جستجوی استاد راهنمای دانشگاهی

Jianguo Wangمشاهده پروفایل

استاد

• Multisensor Integration
• GNSS Technology
• Precision Engineering Surveying
• +۵ مورد دیگر

Dr. Jianguo Wang is a Professor in the Department of Earth and Space Science Engineering at York University's Lassonde School of Engineering. He has been a faculty member since 2006 and is a founding member of the Lassonde School. With over 35 years of academic and industrial experience, he specializes in multisensor integration, GNSS technology, and precision engineering surveying. He holds a Dr.-Ing. in Geomatics Engineering from Universität der Bundeswehr München, Germany, alongside Bachelor’s and Master’s degrees from Wuhan Technical University of Surveying and Mapping (WTUSM). His research focuses on advanced data processing methodologies, including Kalman filtering, error analysis, and LiDAR systems. He has authored/co-authored over 60 publications, including textbooks like Error Theory and Foundation of Surveying Adjustment and Foundation of Geodesy . He is a Fellow of Engineers Canada and licensed as a Professional Engineer in Ontario. Education: Dr.-Ing., Geomatics Engineering, Universität der Bundeswehr München (Germany) M.Sc., Surveying Engineering, Wuhan Technical University of Surveying and Mapping B.Sc., Surveying Engineering, Wuhan Technical University of Surveying and Mapping Dr. Wang teaches courses such as Advanced Optimization and Applications , GNSS , and Global Geophysics and Geodesy . He leads the Earth Observation Laboratory (PSE 432), focusing on multisensor integration for navigation and positioning. His work explores innovative solutions for sensor calibration, data fusion, and geospatial applications. Grants & Labs: Active in lab-based research with collaborators like Baoxin Hu, his laboratory integrates GNSS, IMUs, LiDAR, and cameras for precision navigation. His recent work addresses challenges in sensor error calibration, LiDAR point cloud accuracy, and Kalman filter enhancements.

• Image Processing
• Computer Vision
• Remote Sensing
• +۴ مورد دیگر

Gabriele Facciolo is a Professor at the Centre Borelli, ENS Paris-Saclay, France. He is a Senior Member of the Institut Universitaire de France (IUF) and holds an Innovation Chair (2025). His research focuses on image and video processing, remote sensing, and super-resolution techniques. Current affiliations: Centre Borelli (ENS Paris-Saclay), Institut Universitaire de France His research explores advanced algorithms for satellite stereo pipelines, real-time deblurring, denoising, and explainable AI systems for legal evidence enhancement. He coordinates projects like ANR SURECAVI (Super-resolution for visible camera systems) and ANR IMPROVED (video enhancement for judicial use), with recent work on Gaussian Splatting for Earth Observation and multi-date satellite super-resolution. Notable scientific achievements include the IGARSS 2025 Top 10 Student Paper Award and leadership in projects funded by ANR (€890k) and Prime Minister's entities (SGDSN/ANSSI). His work bridges computational imaging, defense applications, and digital forensics. Project leadership: SURECAVI, IMPROVED, BOFOR Key technologies: GPU acceleration, real-time processing, optical flow estimation, RPC refinement Gabriele actively contributes to open-source tools like S2P (Satellite Stereo Pipeline), MGM (MultiGlobal Matching), and OMNIflip. He teaches in the Master MVA program and collaborates across institutions (ENPC, UPF).

Wooram Parkمشاهده پروفایل

دانشیار

• Robotics
• Biomedical Robotics
• Computational Structural Biology
• +۳ مورد دیگر

Wooram Park is an Associate Professor in the Department of Mechanical Engineering at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. He leads the Robotics and Intelligent Systems Laboratory (ROBINS Lab) and holds a PhD from Johns Hopkins University (2008), along with MS and BS degrees from Seoul National University (2003 and 1999). His research focuses on robotics, biomedical robotics, computational structural biology, and image processing. Key projects include flexible needle steering for medical applications, haptic feedback systems, and advanced algorithms for motion planning and image reconstruction. He has received notable awards such as the Creel Fellowship (2007) and Critics’ Choice Award in ArtBot Design (2004). His work spans theoretical contributions in stochastic systems and practical innovations like vibratory magnetic robots (Vimbot) and wearable haptic devices. The ROBINS Lab emphasizes interdisciplinary research at the intersection of mechanical engineering, computer science, and biomedical applications.

• Control Technology
• Distributed Optimization
• Machine Learning
• +۴ مورد دیگر

Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.

Yusuf Altintasمشاهده پروفایل

استاد

• Machining Processes
• Computer Numerical Control (CNC)
• Machine Tool Dynamics
• +۵ مورد دیگر

Yusuf Altintas is a Professor in the Department of Mechanical Engineering at the University of British Columbia's Faculty of Applied Science, holding the NSERC–P&WC-Sandrik Coromant Industrial Research Chair and coordinating the Mechatronics Option. An internationally acclaimed scholar, he is a Fellow of 10 prestigious academies including the National Academy of Engineering (NAE), Royal Society of Canada (RSC), and ASME. His academic credentials include a Ph.D. from McMaster University, an Honorary Doctor of Engineering from the University of Stuttgart, and a Doctor of Technical Sciences from Budapest University of Technology and Economics. Professor Altintas's research pioneers the integration of physics-based modeling and data-driven approaches for machining systems. His work spans virtual high-performance machining simulation, machine tool dynamics, chatter stability prediction, and intelligent process control for CNC systems. Current projects focus on digital twin development for machining processes, spindle health diagnostics, ultrasonic vibration-assisted tooling, and adaptive damping systems for aerospace manufacturing applications. His methodologies bridge theoretical mechanics with industrial implementation in die/mold and aerospace sectors. Analysis of his 2022-2025 publications reveals dominant trends in physics-informed machine learning for spindle fault detection, topology-optimized tool design, and chatter avoidance in thin-walled component machining. Key thematic clusters include digital twin implementation (28% of recent work), dynamics modeling of multi-axis systems (35%), and intelligent monitoring algorithms (22%), with growing emphasis on anisotropic material machining and 3D printing process control. Georg Schlesinger Award (2016) NSERC Strategic Research Network in Virtual Machining Grant (2016) NSERC Synergy Award (2013) ASME Blackall Machine Tool and Gage Award (2013) Special Distinguished Scientist Award from Turkey's Scientific and Technical Research Council (2013) He directs the Manufacturing Automation Laboratory at UBC, leading an international research consortium on virtual machining systems supported by NSERC and industry partners including Sandvik Coromant and Pratt & Whitney Canada. His team develops real-time process monitoring frameworks and physics-based simulation tools that have been adopted in aerospace manufacturing for blade machining and die/mold production. The laboratory maintains advanced testbeds for five-axis machining dynamics, spindle health monitoring, and ultrasonic vibration-assisted tooling, serving as a hub for industry-academic collaboration in next-generation manufacturing technologies.

Kristin Y. Pettersenمشاهده پروفایل

استاد

• Nonlinear control theory
• Marine robotics
• Snake robotics
• +۵ مورد دیگر

Kristin Y. Pettersen is a Professor at the Norwegian University of Science and Technology (NTNU) in the Department of Engineering Cybernetics, Faculty of Information Technology and Electrical Engineering. She holds a PhD and MSc in Engineering Cybernetics from NTNU and serves as an Adjunct Professor at the Norwegian Defence Research Establishment (FFI). She co-founded and led Eelume AS as its first CEO. PhD in Engineering Cybernetics, NTNU MSc in Engineering Cybernetics, NTNU Her research focuses on nonlinear control theory, motion control of mechanical systems, and marine robotics. Key areas include autonomous vehicles, underactuated systems, and cooperative control. Her recent work involves snake robotics, vehicle-manipulator systems, and safety-critical control algorithms. Her publications demonstrate trends in marine robotics , nonlinear control systems , autonomous navigation , formation control , and adaptive algorithms . Emerging topics include energy-shaping control , extremum-seeking optimization , and task-priority frameworks for complex robotic systems. 2025: Norwegian Academy of Science and Letters (DNVA) 2020: ERC Advanced Grant 2017: IEEE Fellow 2016-2021: Board member, Eelume AS 2013-2023: Key scientist, NTNU AMOS She has supervised 30 PhD graduates and currently mentors 16 PhD candidates. Her grants include ERC PoC UR4energy (€150k), ERC AdG CRÈME (€2.5M), and CAROS (NOK 45M) for subsea autonomy. She leads teams at NTNU's Applied Underwater Robotics Laboratory and contributes to the Cluster of Excellence IntCDC.

Gabriele Ligaمشاهده پروفایل

استادیار

• Digital Communications
• Information Theory
• Optical Communications
• +۵ مورد دیگر

Gabriele Liga is an Assistant Professor at the Department of Electrical Engineering, Eindhoven University of Technology (TU/e), affiliated with the Signal Processing Systems (SPS) Group. He holds a Marie Curie Eurotech Fellowship focusing on signal shaping techniques for nonlinear optical fiber channels. His academic journey includes a Ph.D. in optical communications from University College London, followed by postdoctoral research in digital signal processing and nonlinearity compensation. Education: B.Sc. in Telecommunications Engineering from Università degli Studi di Palermo (2005), M.Sc. in Telecommunications Engineering from Politecnico di Milano (2011), and a Ph.D. in Optical Communications from University College London (2017). Research Interests: Digital communications, information theory, fiber-optic systems, nonlinearity compensation, channel coding, and multi-user optical communication theory. His work emphasizes achieving transmission limits through signal shaping and advanced signal processing techniques. Projects: Active roles in NESTOR (Next-gen optical networks), QuNEST (quantum communication security), Fun-NOTCH (nonlinear optical channel fundamentals), and SSTOC (signal shaping tailored to optical channels). Collaborations span institutions globally, focusing on optical fiber communication challenges. Awards: 2023 ACP/POEM Best Student Paper Award and 2019 OECC Best Paper Award. Serves as a reviewer for IEEE journals and OSA publications. Labs/Teams: Core member of the SPS Group and involved in interdisciplinary projects blending theory and experimental validation.

Gökhan Kiperمشاهده پروفایل

استاد

• Mechanism Science
• Machine Design
• Deployable Structures
• +۱ مورد دیگر

Prof. Dr. Gökhan Kiper is a faculty member in the Department of Mechanical Engineering at Izmir Institute of Technology , Turkey. His research focuses on Mechanism Science , Machine Design , and Deployable Structures , with particular emphasis on Polyhedral Geometry applications. Teaches courses: ME332 (Mechanisms), ME402 (Machine Design), ME577 (Advanced Mechanism Design) Active in IFToMM (International Federation for the Promotion of Mechanism and Machine Science), including roles in the Technical Committee for Computational Kinematics and the Turkey Branch (MakTeD) Co-organized the IFToMM Summer School on Mechanism Design for Medical Applications (2018) Research interests span kinematic synthesis of mechanisms, deployable architectural structures, and medical robotics. Key projects include a rollable ramp for temporary use, finger exoskeletons for rehabilitation, and remote-center-of-motion manipulators for minimally invasive surgery. His work integrates theoretical analysis with practical prototyping, reflected in publications across robotics, structural mechanics, and geometric design. Affiliates with the Rasim Alizade Mechatronics Laboratory (RAML) and the IzTech Kinetic Designs in Architecture Group . Presented at international conferences like International Symposium of Mechanism and Machine Science (ISMMS-2017) in Baku, Azerbaijan, where he chaired sessions on mechanism kinematics.

Adam Woźniakمشاهده پروفایل

استاد

• Coordinate Metrology
• Mechanical Engineering
• Quality Engineering
• +۵ مورد دیگر

Adam Woźniak is a Professor and Vice-Rector for Development at Warsaw University of Technology (WUT), holding positions at the Faculty of Mechatronics and the Institute of Metrology and Biomedical Engineering. He earned a PhD in 2002, D.Sc. (habilitation) in 2011, and was promoted to full professor in 2017. His research focuses on advanced geometrical measurement techniques, coordinate metrology, quality engineering, and reliability of mechatronic systems. He has authored 2 books and over 130 scientific publications, including work on probing accuracy, X-ray CT applications, and dynamic error analysis in manufacturing systems. Notably, he served as Director of the Institute of Metrology and Biomedical Engineering (2012–2020) and later as Dean of the Faculty of Mechatronics (2020). He received the Polish Prime Minister’s Prize for Scientific Achievements (2012) and multiple scholarships from the Foundation for Polish Science. Education: PhD (2002), D.Sc. (2011), Warsaw University of Technology; Visiting Professor at École Polytechnique de Montréal (2005–2006). Research interests include coordinate measuring machine (CMM) performance, probing system accuracy, and industrial CT applications. His work addresses dynamic error identification, probe error compensation, and precision measurement techniques. Recent projects involve high-density point cloud correction, scanning probe validation, and pediatric growth measurement systems. His articles analyze topics like probe reliability, CNC machine tool errors, and X-ray CT threshold optimization. Awards also include recognition for leadership in standardization bodies, including roles in Poland’s Council for Metrology and Standardization. He has supervised 6 PhD students and numerous master’s candidates, contributing to over a dozen funded research projects. His lab, the Virtual Manufacturing Research Laboratory, integrates metrology, mechatronics, and biomedical engineering for advanced measurement solutions.

• Acoustic Signal Processing
• Blind Source Separation
• Digital Signal Processing
• +۶ مورد دیگر

Shoji Makino is a Professor at Waseda University's Graduate School of Information, Production and Systems. He has held academic and research positions at institutions such as the University of Tsukuba and NTT Communication Science Laboratories. His work spans acoustic signal processing, blind source separation, and adaptive filtering. Education: Ph.D., Tohoku University (1993.03) Mechanical Engineering, Tohoku University Graduate School of Engineering (1979.04–1981.03) Engineering, Tohoku University Faculty of Engineering (1975.04–1979.03) Research Interests: His research focuses on acoustic signal processing for speech and audio, including blind source separation (BSS) , beamforming , and adaptive filtering . He pioneered methods for solving permutation alignment in frequency-domain BSS and developed geometrically constrained ICA techniques. Scientific Awards: Hoko Award (2018.10, Hattori Hokokai Foundation) Outstanding Contribution Award of the Institute of Electronics, Information, and Communication Engineers (2018.06) IEEE Signal Processing Society Best Paper Award (2014.01) IEEE Fellow (2004.01) IEICE Achievement Award (1997.05) Committee Memberships: He has served as Chair of the IEEE CAS Society's Blind Signal Processing TC, General Chair of IEEE WASPAA2007, and Associate Editor of IEEE Trans. SAP. He is actively involved in EURASIP, APSIPA, and the Acoustical Society of Japan.

Richard J. Vaccaroمشاهده پروفایل

استاد

• Array Signal Processing
• Direction Finding (DOA Estimation)
• Statistical Modeling of Inertial Sensors
• +۳ مورد دیگر

Richard J. Vaccaro is a Professor in the Department of Electrical, Computer and Biomedical Engineering at the University of Rhode Island. His research focuses on subspace estimation in sensor array signal processing, statistical modeling of inertial sensors, and control system design. Education : Ph.D., Electrical Engineering, Princeton University, 1983 M.S., Electrical Engineering, Drexel University, 1979 B.S., Electrical Engineering, Drexel University, 1979 Research Interests include array signal processing, direction-of-arrival (DOA) estimation, inertial sensor modeling, and control theory. His work explores subspace perturbation expansions, sensor fusion for drift reduction, and robust underwater acoustic localization. Recent Publications highlight advancements in subspace-based parameter estimation, optimal sensor array design, and geometric approaches to signal processing. Key trends involve applications in radar, underwater acoustics, and mobile robotics. Grants include collaborations with MIT (2023) and funding from the Office of Naval Research (2021). His patented technologies address sensor array calibration and noise reduction in inertial measurement units.

• Microelectronics
• Radiation Effects on Electronics
• Semiconductor Reliability
• +۳ مورد دیگر

Jean-Luc Autran is an Exceptional University Professor (PRCE2) at Aix-Marseille University, affiliated with the Department of Detection, Radiation and Reliability (DETECT) within the Faculty of Sciences. Since July 2023, he has been temporarily assigned to the University of Rennes for managerial roles. His research focuses on radiation effects in microelectronics, particularly soft errors caused by atmospheric neutrons, muons, protons, and terrestrial radiation in nanoscale devices. Key Research Areas: Microelectronics Reliability, Single-Event Effects, Atmospheric Radiation, Neutron Interactions, Muon Physics, Radiation-Hardened Design. Scientific Leadership: As an Honorary Member of the Institut Universitaire de France (since 2003), he leads multidisciplinary efforts from radiation metrology to multi-physics circuit simulation via tools like GEANT4, SRIM, and NGSPICE. His work spans 25+ years, evolving from quantum transport in nano-MOSFETs (1998-2008) to atmospheric radiation effects (2005-present). Recent Contributions: 2025 studies on ultrawide-bandgap semiconductors, deep learning-based radiation simulations, and JET Tokamak neutron experiments. He pioneers a multi-scale Single-Event Effect simulation framework for decananometer CMOS, integrating particle physics, device modeling, and system-level error rate prediction. Scientific Awards: Honorary Member, Institut Universitaire de France (2003 class). Educational Impact: Teaches graduate courses in quantum mechanics simulation, nanoelectronics reliability, and radiation detection at Aix-Marseille University, with lectures delivered in English for international audiences.

Jasper Goselingمشاهده پروفایل

دانشیار

• Differential Privacy
• Network Coding
• Optimization Problem
• +۴ مورد دیگر

Jasper Goseling is an Associate Professor at the Digital Society Institute and affiliated with the Mathematics of Operations Research department. His research spans differential privacy, network coding, optimization, and wireless systems, often bridging theoretical and applied domains. Key research areas: Differential Privacy, Network Coding, Optimization, Wireless Sensor Networks, Machine Learning His recent work focuses on robust optimization techniques for local differential privacy, addressing trade-offs between data utility and privacy preservation. Earlier contributions include studies on energy-efficient data collection in sensor networks, caching strategies in wireless environments, and entropy-based analysis of hydrothermal systems. Article trends reveal a strong emphasis on privacy-preserving algorithms (2022-2024) and historical expertise in network coding, queueing theory, and thermodynamic entropy. His research integrates mathematical rigor with practical applications in wireless communication and data management. Activities include organizing the 45th Symposium on Information Theory and Signal Processing (2025) and leadership roles in the IEEE Benelux Chapter on Information Theory (Chair, 2017; Member, 2012-2017). He also contributed to the 2015 European School of Information Theory.

• Mechanical Engineering
• Aerospace Engineering
• Manufacturing Engineering
• +۵ مورد دیگر

Oguzhan Tuysuz is an Assistant Professor in the Department of Mechanical Engineering at Polytechnique Montréal since November 2021. He holds a Ph.D. and MASc in Mechanical Engineering from the University of British Columbia (UBC) under Professor Yusuf Altintas, with prior industrial experience at Pratt & Whitney Canada (P&WC) as a Machining Technologies Development Specialist. B.Sc. Mechanical Engineering, Istanbul Technical University (ITU), 2011 B.Sc. Manufacturing Engineering, ITU, 2011 M.A.Sc. Mechanical Engineering, UBC, 2017 Ph.D. Mechanical Engineering, UBC, 2019 His research focuses on physics-based interdisciplinary approaches to digitize manufacturing processes while minimizing physical testing. Key areas include machine tool dynamics , vibration stability in thin-walled part machining , hybrid manufacturing , process damping modeling , and Industry 4.0 integration . He combines analytical, numerical, and experimental methods. Recent publications (2024-2025) demonstrate his expertise in non-contact vibration measurement , acoustic monitoring , tool wear thermal modeling , and nonlinear dynamics in aerospace manufacturing . His work bridges virtual manufacturing with real-time process control , emphasizing data assimilation and reduced-order modeling . Scientific Awards: NSERC Research Grant recipient (2023, part of $2.6 million funding to Polytechnique Montréal researchers) He supervises graduate students in projects related to machining process optimization and dynamic stability analysis , with completed theses on in-process machine tool dynamics and process damping modeling . His affiliations include the Product Development and Manufacturing Research Group (GRDFP) and Virtual Manufacturing Research Laboratory (LRFV) . Teaching includes specialized courses on Machining of Aerospace Alloys (MEC6619) , Advanced Mechanical Manufacturing (MEC8554) , and Aerospace Manufacturing Processes (AER8505) .

• Mechanical Engineering
• Manufacturing
• Incremental Forming
• +۳ مورد دیگر

Marthe Vanhulst is a researcher affiliated with the Department of Mechanical Engineering at KU Leuven, specializing in incremental sheet metal forming and its applications in biomedical engineering. She works in the MaPS division (Manufacturing and Process Systems) and contributes to collaborative research initiatives like Flanders Make, the strategic research center for the manufacturing industry in Flanders. Research Interests Development of advanced manufacturing techniques for complex geometries Application of machine learning in optimizing sheet metal forming processes Biomedical applications of incremental forming, particularly cranial implants Knowledge management systems for industrial engineering workflows Integration of Digital Image Correlation for strain and thickness analysis Publication Trends Her research focuses on improving the geometric accuracy and thickness distribution in multi-stage incremental forming. Key themes include toolpath optimization, intermediate shape design, and digital compensation methods. Recent work integrates collaborative platforms for knowledge sharing in manufacturing, reflecting interdisciplinary efforts between mechanical engineering and computer science. Laboratory Affiliation Marthe is part of the Manufacturing and Process Systems (MaPS) research group at KU Leuven, which collaborates closely with Flanders Make. Her projects emphasize industrial partnerships and translating theoretical advancements into practical solutions for precision manufacturing.