جست‌وجوی استاد و پژوهشگر

Zhong-Ping Jiangمشاهده پروفایل

استاد

• Nonlinear Control Theory
• Dynamical Networks
• Data-Driven Optimization
• +۷ مورد دیگر

Dr. Zhong-Ping Jiang is a Professor in the Department of Electrical and Computer Engineering and an Affiliate Professor in the Department of Civil and Urban Engineering at the Tandon School of Engineering, New York University. He has been with NYU since 2007, previously serving as Associate Professor (2002-2007) and Assistant Professor (1999-2002) at Polytechnic University (now part of NYU). Dr. Jiang received his MSc degree in Statistics from the University of Paris XI in 1989 and his PhD degree in Automatic Control and Mathematics from the Ecole des Mines de Paris in 1993. He has maintained strong international collaborations with researchers across Europe throughout his career. Internationally recognized as a key contributor to nonlinear small-gain theory, Dr. Jiang is also well-known for his seminal work in robust adaptive dynamic programming and robust reinforcement learning for real-time safety-critical control applications. His research spans dynamical networks, nonlinear control theory, data-driven optimization, and reinforcement learning with applications to mechanical, information and biological systems. Dr. Jiang's publications have had significant impact in the field, with over 500 peer-reviewed journal and conference papers, more than 34,300 citations, and an h-index of 90 on Google Scholar. He has also published six research monographs since 2011. His notable awards and honors include: Election to European Academy of Sciences and Arts (2023) Stanford's Top 2% Most Highly Cited Scientists (2023) Election to Academia Europaea (2021) Highly Cited Researchers by Clarivate Analytics (2018) Fellow of Chinese Association of Automation (2017) Fellow of International Federation of Automatic Control (2013) Fellow of IEEE (2008) National Distinguished Professor, Chinese Ministry of Education (2009) Dr. Jiang serves as Deputy Editor-in-Chief for the IEEE/CAA Journal of Automatica Sinica and has held editorial positions for numerous prestigious journals including IEEE Transactions on Automatic Control. He has delivered more than 20 plenary, semi-plenary and keynote speeches at major international conferences and workshops.

Simon Haller-Seeberمشاهده پروفایل

مدرس

• Free Software
• System Automation
• Educational Robotics
• +۴ مورد دیگر

Simon Haller-Seeber is a Systems Engineer at the Department of Computer Science (Intelligent and Interactive Systems) at the University of Innsbruck, a role he has held since 2010. He also serves as a part-time Lecturer in Scientific Computing and Science Education. His academic background includes a Master's degree in Computer Science (2024) and a Bachelor's degree (2006), alongside professional certifications like Engineer Degree (2012) and Apprentice Instructor (2014). Research & Education: Focused on Free Software, System Automation, and Educational Robotics. He co-founded the STAIR-Lab and contributed to initiatives like ROSSINI workshops promoting youth robotics innovation. His work bridges robotics with pedagogy, emphasizing open-source tools and accessible education platforms. Publications: Recent works include web-based robotics IDEs (2025), AI-driven training frameworks (2023), and taxonomies for robotics action models (2019). His 2020 paper on recycling automation won the ROBOVIS Best Paper Award. Grants & Projects: Led EU-funded projects like IMAGINE (2018–2021) and participated in Squirrel/PaCMan (2014–2018). Co-organizes RoboCup Junior and the Computer Camp Malbun. Awards & Roles: Recognized for educational robotics contributions. Active in academic governance as former Senate member and board chair of 'brainity' and 'Natur Mensch Technik' associations.

Samuele Tosattoمشاهده پروفایل

استادیار

• Reinforcement Learning
• Robotics
• Machine Learning
• +۶ مورد دیگر

Samuele Tosatto is an Assistant Professor in the Computer Science Department at the University of Innsbruck and affiliated with the Digital Science Center. His research focuses on enabling robots to learn in real-world environments through reinforcement learning and abstraction techniques, addressing challenges in scalability and efficiency. Ph.D. in Computer Science from Technical University of Darmstadt (2020) M.Sc. and B.Sc. in Software Engineering from Polytechnic University of Milan His work emphasizes theoretical aspects of reinforcement learning, particularly policy gradient estimation and temporal-difference methods. Recent publications highlight innovations in data-driven teleoperation, movement primitives, and off-policy optimization, aligning with his goal of bridging simulation-to-reality gaps. He teaches courses including Introduction to Robotics, Optimization and Numerical Computation, Machine Learning, and Data Analysis II. His research is disseminated via platforms like Google Scholar and samueletosatto.com.

Nikolaus Feithمشاهده پروفایل

پژوهشگر

• Machine Learning
• Interactive Machine Learning
• Model-Free Reinforcement Learning
• +۶ مورد دیگر

Nikolaus Feith is a Doctoral Student at the Chair for CPS at Montanuniversität Leoben, supervised by Univ.-Prof. Dr. Elmar Rueckert since July 2022. He holds a Master’s degree in Mining Mechanical Engineering from the same university, completed in June 2022. His research focuses on integrating human expertise into robotic systems through Interactive Machine Learning. Education: Master’s degree in Mining Mechanical Engineering, Montanuniversität Leoben (June 2022) Research Interests: Machine Learning (Interactive Machine Learning, Model-Free Reinforcement Learning), Robot Learning, Optimization (Bayesian Optimization, CMA-ES), Human-Robot Interfaces, Augmented Reality, Embedded Systems in Robotics, and Cyber Physical Systems. Publications (2024): Explores topics like Bayesian Optimization frameworks for human expertise integration and mixed reality interfaces for robot learning, contributing to robotics and interactive learning systems. Teaching & Supervision: Course: 170.031 Programming in Python (WS23) Thesis Supervision: B.Sc. Christoph Andres: ROS2 Interface for FANUC CRX-10iA M.Sc. Christopher Martin Shimmin: Bayesian Optimization for Motorcycle ECU Parameters B.Sc. Marco Schwarz: Generic ROS2 Device Interface (Micro-ROS on ESP32) Awards: None listed. Labs/Teams: Part of the CPS research group, focusing on Cyber Physical Systems and robotics applications.

• Complex Systems
• Network Theory
• Financial Networks
• +۲ مورد دیگر

Guido Caldarelli is a Full Professor of Theoretical Physics at Ca' Foscari University of Venice , with affiliations at CNR-ISC, IMT Lucca, and the London Institute for Mathematical Sciences (LIMS). His career spans roles including President of the Complex Systems Society (2018-2020), co-founder of the Network Science Society, and director of CNR-ISC. Active in interdisciplinary research, he bridges statistical physics, network science, and applications in finance, urban planning, and biomedicine. PhD in Condensed Matter Physics, SISSA Trieste (1996) MPhil in Physics, SISSA (1994) Physics Degree, Sapienza Rome (1992) Guido's research focuses on complex systems and network theory , particularly in financial networks, urban dynamics, and biological systems. His work explores scale-free networks, systemic risk, and entropy-based models, with applications in digital twins for cities, microbiome analysis, and misinformation spread on social media. Recent publications highlight trends in network analysis for urban planning (green infrastructure), machine learning in NMR spectroscopy, and social media dynamics during political events. His interdisciplinary approach connects theoretical physics to practical challenges in healthcare, finance, and climate resilience. Scientific Awards Honorary ISI Fellow APS Fellow (2020) Member of Academia Europaea (2020) Fellow of the Network Science Society Outstanding Service Prize, Network Science Society (2020) Guido leads the Complex Networks group at CNR-ISC, co-founded Catchy s.r.l. (data-driven innovation), and serves on the Scientific Committee for Italian Police Force training . His work integrates theoretical rigor with real-world impact across disciplines.

Erwan Renaudoمشاهده پروفایل

پژوهشگر ارشد

• Autonomous robotics
• Machine Learning for robotics
• Action to behaviour processes in robotics

Erwan Renaudo served as a Postdoctoral Researcher at the Department of Computer Science, Intelligent and Interactive Systems, University of Innsbruck from 2017 to 2024, following prior postdoctoral and doctoral work at Institut des Systèmes Intelligents et de Robotique, University Pierre et Marie Curie. His academic credentials include: PhD in Computer Science and Robotics from Université Pierre et Marie Curie (2016) MSc in Artificial Intelligence and Robotics from Université de Cergy Pontoise (2012) MSc in Electronics Engineering from École Nationale Supérieure d'Électronique et de ses Applications (2011) Renaudo's research centers on Autonomous robotics , Machine Learning for robotics , and Action to behaviour processes in robotics , with emphasis on neuro-inspired architectures that bridge cognitive science and robotic adaptation. His work develops flexible learning frameworks where robots transition between goal-directed and habitual behaviors, enhancing real-world applicability in dynamic environments. Analysis of his 2020-2025 publications reveals dominant trends in reinforcement learning optimization for robotics, particularly in e-waste recycling automation and human-robot interaction. Key contributions include computational cost reduction through hybrid model-based/model-free architectures, exploration strategy innovations in deep reinforcement learning, and visual intelligence systems for robotic disassembly. His research consistently integrates multi-strategy learning to handle real-world variability in human rewards and environmental constraints. No scientific awards were documented in available sources. Renaudo actively supervises Bachelor's and Master's thesis projects through the University of Innsbruck's Intelligent and Interactive Systems group. His research is supported by significant projects: Current: ELSA (ANR-FWF Joint project 2022-2026) Past: IMAGINE (EU Horizon 2020, 2017-2021) Past: RoboErgoSum (ANR-12-CORD-30) He maintains active involvement with the Intelligent and Interactive Systems research group at the University of Innsbruck and previously collaborated with the AMAC team at ISIR in Paris, with recent participation in RoboCup competitions (2021-2023) demonstrating practical implementations of his research.