جست‌وجوی استاد و پژوهشگر

Mehdi Eshaghiمشاهده پروفایل

استادیار

• Vibration Analysis
• Smart Materials
• Magnetorheological/Electrorheological Fluids
• +۵ مورد دیگر

Dr. Mehdi Eshaghi is an Assistant Professor - Teaching Stream in the Department of Mechanical and Aerospace Engineering at Carleton University since 2021. He holds a Ph.D. from Concordia University, specializing in Vibration and Control of Smart Systems, with postdoctoral research in smart material characterization. His expertise spans magnetorheological (MR)/electrorheological (ER) fluids, piezoelectric systems, nonlinear vibration analysis, and nano/micro-robotics. Eshaghi has extensive teaching experience, including a 15-credit Graduate Certificate in University Teaching from Concordia, and industrial engineering roles at Now Energy Solutions and through NSERC Engage programs. Education: BSc (Chamran University), MSc (Iran University of Science and Technology), PhD (Concordia University). His research focuses on adaptive structures, smart material applications, and structural dynamics. He has published extensively in journals like Extreme Mechanics Letters , Aerospace Science and Technology , and Composite Structures . Teaching specialties include Mechanical Vibrations, Finite Element Methods, and Numerical Techniques. His work combines theoretical modeling, experimental validation, and industrial collaboration. Current research trends include optimizing MR-fluid sandwich panels for flutter suppression, analyzing post-yield MR/ER fluid behavior in smart structures, and developing small-scale magnetic soft robots. Grants and collaborations include NSERC Engage projects with industry partners. He has advised on experimental setups for MR-fluid systems and contributed to benchmark solutions for functionally graded plates. His work bridges mechanical engineering fundamentals with advanced smart material applications in aerospace and robotics domains.

• Computer Vision
• Augmented Reality
• Image Processing
• +۴ مورد دیگر

Gerhard Roth is an Adjunct Professor in the Department of Computer Science at Carleton University, affiliated with the School of Computer Science. His research focuses on computer vision, augmented reality, and 3D modeling, with significant contributions to camera calibration, real-time tracking systems, and GPU-accelerated algorithms. He has pioneered work in markerless augmented reality, robust feature matching, and applications in robotics and medical imaging. Key research interests include augmented reality systems development , camera pose estimation , and biologically inspired vision algorithms . His work often bridges computer vision and graphics, addressing challenges such as realistic illumination in AR, efficient video copy detection, and collaborative gesture interaction. Publications span topics ranging from GPU-based visual cortex modeling to panoramic image stitching, reflecting a focus on practical, real-world applications. He collaborates with institutions like the University of Ottawa’s VIVA Lab on projects like TRECVID benchmarking and medical imaging analysis. Current efforts emphasize improving AR authoring tools and robust feature descriptors for dynamic environments. Notable contributions include the Projective Vision Toolkit , Command Center AR tool , and advancements in stereo vision algorithms. His research has implications for robotics, healthcare interfaces, and immersive visualization systems.

Yi Zhuمشاهده پروفایل

استادیار

• Adaptive Structures
• Computational Mechanics
• Origami Engineering
• +۱ مورد دیگر

Dr. Yi Zhu is Assistant Professor of Civil, Environmental and Geospatial Engineering at Michigan Technological University, specializing in adaptive structural systems. He holds a PhD in Civil Engineering and Scientific Computing from University of Michigan, with research focusing on computational mechanics and reconfigurable structures. Zhu develops novel simulation frameworks and fabrication techniques for origami-inspired engineering systems across scales - from micro-robots to civil infrastructure. His recent breakthrough in modular thick origami enables rapidly deployable load-bearing structures with applications in disaster response and space habitats. Research integrates computational modeling with experimental validation, supported by NSF and university grants. Research interests include: Reconfigurable structural systems Computational mechanics frameworks Origami-inspired engineering Machine learning for structural design Multi-physics simulation His MEchanics for Adaptive Reconfiguration (MAR) group develops open-source simulation tools (Sim-FAST, SWOMPS) and investigates applications in soft robotics, space deployables, and adaptive infrastructure. Publications demonstrate consistent focus on bridging theoretical models with practical fabrication techniques. Awards include ProQuest Distinguished Dissertation recognition and multiple research fellowships for innovations in computational mechanics and adaptive structures.

Hairong Qiمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Remote Sensing
• +۳ مورد دیگر

Dr. Hairong Qi is the Gonzalez Family Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville, part of the Tickle College of Engineering. Her research focuses on collaborative signal processing, computer vision, machine learning, and remote sensing. She directs the Advanced Imaging and Collaborative Information Processing (AICIP) Lab. Dr. Qi holds a PhD in Computer Engineering from North Carolina State University (1999), and MS/BS degrees in Computer Science from Northern JiaoTong University, China. Her work has been funded by NSF, DARPA, IARPA, ONR, NASA, and DHS. Her research contributions include over 200 technical papers and two co-authored books in computer vision. Notable awards include the IEEE Fellow (2018), NSF CAREER Award (2005), and GRSS Highest Impact Paper Award (2012). She has led projects in smart grid resilience, AI-driven healthcare, and hyperspectral imaging. Professional service includes editorial roles for IEEE Transactions on Image Processing and IEEE Multimedia Magazine, and leadership in conferences like ICPR, ICDSC, and WHISPERS. She has mentored numerous students and advised on interdisciplinary initiatives like the UT Cluster Hiring Initiative in Foundational AI. Dr. Qi’s work spans academic, industrial, and societal impacts, with innovations in sensor networks, cybersecurity, and agricultural robotics.

Yvonne Coadyمشاهده پروفایل

استاد

• Aspect-oriented software development
• Scalable system infrastructures
• Distributed virtualization
• +۷ مورد دیگر

Yvonne Coady is a Professor in the Department of Computer Science at the University of Victoria. She leads the MOD(ularity) Squad, focusing on system infrastructure modularity, mixed reality systems, and geospatial computing. Her research spans scalable distributed systems, immersive technologies, and AI-driven applications. She has co-authored over 170 papers and supervised numerous graduate students. Research interests include citizen science integration, advanced software modularity, and cloud computing architectures. Collaborations include projects with IBM, Ericsson, and Urthecast, addressing Earth observation, urban planning, and virtual reality analytics. Recognized with the 2015 Knowledge Mobilization Award, her work emphasizes real-world impact through industry partnerships. Current projects explore immersive applications via VR/AR, such as the RAVR and SAVR initiatives, and accessibility-enhanced interfaces. She also investigates geospatial computing for environmental monitoring and disaster response. Awards and grants include NSERC Collaborative Research and Mitacs Accelerate funding. Grants: NSERC grants (2023-2024), Mitacs projects (2020-2024) Labs/Teams: MOD(ularity) Squad, RAVR (Research in Augmented and Virtual Reality) Key Collaborations: Ocean Networks Canada, SALA Lab (UBC)

• Head and Neck Surgical Oncology
• Otolaryngology
• Surgical Education
• +۳ مورد دیگر

Hilary McCrary, MD, MPH is a Clinical Assistant Professor of Otolaryngology – Head and Neck Surgery at the University of Utah's Spencer Fox Eccles School of Medicine , where she practices as a surgeon at the Huntsman Cancer Institute . A board-certified specialist in Otolaryngology – Head and Neck Surgery , she completed fellowship training in head and neck surgical oncology at The Ohio State University. Education: B.S. in Health Sciences, University of Arizona M.P.H., University of Arizona M.D., University of Arizona Fellowship: Head and Neck Surgical Oncology and Microvascular Reconstruction, Ohio State University College of Medicine Residency: Otolaryngology, University of Utah Research Interests focus on large-scale dataset analysis (Utah Populations Database, SEER Database) to study head and neck cancer trends , with additional work in surgical education and public health policy . Her publications span topics like opioid prescription patterns , cadaver-based surgical training , and robotic surgery protocols . Scientific Awards include induction into the Gold Humanism Honor Society and Alpha Omega Alpha National Medical Honor Society during medical school. Clinical Work includes head and neck cancer care at Huntsman Cancer Institute and pediatric otolaryngology at Primary Children's Hospital, with expertise in microvascular reconstruction and advanced robotic surgery .

Micah Corahمشاهده پروفایل

استادیار

• Robotics
• Multi-Robot Systems
• Aerial Robotics
• +۵ مورد دیگر

Micah Corah is an Assistant Professor of Computer Science at the Colorado School of Mines, directing the Navigation, Aerial-robots, and Perception Planning Laboratory (NAPPLab). His research focuses on aerial robotics, multi-robot systems, and active perception with applications in autonomous exploration, infrastructure inspection, and search and rescue. He holds a PhD in Robotics from Carnegie Mellon University (2020), and completed postdoctoral work at CMU’s AirLab and NASA’s Jet Propulsion Laboratory (JPL). His work emphasizes scalable algorithms for multi-robot coordination, submodular optimization, and perception planning in challenging environments. Education: PhD (2020) and MS (2017) in Robotics from Carnegie Mellon University; BS in Computer Science and Mechanical Engineering from Rensselaer Polytechnic Institute (2015). Research interests include: Multi-robot coordination and distributed planning Aerial robotics and autonomous filming Active perception and sensor optimization Subterranean and 3D environment exploration Applications in search and rescue, infrastructure inspection, and cinematography His recent publications highlight advancements in multi-drone view planning, coordinated motion capture for dynamic scenes, and resilient submodular maximization for large-scale systems. Micah actively mentors students in Computer Science, Robotics, and Mechanical Engineering, emphasizing both theoretical and experimental research.

Hua Wangمشاهده پروفایل

استاد

• Machine Learning
• Data Mining
• Medical Image Computing
• +۶ مورد دیگر

Hua Wang is a Professor and Graduate Director in the Department of Computer Science at the Colorado School of Mines. He joined the university in 2012 after completing his Ph.D. in Computer Science & Engineering at the University of Texas at Arlington. Prior to academia, he worked in industry as a Signal Processing engineer at Motorola for four years. Education B.S. in Electronic Engineering, Tsinghua University (Beijing, 1999) M.S. in Signal Processing, Nanyang Technological University (Singapore, 2003) Ph.D. in Computer Science & Engineering, University of Texas at Arlington (2012) Research Interests : Dr. Wang focuses on developing efficient machine learning and data mining algorithms with theoretical guarantees for large-scale data challenges. His work spans applications in medical image computing, health informatics, cheminformatics, material informatics, additive manufacturing, bioinformatics, and computer vision. He emphasizes practical solutions for interdisciplinary problems such as drug discovery, disease diagnosis, and robotics. Advising & Grants : While no specific student advisees or grant details are listed, his publications reflect extensive collaboration across domains like healthcare, materials science, and robotics. His work often involves multi-institutional efforts addressing real-world data-driven challenges. Labs & Teams : His research group likely focuses on algorithmic development for medical imaging and multi-modal data fusion, though specific lab affiliations are not explicitly mentioned in the text.

Tom Williamsمشاهده پروفایل

دانشیار

• Human-Robot Interaction
• Natural Language Processing
• Robot Ethics
• +۱ مورد دیگر

Dr. Tom Williams is Associate Professor of Computer Science and Director of the MIRRORLab at Colorado School of Mines. His research program centers on natural language-based human-robot interaction with emphasis on ethical, social, and contextual dimensions of communication. Williams investigates how robots can understand and generate context-sensitive language, particularly in morally complex situations. Current projects explore role-based moral reasoning, politeness strategies, and cultural variations in human-robot interaction. His work integrates cognitive science, artificial intelligence, and human-computer interaction methodologies. He has received significant recognition including NSF CAREER, NASA Early Career Faculty, and AFOSR Young Investigator awards. Williams teaches courses in Human-Robot Interaction, Robot Ethics, and Computer Vision, maintaining international collaborations on socially intelligent robotic systems.

• Nonlinear Control
• Automotive Systems
• Robotics
• +۴ مورد دیگر

Antonella Ferrara is a Full Professor of Automatic Control at the University of Pavia's Department of Electrical, Computer and Biomedical Engineering (ECBE). She holds leadership roles, including Head of the Intelligent Robotics Laboratory and President of the Department's Research Standing Committee. Her academic journey includes a Laurea Degree (MSc equivalent) in Electronic Engineering from the University of Genova (1987) and a PhD in Computer Science and Electronics (1992). She transitioned from Assistant to Full Professor at the University of Pavia, contributing significantly to nonlinear control, automotive systems, robotics, and power systems. Her research focuses on sliding mode control, vehicular traffic modeling, and applications in autonomous systems. She has authored/co-authored over 450 publications, including 160 journal papers and monographs on topics like vehicle dynamics and freeway traffic control. Awards include IEEE Fellow (2020), IFAC Fellow (2021-2023), and AAIA Fellow (2024). She teaches courses such as Process Control, Robot Control, and Nonlinear Control in English, and contributes to international collaborations, including projects on sustainable mobility and medical robotics. Her institutional roles span research leadership, international mobility coordination, and editorial contributions to journals like Automatica and IEEE Transactions. Prof. Ferrara supervises numerous PhD, postdoc, and graduate students, leading over 200 MSc theses since 2020. She chairs major conferences, including the 24th IFAC World Congress (2029) and the 2024 IEEE Workshop on Variable Structure Systems. Her work bridges theoretical advancements with practical applications in industry, including collaborations with automotive companies like Ferrari F1 and FIAT.

Junsong Yuanمشاهده پروفایل

استاد

• Computer Vision
• Pattern Recognition
• Video Analytics
• +۶ مورد دیگر

Junsong Yuan is a Professor and Director of the Visual Computing Lab at the Department of Computer Science and Engineering, University at Buffalo (SUNY). He previously served as an Associate Professor and Nanyang Assistant Professor at Nanyang Technological University (NTU), Singapore. His research focuses on computer vision, pattern recognition, video analytics, and large-scale visual search. He holds a Ph.D. from Northwestern University, M.Eng. from National University of Singapore, and B.Eng. from Huazhong University of Science and Technology. Education : Ph.D., Electrical and Computer Engineering, Northwestern University, 2009 M.Eng., Electrical and Computer Engineering, National University of Singapore, 2005 B.Eng., Communication Engineering, Huazhong University of Science and Technology, 2002 Research Interests : Dr. Yuan's work spans computer vision, video analytics, gesture/action analysis, and multimodal learning. He emphasizes scalable visual search, 3D reconstruction, and federated learning for medical imaging. His lab develops algorithms for autonomous systems, generative media processing, and human-AI interaction. Awards : IEEE Fellow (2021) IAPR Fellow (2018) SUNY Chancellor's Award for Excellence in Scholarship (2022) Advising & Grants : He has advised numerous PhD students, including Sudhir Yarram, Nan Xi, and Tianyu Luan. His research is supported by grants focusing on video generation, medical image analysis, and federated learning. He serves as Editor-in-Chief of JVCI and on editorial boards of T-PAMI, T-IP, and T-CSVT. Labs & Teams : Director of the Visual Computing Lab, leading projects in generative models, 3D scene understanding, and healthcare AI. Collaborates with industry partners like Meta, Amazon, and Accenture on applied vision systems.

Kihan Parkمشاهده پروفایل

استادیار

• Medical Robotics
• Micro-scale Sensing/Actuation
• Machine Learning
• +۳ مورد دیگر

Kihan Park serves as an Assistant Professor in the Department of Mechanical Engineering at the University of Massachusetts Dartmouth. He holds a PhD in Robotics (with home department in Biomedical Engineering) from Georgia Institute of Technology (2019) and BS/MS degrees in Mechanical Engineering from Korea Advanced Institute of Science and Technology (KAIST) (2009 and 2011). His research focuses on medical robotics, micro-scale sensing and actuation, machine learning applications, and biosignal processing. Dr. Park's work bridges medical diagnostics with industrial robotics through innovative design of robotic systems, microfabrication techniques, and machine learning algorithms. His research has significant applications in healthcare and defense sectors, particularly in non-invasive imaging and underwater vehicle technology. Dr. Park leads the Multi-scale Medical Robotics (MSMR) Laboratory where his team develops cutting-edge technologies funded by major organizations. His research portfolio demonstrates strong interdisciplinary connections between mechanical engineering, biomedical applications, and advanced computing. Notable research funding includes: $478,972 from Office of Naval Research for UUV sensor networks $175,000 from NSF for non-invasive breast imaging $400,230 from Office of Naval Research for soft robotic end-effectors in EOD missions Dr. Park teaches undergraduate and graduate courses including Robotics (MNE 482), Control Systems Design (MNE 466), and Electronics and Implementation (MNE 465), contributing to multiple degree programs in mechanical engineering and sustainable energy.

Markian Pahutaمشاهده پروفایل

دانشیار

• Spine surgery
• Orthopaedic trauma
• Degenerative cervical myelopathy
• +۶ مورد دیگر

Markian Pahuta MD PhD is an Associate Professor of Surgery at McMaster University and an orthopaedic spine surgeon at Hamilton General Hospital, Ontario. Board-certified by the American Board of Orthopaedic Surgery, he completed his MD at the University of Toronto (2004-2008), residency at the University of Ottawa (2008-2015), a Clinician-Investigator Program (2011-2013), and a spine-surgery fellowship at the University Health Network/University of Toronto (2015-2016), followed by a PhD at the University of Ottawa (2013-2019). His practice and research cover the entire spectrum of spinal disorders, with a recent focus on degenerative cervical myelopathy, spinal trauma, oncology, adult deformity, health-economic valuation, and technology-enhanced surgical training. Education & Training PhD, University of Ottawa, 2013-2019 Clinical Fellowship in Spine Surgery, University Health Network/University of Toronto, 2015-2016 Clinician Investigator Program, University of Ottawa, 2011-2013 MD, University of Toronto, 2004-2008 Orthopaedic Surgery Residency, University of Ottawa, 2008-2015 Diplomate, American Board of Orthopaedic Surgery, 2019-2029 Research Interests Dr Pahuta leads Canada-wide observational studies through the Canadian Spine Outcomes and Research Network (CSORN) examining wait-times, opioid utilisation, complication rates, and cost-effectiveness of spine surgery. He publishes systematic reviews and health-economic analyses that define utility scores for metastatic epidural spinal cord compression and degenerative cervical myelopathy, enabling cost-utility and budget-impact evaluations. His surgical oncology work clarifies optimal treatment strategies for patients with intermediate SIN scores and establishes consensus terminology for cancer-related spine pain. He explores augmented- and virtual-reality platforms to enhance competency-based training of spine surgeons and investigates AI-driven automation of spinopelvic parameter measurement. Across more than 120 peer-reviewed articles since 2008, his recent output (2022-2025) clusters into four dominant themes: (1) large-scale prospective cohort analyses of Canadian elective and traumatic spine populations; (2) health-services and economic evaluations that translate patient-reported outcome scores into policy-relevant utility metrics; (3) systematic reviews and meta-analyses that synthesise complication rates, survivorship, and comparative effectiveness of cervical and lumbar procedures; and (4) innovation studies on robotics, navigation, and immersive technologies in surgical education. Scientific Awards & Recognition No specific prizes or named lectureships are listed in the supplied material; however, his work is frequently cited in national guidelines and picked up by mainstream Canadian media (>30 news outlets for one 2023 study). Grants & Advising While explicit grant numbers are not provided, he is the principal architect of multiple CSORN analyses, indicating sustained national funding. No individual graduate students or post-doctoral fellows are named in the available text. Laboratory & Team Dr Pahuta collaborates with the McMaster Spine Program, the CSORN national consortium, the AO Spine Knowledge Forum, and international working groups developing consensus frameworks such as OSCO-M. These multi-institutional teams link clinicians, epidemiologists, health economists, and data scientists across more than 20 Canadian centres and multiple international sites.

Erica Cochran Hameenمشاهده پروفایل

دانشیار

• Building Performance
• Indoor Environmental Quality
• Sustainable Design
• +۱ مورد دیگر

Erica Cochran Hameen is Associate Professor, Co-Director of the Center for Building Performance & Diagnostics, and Doctor of Design Track Chair at Carnegie Mellon University. Her research investigates indoor environmental quality, building performance, and sustainable retrofits with focus on health, energy efficiency, and occupant comfort. Key research areas: Healthy building retrofits for schools Personal comfort modeling HVAC control optimization Post-occupancy evaluation methods Life cycle assessment of building materials Publications demonstrate consistent focus on occupant-centered building performance, with recent advances in sensor-driven thermal comfort modeling, robotics for building assessment, and cross-cultural studies of sustainable materials. Work increasingly integrates machine learning with building science. Recognition includes awards from: American Institute of Architects (AIA) New York Landmarks Conservancy Brooklyn Chamber of Commerce Department of Energy competitions

• Artificial Intelligence
• Robotics
• Biomedical Engineering
• +۶ مورد دیگر

Dr. Dandan Zhang is an Assistant Professor in AI & Machine Learning at the Department of Bioengineering, Imperial College London, and holds a Lecturer position in the I-X initiative. She directs the Multi-Scale Embodied Intelligence Laboratory and is affiliated with the Hamlyn Centre’s Robotics and Sensing groups. Previously, she was a Lecturer at the University of Bristol’s Department of Engineering Mathematics (Bristol Robotics Laboratory). Her research integrates robotics, biomedicine, and AI, focusing on dexterous manipulation via multi-modal sensor fusion, micro-robotics for biomedical applications, and enhancing autonomy in multi-scale robotic systems. She aims to develop AGI-driven robots with super-human capabilities for healthcare and daily life. Education: PhD (Computing) and MRes (Surgery and Cancer), both from Imperial College London. Cross-disciplinary expertise spans Mechanical Engineering, Electrical Engineering, Clinical Sciences, Manufacturing Engineering, and Optical Physics. Lab leadership includes the Multi-Scale Embodied Intelligence Laboratory, with honorary research ties to Imperial’s Department of Electrical and Electronic Engineering. Research priorities emphasize AI-driven robotics for healthcare innovation, particularly in surgical robotics and biomedical applications. No specific awards or grants are listed, but her work aligns with Imperial’s strategic focus on translational technologies.