جست‌وجوی استاد و پژوهشگر

Philippe Moireauمشاهده پروفایل

استاد

• Inverse Problems
• Data Assimilation
• Partial Differential Equations
• +۴ مورد دیگر

Philippe Moireau is a Full Professor in the Department of Applied Mathematics at École Polytechnique, where he is also affiliated with the Center for Applied Mathematics (CMAP). He serves as the head of the Inria Project-Team MΞDISIM (Mathematical and Mechanical Modeling with Data Interaction for Simulation in Medicine) and holds the distinguished position of Ingénieur Général of The Corps des Mines. His primary research focuses on inverse problems and data assimilation for partial differential equation models, with particular emphasis on: Observer-based methods from optimal control perspectives Stabilization approaches for evolution equations Numerical analysis of time-dependent control problems Digital twin applications in cardiovascular medicine Professor Moireau's publication portfolio demonstrates consistent focus on mathematical methods for physical systems, with recurring themes in: Data assimilation techniques for PDE-based models Numerical stabilization and discretization methods Cardiovascular biomechanics and hemodynamics Stochastic modeling of biological systems Epidemiological forecasting and control He leads the ANANKΞ project-team at Inria focused on Analysis And Numerics of physical-Knowledge-based Estimation. His educational contributions include lectures on data assimilation theory at CEMRACS and courses on mathematical modeling in cardiac biomechanics at Institut Polytechnique de Paris.

• Soil Biogeochemistry
• Carbon Cycling
• Mineral-Soil Interactions
• +۳ مورد دیگر

Dr. Marion Schrumpf is a Group Leader in the Soil Biogeochemistry research group at the Max Planck Institute for Biogeochemistry, affiliated with the Department of Biogeochemical Processes. Her work focuses on soil carbon dynamics, mineral-organic matter interactions, and climate change impacts on soil systems. Research areas: Soil biogeochemistry, carbon cycling, mineral-soil interactions, nutrient stoichiometry, microbial ecology, and climate modeling. Email: mschrumpf@... Phone: +49 3641 57-6182 Office: B2.015 Her recent publications address themes like mineral control over soil carbon stabilization, drought effects on soil processes, microbial stoichiometric adaptation, and the Jena Soil Model's role in simulating carbon-nutrient interactions. She leads efforts to disentangle the complex relationships between land use, mineralogy, and soil organic matter turnover across diverse ecosystems.

• Control Theory
• Optimization
• Machine Learning
• +۹ مورد دیگر

Andrea Iannelli is a Tenure-Track Assistant Professor at the Institute for Systems Theory and Automatic Control (IST) , University of Stuttgart, Germany. He also serves as a faculty member of the International Max Planck Research School for Intelligent Systems (IMPRS-IS) and participates in the Cluster of Excellence Data-Integrated Simulation Science (SimTech) . His research focuses on reconciling model-based and data-driven approaches for robust and adaptive control of uncertain dynamical systems. Ph.D. : Control and Dynamical Systems, University of Bristol (UK), 2019 Postdoctoral Researcher : ETH Zürich (Switzerland), 2019–2022 Harnessing the intersection of control theory, optimization, and machine learning , Iannelli’s work addresses data-driven modeling, uncertainty quantification, and robust control with applications in energy systems, intelligent transportation, and industry 4.0 . His recent publications highlight trends in LPV frameworks, online convex optimization, and hybrid control systems , emphasizing safety and efficiency. He contributes to the academic community as an Associate Editor for the International Journal of Robust and Nonlinear Control and as a member of international conference IPCs. His group, Trustworthy Autonomy for Smart Adaptive Systems (TASAS) , mentors PhD students in projects spanning adaptive control, uncertainty quantification, and reinforcement learning .

• Radiomics
• Medical Imaging Analysis
• Machine Learning in Healthcare
• +۷ مورد دیگر

Adrien Depeursinge is a Professor at HES-SO Valais-Wallis - Haute Ecole de Gestion, affiliated with the School of Economics and Services and the Management Information Systems department. His research focuses on radiomics, personalized medicine via image-based analysis, and clinical workflow optimization. He leads the development of the QuantImage platform, a physician-centered web-based tool for radiomics research, and contributes to radiomics standardization efforts through initiatives like the Image Biomarker Standardization Initiative (IBSI). His work emphasizes machine learning applications in healthcare, including tumor segmentation, biomarker extraction, and improving diagnostic accuracy through computational models. Key research themes include: 1) Radiomics – developing quantitative imaging features for cancer diagnosis/prognosis; 2) Medical Imaging Analysis – advancing texture-based models, multi-modal fusion, and automated lesion detection; 3) Physician-AI Collaboration – designing user-centric tools for clinical integration. His contributions span neuro-oncology (brain metastases), head-and-neck cancer, and multiple sclerosis imaging. Publications emphasize methodological advancements (e.g., kernel optimization in CNNs, steerable detectors) and clinical validation (e.g., reproducibility of radiomics features across imaging protocols). He collaborates with institutions like the University Hospital of Lausanne (CHUV) and international teams on projects like the HECKTOR challenge for PET/CT tumor segmentation. His work bridges technical innovation with clinical impact, aiming to translate radiomics into actionable clinical tools. QuantImage v2, his flagship tool, enables no-code development of machine learning models using clinical imaging data. Research also includes phantom-based validation of radiomics features and addressing challenges in feature stability across imaging modalities. Current projects explore improving contour quality for radiomics studies and optimizing AI explainability in medical decision-making.

Ayhan Günمشاهده پروفایل

دانشیار

• Control Systems
• Mathematical Modeling in Electrical Engineering
• Artificial Neural Networks
• +۱۲ مورد دیگر

Assoc. Prof. Dr. Ayhan Gün is an Associate Professor in the Department of Electrical and Electronics Engineering at Kütahya Dumlupınar University's Faculty of Engineering. With a career spanning over two decades, he has held various academic positions including Research Assistant, Assistant Professor, and currently Associate Professor since 2024. His extensive administrative experience includes serving as Head of the Control and Command Systems Department (2007-2021) and various leadership roles in university-industry collaboration initiatives. Dr. Gün completed his Bachelor's degree at Near East University (1991-1996), Master's at Dumlupınar University (1998-2001), and PhD at Eskişehir Osmangazi University (2001-2007). His research focuses on control systems, mathematical modeling, artificial neural networks, robotics, SCADA, PLC programming, electromechanical systems, nonlinear control, fuzzy logic, optimization techniques, automation, biomechanics, and mechatronics. His recent publications demonstrate a consistent research trajectory in control engineering, with particular emphasis on optimization algorithms applied to quadrotor control, inverted pendulum systems, and electrical motor design. His work bridges theoretical control concepts with practical implementations in robotics and power systems. A significant portion of his research involves applying swarm intelligence and evolutionary algorithms to solve complex control problems. Bilim, Sanayi ve Teknoloji Bakanlığı Kurumsal Kapasitenin Arttırılması (2016) BİLİM SANAYİ VE TEKNOLOJİ BAKANLIĞI Çift Beslemeli İndüksiyon Generatörü Tasarımı ve İmalatı (2016) Dr. Gün has supervised multiple graduate students and managed numerous research projects, including the current 'Robotic Arm Design and Implementation for Patients with Hemiparetic Arms' project. His external roles include serving as an expert witness for judicial institutions, project referee for TÜBİTAK, and publication reviewer for IEEE Transactions. He has also contributed to regional development through his work with Kütahya Governorship's Planning and Development Board.

Murat Arcakمشاهده پروفایل

استاد

• Control Theory
• Autonomous Systems
• Multi-Agent Systems
• +۵ مورد دیگر

Murat Arcak is a Professor of Electrical Engineering and Computer Sciences and Mechanical Engineering at the University of California, Berkeley, holding the Robert M. Saunders Endowed Chair in the College of Engineering. His research spans control theory, autonomous systems, and multi-agent systems with applications in transportation, energy, and biology. Dr. Arcak received his Ph.D. in Electrical Engineering from the University of California, Santa Barbara in 2000, following an M.S. from the same institution in 1997 and a B.S. from Bogazici University in Istanbul, Turkey in 1996. His research interests focus on developing scalable control design and verification methods for complex systems with many interconnected components, nonlinear dynamics, and learning capabilities. He has made significant contributions to control theory, particularly in areas like reachability analysis, dissipative systems, and compositional verification methods. His work bridges theoretical advances with practical applications in transportation systems, energy networks, and biological systems. A leading researcher in control systems, Dr. Arcak's recent publications demonstrate a strong focus on data-driven approaches for system verification, synthetic biology applications, and formal methods for traffic control. His research combines mathematical rigor with practical implementation, often developing novel theoretical frameworks that address real-world engineering challenges. CAREER Award from the National Science Foundation (2003) Donald P. Eckman Award from the American Automatic Control Council (2006) Control and Systems Theory Prize from SIAM (2007) Antonio Ruberti Young Researcher Prize from IEEE Control Systems Society (2014) Brockett-Willems Outstanding Paper Award (2021) IFAC Fellow (2020) IFAC Automatica Paper Prize (2020) CSS Transactions on Control of Network Systems Outstanding Paper Award (2017) Electrical Engineering Award for Outstanding Teaching (2014) CSS Antonio Ruberti Young Researcher Prize (2014) IEEE Fellow (2012) SIAM Activity Group Control and Systems Theory Prize (2007) Dr. Arcak has advised numerous graduate students and postdoctoral researchers, though specific names are not listed in the available information. His research has been supported by various grants from the National Science Foundation and other funding agencies, enabling his work on control theory and applications across multiple domains. He is affiliated with several research centers at UC Berkeley including the Berkeley Artificial Intelligence Research Lab (BAIR), Berkeley Deep Drive (BDD), the Center for the Theoretical Foundations of Learning, Inference, Information, Intelligence, Mathematics and Microeconomics at Berkeley (CLIMB), the Institute of Transportation Studies (ITS), and Partners for Advanced Transit and Highways (PATH).

Mattias Brunströmمشاهده پروفایل

استادیار

• Cardiovascular Disease
• Hypertension
• Aortic Diseases
• +۳ مورد دیگر

Mattias Brunström serves as Assistant Professor of Cardiology and Associate Professor of Epidemiology at Umeå University's Faculty of Medicine within the Department of Public Health and Clinical Medicine, Section of Cardiology. He is concurrently a resident physician at Norrlands University Hospital and holds leadership roles as chairman of Sweden's national hypertension working group and scientific secretary of the Swedish Society for Hypertension, Stroke and Vascular Medicine, with active participation in the European and International Societies of Hypertension. His academic foundation includes a 2018 PhD thesis examining blood pressure-lowering treatment effects across different blood pressure levels through systematic reviews and meta-analyses of randomized clinical trials. This doctoral work established his expertise in evidence-based cardiovascular therapeutics and epidemiological methodology. Dr. Brunström's research program centers on cardiovascular disease risk factors, with specialized focus on hypertension pathophysiology and aortic diseases. His group investigates how adolescent blood pressure levels predict future cardiovascular events, examining interactions with obesity, physical fitness, and diabetes to improve risk stratification. They also analyze differential effects of antihypertensive drug classes on cardiovascular outcomes and study risk factors for aortic dissection/rupture to optimize preventive surgical interventions. This work addresses critical gaps in managing the world's leading cause of death, where uncontrolled hypertension contributes to 10 million annual fatalities despite effective treatments. Analysis of his 2024-2025 publications reveals dominant themes in hypertension guideline development, treatment threshold controversies, and cardiovascular risk assessment. His work frequently challenges conventional approaches (e.g., questioning excessive treatment of 'elevated' blood pressure in elderly patients) while advancing evidence for lifestyle interventions and beta-blocker utility. Methodologically, his research leverages large cohort studies (including 1.4 million enlistee data), systematic reviews, and international collaborations through societies like ESH and ISH to translate epidemiological findings into clinical practice. Dr. Brunström leads multiple funded research initiatives including 'Remission of type 2 diabetes through eHealth' (2022-2028) and 'VIPviza' (2013-2027), directing a multidisciplinary team that bridges clinical cardiology, epidemiology, and public health. His advisory role extends to national guideline committees and international hypertension societies where he shapes clinical practice through evidence synthesis and position papers. Based at Norrlands University Hospital's Cardiology Section, his research group operates within Umeå University's strong cardiovascular research ecosystem, maintaining active collaborations with the Swedish National Diabetes Register and international consortia. Their work emphasizes real-world applicability, examining topics like bedtime dosing of antihypertensives and self-report diagnostic tools to overcome barriers in hypertension control where only 25% of affected individuals achieve target blood pressure levels.

Scott L. Nyklمشاهده پروفایل

استاد

• Computer Vision
• Real Time 3D Computer Graphics
• Sensor Fusion
• +۱۲ مورد دیگر

Dr. Scott L. Nykl is a Professor in the Department of Computer Science at the Air Force Institute of Technology (AFIT), part of the Graduate School of Engineering & Management. He is a leading researcher in computer vision, real-time 3D graphics, and autonomous aerial systems, with a focus on automated aerial refueling and navigation in GPS-denied environments. Education: Ph.D. in Computer Science, Ohio University (2008–2013), Summa Cum Laude, GPA: 4.0/4.0 M.S. in Computer Science, Ohio University (2011–2012), Summa Cum Laude, GPA: 4.0/4.0 B.S. in Software Engineering, University of Wisconsin–Platteville (2002–2006), Summa Cum Laude, GPA: 3.94/4.0 Dr. Nykl's research interests include computer vision, sensor fusion, interactive virtual worlds, and real-time 3D graphics, with applications in aerospace and defense. His work bridges simulation and real-world deployment, particularly in autonomous aerial refueling using stereo and monocular vision. He has pioneered techniques in pose estimation, occlusion mitigation, and sim-to-real transfer learning. His recent publications and projects show a strong trend toward robust, vision-based navigation systems for unmanned and manned aircraft, with emphasis on reliability, accuracy, and real-time performance. His work frequently appears in IEEE, AIAA, and ION venues, reflecting its high technical and operational relevance. Scientific Awards and Recognitions: 2024 Harold Brown Award – Highest U.S. Air Force scientific honor 2024 General Bernard A. Schreiver Award 2025 AETC Airmen of the Year Multiple Air Force Outstanding Scientist/Engineer Awards (2017–2023) Best Paper Award, ACM SIGGRAPH i3D 2013 Forbes' The Greatest Young Inventors in America (2012) NSF GK-12 Fellow (2006) Dr. Nykl has advised numerous graduate students and collaborated extensively on projects involving automated aerial refueling, 3D reconstruction, and cyber education. He has secured significant research funding, including a $100,000 Ohio Third Frontier grant. His work has led to multiple patents and technology transfers. He leads research integrating virtual worlds, digital twins, and augmented reality for both research and pedagogy. Laboratories and Research Teams: His work is conducted within AFIT’s research ecosystem, involving collaborations with the Air Force Research Laboratory (AFRL), Boeing, and academic partners. He leads projects under the Aerial Refueling Systems Advisory Group (ARSAG) and presents regularly at ION, AIAA, and IEEE conferences.

• Sleep Disorders
• Obstructive Sleep Apnea
• Digital Health
• +۷ مورد دیگر

Dr Bastien Lechat is a Research Fellow at Flinders Health and Medical Research Institute (FHMRI): Sleep Health, within the College of Medicine and Public Health at Flinders University. He is also a Full Member of the College of Science and Engineering and the Medical Device Research Institute. As an NHMRC Emerging Leadership Fellow, he leads innovative research at the intersection of sleep medicine, artificial intelligence, and wearable technology. Education: PhD in Sleep Health, Adelaide Institute for Sleep Health, Flinders University (2018–2021) Bachelor of Engineering in Engineering Science/Acoustics, Université du Maine, France (2014–2017) Dr Lechat’s research focuses on understanding the physiological mechanisms and consequences of obstructive sleep apnea (OSA), particularly night-to-night variability and patient subtypes. He develops AI-driven tools for efficient and accurate diagnosis using wearables and signal processing. His work aims to create a scalable, low-cost model of care for sleep-disordered breathing, addressing global diagnostic gaps. His recent publications reveal a strong trend in digital health innovation, with a focus on machine learning for OSA detection, circadian rhythm modeling, cardiovascular risk prediction, and climate impacts on sleep. His research has been published in top journals including Nature Communications , Journal of Sleep Research , and Sleep Medicine , demonstrating interdisciplinary reach. Scientific Awards and Recognition: NHMRC Emerging Leadership Fellow (2023) Helen Bearpark Memorial Scholarship (2022) Emerging Research Leader Award, Flinders University (2021) Multiple early-career awards from Sleep Down Under, Australasian Sleep Association, and Adelaide Sleep Retreat Ranked in the top 5% of international authors in sleep apnea by Expertscape Dr Lechat has secured over $2.5 million in competitive research funding and actively supervises and mentors junior researchers. He serves on the program committee of the American Thoracic Society meetings and contributes to clinical guidelines. He collaborates globally with industry and academic partners to translate research into clinical practice. Laboratories and Research Teams: He co-leads the 'Novel use of digital innovations & technology development' theme at FHMRI: Sleep Health, working closely with Professor Danny Eckert. His team integrates expertise in biomedical engineering, data science, and clinical sleep physiology to advance digital sleep medicine.

Vahid Jamaliمشاهده پروفایل

استادیار

• Resilient Communications
• Wireless Communications
• 6G Networks
• +۴ مورد دیگر

Prof. Vahid Jamali is an Assistant Professor and Head of the Resilient Communication Systems Group at the Technical University of Darmstadt, Germany. His research focuses on resilient communications, 6G wireless systems, bio-inspired molecular communication, and reconfigurable intelligent surfaces (RIS). He holds a Doctoral Degree from Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany, and has served as a postdoctoral researcher at Princeton University and FAU. Education PhD in Communication Systems, FAU (2019) Visiting Researcher at Stanford University (2017) Research Assistant at FAU's Institute for Digital Communications (2013-2019) Research Interests Resilient Networks : Emergency networks, RIS-based systems, and resilience-by-design architectures. Wireless Innovations : 6G technologies, holographic MIMO, and joint communication-sensing systems. Bio-inspired Systems : Molecular communication modeling using biological principles like diffusion and chemical reactions. Recent Work Trends His 2024-2025 publications emphasize RIS optimization (e.g., temperature-aware phase shifts, fast beam switching) and molecular communication (e.g., Poisson channel identification, bio-inspired receiver designs). Emerging themes include AoI-based RIS reconfiguration and integrated sensing-communication-powering (ISCAP) for IoT. Lab Activities He leads the Resilient Communication Systems Group, exploring cutting-edge RIS hardware (e.g., liquid crystal implementations) and theoretical foundations for future wireless systems.

Steffi Colyerمشاهده پروفایل

مدرس ارشد

• Biomechanics
• Sports Biomechanics
• Motion Analysis
• +۷ مورد دیگر

Steffi Colyer is a Senior Lecturer in Biomechanics at the Department for Health, University of Bath. She is affiliated with the Centre for Health and Injury and Illness Prevention in Sport and the Bath Institute for the Augmented Human. Her research is supported by major grants from EPSRC and ESA, focusing on elite athletic performance, rehabilitation, and motion analysis technologies. Her research interests center on biomechanics of athletic performance, particularly in sports such as skeleton, badminton, and sprinting. She investigates the kinetic and kinematic determinants of elite performance, develops markerless motion capture systems for real-world analysis, and applies musculoskeletal modelling to understand internal loading and adaptation in normal and simulated gravity environments. Her work bridges sports science, engineering, and rehabilitation. The recent trend in her publications shows a strong focus on markerless motion analysis, pose estimation, musculoskeletal modelling, and the biomechanics of sprinting and racket sports. She leverages advanced computational methods, including deep learning and in silico simulations, to improve performance analysis and injury prevention. Her scientific awards include: ISBS New Investigator Award finalist (oral) (co-author), 2022 Departmental Staff Award for Innovation in Learning and Teaching, 2025 She has supervised multiple research students and projects, including PhD and postdoctoral work, and is actively involved in peer review for journals such as Journal of Sports Sciences , Scientific Reports , and Journal of Biomechanics . She leads the IAA project on markerless motion capture for skeleton push-start analysis and contributes to the CAMERA initiative, a major interdisciplinary research center focused on motion analysis and virtual reality applications. Her research is conducted within the Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA), where she collaborates with computer scientists, engineers, and sports scientists to develop and apply cutting-edge motion capture technologies in real-world settings.

• Biomedical Signal Processing
• Electroencephalography (EEG)
• Mental Workload Assessment
• +۱۲ مورد دیگر

Tarmo Lipping is a Professor in the Department of Computer Science and Engineering at the Faculty of Information Technology and Electrical Engineering, University of Oulu. His work bridges computing sciences with biomedical engineering, environmental modelling, and data-driven societal applications. Doctor of Science (Technology), Information Technology – Awarded 14 Feb 2001 Master of Science (Technology), Information Technology – Awarded 10 Sept 1993 His research focuses on electroencephalography (EEG) , mental workload assessment , depth of anesthesia monitoring , and machine learning applications in healthcare and human-computer interaction. He also contributes to environmental informatics , particularly in land uplift modelling and radionuclide transport , aligning with UN Sustainable Development Goals. Recent publications highlight trends in transformer networks for EEG analysis , wearable HCI systems , data-driven food safety , and participatory municipal governance . His work integrates deep learning, signal processing, and real-world deployment. Scientific awards include: CIMO opettajavaihto (2017) Lipping has supervised numerous master’s students and served as an examiner in diverse topics including data vault modelling , telecom revenue estimation , and EEG hyperscanning . He has evaluated funding applications, acted as a journal reviewer (65 times), and contributed to editorial work. His activities reflect strong engagement in academic service and interdisciplinary research mentorship. He has contributed datasets on Fennoscandian land uplift , lake isolation , and archaeological shorelines to PANGAEA, supporting open science in geosciences and environmental history.

Terri S. Hogueمشاهده پروفایل

استاد

• Hydrology
• Water Resources Management
• Land Surface Processes
• +۹ مورد دیگر

Terri S. Hogue is a Professor in the Department of Civil and Environmental Engineering at the Colorado School of Mines, where she also serves as Dean of Earth and Society Programs and Director of the Center for a Sustainable WE 2 ST. Her work bridges engineering, hydrology, and environmental sustainability, with a strong focus on semi-arid regions. Education: PhD in Hydrology and Water Resources, University of Arizona, 2003 MS in Hydrology and Water Resources, University of Arizona, 1998 BS in Geology, University of Wisconsin-Eau Claire, 1995 Her research focuses on hydrologic and land surface processes, particularly in the context of water resource management, climate variability, urbanization, and natural hazards. She integrates field observations, remote sensing, and modeling to study catchment responses to wildfires, urban development, and climate change. Her work emphasizes improving hydrologic forecasts and understanding human-environment interactions in water-limited systems. The 15 most recent publications highlight consistent themes in hydrologic modeling, remote sensing applications, evapotranspiration estimation, post-wildfire hydrology, and urban water systems. Her research spans both observational and computational methods, with strong applications to real-world water management challenges in the western U.S. Scientific Awards and Honors: NSF Faculty Early Career Development (CAREER) Award, 2009 NSF Fellowship Trainee Award (multiple years) NASA Earth Observing System (EOS) Graduate Fellowship, 2001–2002 AMS Journal of Hydrometeorology Editor’s Award, 2011 UCLA Professor of the Year (2004, 2007, 2010) Appointment to National Academy of Sciences Board on Atmospheric Sciences and Climate, 2013 AMS Science and Policy Colloquium Fellowship, 2002 Multitude of scholarships and fellowships from NASA, NSF, and professional societies Dr. Hogue has been actively involved in advising and research leadership through her Hogue Research Group and the Center for a Sustainable WE 2 ST. She has secured significant grants, including the NSF CAREER Award, and contributes to national science policy through service on the AGU Hydrology Section and the National Academy of Sciences. Her work emphasizes interdisciplinary collaboration, data-driven modeling, and sustainable solutions for water-stressed regions. She leads the Hogue Research Group and the Center for a Sustainable WE 2 ST, both of which focus on integrated water, energy, and environmental systems. These teams bring together engineers, hydrologists, and environmental scientists to tackle pressing sustainability challenges through research, education, and policy engagement.

Burak Kurkcuمشاهده پروفایل

استادیار

• Robust Control
• Soft Robotics
• Switched Neural Networks
• +۳ مورد دیگر

Burak Kurkcu is an Assistant Professor in the Department of Electrical and Computer Engineering at Santa Clara University's School of Engineering. He previously served as an Assistant Professor at Hacettepe University and as a Senior Control System Design Engineer at Aselsan Inc. Education: Ph.D., TOBB University of Economics and Technology (2019) M.S., TOBB University of Economics and Technology (2015) B.S., Istanbul Technical University (2010) Research Interests: Dr. Kurkcu specializes in robust control systems, soft robotics, switched neural networks, and autonomous systems. His work focuses on disturbance estimation, simultaneous learning algorithms, and control of nonlinear systems. Recent Publication Trends: His research includes soft pneumatic actuator modeling, disturbance observer-based control methods, and evolutionary optimization for state-space models. Key themes involve soft robotics, autonomous control, and computational intelligence applications. Scientific Awards: IEEE Turkey Ph.D. Thesis Award (2020) Editorial Roles: Associate Editor for TIMC, Measurement and Control , and Turkish Journal of Electrical Engineering and Computer Science . Principal Investigator for defense-related control system projects.

Jeeseop Kimمشاهده پروفایل

استادیار

• Robotics
• Autonomy
• Control Theory
• +۳ مورد دیگر

Jeeseop Kim is an Assistant Professor in the Department of Aerospace and Mechanical Engineering at The University of Texas at El Paso (UTEP), College of Engineering, specializing in robotics, autonomy, and control theory. His research focuses on safety-critical planning and control, with emphasis on bipedal/quadrupedal locomotion, hybrid dynamical system control, and whole-body planning and control. Education: B.S. in Mechanical and Aerospace Engineering, Seoul National University (2014) M.S. in Intelligence and Information (Robotics), Seoul National University (2017) Ph.D. in Mechanical Engineering, Virginia Tech (2022) Postdoctoral Scholar, Mechanical and Civil Engineering, Caltech (2022–2025) His research spans safety-critical control systems for legged robots, including obstacle-aware nonlinear model predictive control (MPC), control barrier functions, and distributed coordination algorithms. Recent work explores adaptive delay estimation, tactile sensing for robotic grasping, and hardware-software co-design for humanoid robots. Key article trends highlight advancements in autonomous inspection robotics, hybrid control architectures, and real-time planning for quadrupedal systems. His work integrates control theory with practical applications in industrial and healthcare domains. Awards: ASME DSCD Rudolf Kalman Best Paper Award (2022) IEEE ICRA Outstanding Paper Award (2023) Jeeseop teaches MECH 4332: Mechanical Computational Applications in Vision and Robotics (Fall 2025). He actively recruits Ph.D. students for Spring/Fall 2026 and seeks motivated undergraduates/MS students with skills in robotics kinematics, programming (C/C++, Python, MATLAB), and CAD design. The AIGIS Lab welcomes applicants with interests in robotics, controls, and autonomous systems.