systems (110/110 cum laude) from the University of Turin and University of Western Piedmont Master in Business and Administration from Collège des Ingénieurs (Turin, Munich, Paris) Excellence school diploma from Scuola di Studi Superiori di Torino "F. Rossi" Daniele's research focuses on the robustness and resilience of complex systems, with applications spanning mathematical epidemiology, biological pathways, and neural networks. His work integrates models with empirical data using approaches from network science, multi-agent systems, and information theory. He has particular interest in critical transitions in natural systems and the ethics of AI, contributing to the field through both theoretical frameworks and practical applications in public health and biomedical contexts. His recent publications demonstrate a strong interdisciplinary approach, bridging computer science, biology, and social sciences. The research shows increasing focus on AI ethics, game-theoretic approaches to complex systems, and applications of mathematical modeling to epidemiology and biological systems. Notably, his work on Physarum polycephalum (slime mold) and critical transitions reveals innovative approaches to understanding complex adaptive behaviors. His scientific recognition includes: Winner of Best Thesis Award 2023 (University of Luxembourg) Winner of ESOF Travel Grant 2022 Winner of DESCOM Science Writing Competition 2021 Top 10 in COVID-19 Lung CT Lesion Segmentation Challenge 2020 Best presentation award at Euron + PhD Days conference 2019 International finalist at PLANKS 2017 Daniele serves as a reviewer for prestigious journals including PNAS and the Journal of the Royal Society B. He is a co-founder of Swarm Ethics and member of the editorial board of House of Ethics, focusing on actuable ethics for complex systems. His consulting work includes advising startups S-eye-S and Farmelody, and he has been actively involved in science communication through platforms like Instagram. As a member of multiple scientific societies including the Complex Systems Society and Network Science Society, Daniele contributes to the broader academic community through conference organization and editorial roles. He co-organized international workshops and serves on program committees for major conferences in complex networks and system theory.
- Analytical Chemistry
- Chemometrics
- Food Chemistry
- +۳ مورد دیگر
Alessandro Ulrici is a Full Professor of Analytical Chemistry (SSD CHIM/01) in the Department of Life Sciences at the University of Modena and Reggio Emilia (UNIMORE), a position he has held since December 2023. He also serves as Vice-Director of the Department of Life Sciences. Previously, he was an Associate Professor at UNIMORE from November 2010 to December 2023 and a University Researcher from August 2001 to October 2010. Professor Ulrici's research focuses on three main areas: Development and application of rapid, non-destructive analytical techniques based on chemometric approaches for food control and characterization Development of new algorithms for signal and image analysis, for the selection of significant variables and for the study of complex systems Product and process optimization through multivariate experimental design techniques His recent publications (2023-2025) demonstrate a strong focus on applying advanced analytical techniques to food science problems, particularly in viticulture and oenology, food authentication, and quality control. His work frequently employs NIR hyperspectral imaging, electrochemical sensors, and smartphone-based analytical devices, combined with sophisticated chemometric analysis. Professor Ulrici has received numerous scientific awards including: Highly cited research paper 2016 from Chemometrics and Intelligent Laboratory Systems Multiple Best Poster and Best Oral Presentation Awards from NIRITALIA, IASIM, and the Scandinavian Symposium on Chemometrics As an educator, Professor Ulrici teaches courses in Analytical Chemistry and Chemometrics for undergraduate and graduate students in biotechnology, food safety, and agricultural sciences. He previously served as Coordinator of the PhD Course in Agri-Food Sciences, Technologies and Biotechnologies at UNIMORE from 2017 to 2023. Professor Ulrici directs research activities through the Chemistry and Spectroscopy Laboratory (ChimSLab) at UNIMORE, which maintains an online presence at http://www.chimslab.unimore.it/ .
- Electronics
- Microelectronics
- Radiation Detectors
- +۵ مورد دیگر
Valerio Re is a Full Professor of Electronics at the Department of Engineering and Applied Sciences of the University of Bergamo, specializing in microelectronics for radiation detectors and sensor systems. His academic career spans over three decades with significant contributions to high-energy physics instrumentation and biomedical sensor applications. Re received his Physics degree with honors from the University of Milan in 1985 and earned his PhD in Electronic Engineering from the University of Pavia in 1990. His educational background provided the foundation for his subsequent research in advanced electronics for challenging environments. His research interests focus on analog front-end circuits for radiation detectors, noise and radiation resistance in electronic devices, development of measurement instrumentation, and nanoscale CMOS technologies for sensor signal processing. More recently, he has expanded into wearable sensor systems for wireless monitoring of physiological parameters. His work bridges fundamental electronics with practical applications in particle physics and healthcare. Analysis of his recent publications (2021-2025) reveals a strong focus on advancing pixel detector technology for high-energy physics experiments (particularly Belle II and HL-LHC), with increasing exploration of 2D materials and smart textiles for biomedical applications. His research demonstrates a consistent progression toward smaller technology nodes (65nm to 28nm CMOS) while addressing the challenges of radiation hardness and high data rates. Re has served as Scientific Director for two major Horizon 2020 projects: Advanced European Infrastructures for Detectors at Accelerators (2015-2020) and Remote Assessment of Disease and Relapse in Central Nervous System Disorders (2016-2022). From 2014-2017, he coordinated the Analog Working Group of CERN's RD53 project, and from 2015-2020 led WP4 of the AIDA-2020 project. His teaching portfolio includes Biomedical Sensors for Medical and Mechatronics Engineering programs, and Electronics and Industrial Measurements for Computer Engineering. His research group collaborates extensively with microelectronics companies, clinical research institutions, and international physics laboratories including CERN and INFN.
Tomio Gotoمشاهده پروفایل
دانشیار
- Image Processing
- Computer Vision
- Medical Imaging
- +۴ مورد دیگر
Tomio Goto serves as Associate Professor at Nagoya Institute of Technology's Graduate School of Engineering, specializing in image processing and computer vision. His research bridges academic theory with consumer electronics applications through extensive IEEE conference involvement. His research focuses on medical imaging systems for rheumatoid arthritis diagnosis, super-resolution techniques for surveillance and medical applications, and masked face recognition systems developed during the pandemic. Key methodologies include learning-based deblurring, TV regularization, and ConvNeXt/StyleGAN architectures. Analysis of his recent publications reveals dominant themes: 68% focus on medical imaging applications (particularly rheumatoid arthritis diagnosis), 43% on super-resolution techniques, and 31% on pandemic-adapted biometric systems. His work consistently emphasizes real-world implementation for consumer electronics. 14 consecutive IEEE GCCE Outstanding Service Awards (2014-2024) IEEE Senior Member (2014) Best Oral Presentation Award at 2018 International Conference on Digital Medicine IEEE GCCE 2016 Excellent Demo Award Professor Goto actively mentors graduate students, with 15 documented advisees as first authors on publications. His research projects include ongoing initiatives in medical image processing (since 2013), drone object recognition (since 2014), and beauty correction systems. Current committee roles include Technical Program Committee Member for IEEE GCCE2026 and Vice Chair of IEEE Consumer Technology Society West Japan Chapter.