جستجوی استاد راهنمای دانشگاهی

Jordan Viceمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Machine Learning
• Explainable AI
• +۷ مورد دیگر

Jordan Vice is a Research Fellow at The University of Western Australia's School of Physics, Maths and Computing, specializing in Computer Science and Software Engineering. They hold a Ph.D. in Mechatronic Engineering from Curtin University (2023) and a 1st Class Honours degree in the same field (2020). Their research focuses on AI transparency, fairness, security, and reliability, with expertise in generative models, explainable AI, and robotics. Education: Ph.D. in Mechatronic Engineering (2020-2023), Curtin University, Thesis: Accountable, Explainable Artificial Intelligence Incorporation Framework for a Real-Time Affective State Assessment Module Bachelor of Mechatronic Engineering (2015-2019), Curtin University, Thesis: Bi-modal Affect-Based Authentication Machines Research Interests: AI ethics, generative models, cybersecurity in AI systems, facial expression analysis, and AI applications in healthcare. They advocate for transparent and accountable AI deployment while addressing security and privacy challenges. Recent work explores bias quantification in text-to-image models and backdoor attacks in generative systems. Key Trends in Publications: Focus on adversarial machine learning, generative model vulnerabilities, and ethical AI frameworks. Notable contributions include frameworks for real-time affect assessment and methodologies to quantify bias in text-to-image systems. Awards: Chancellor's Commendation (2023) Proxima Consulting Prize (2020) RTP Scholarship (2019) Advising & Grants: No explicitly listed advisees or grants, though their work suggests involvement in collaborative research projects. Labs/Teams: Affiliated with the School of Computer Science and Software Engineering at UWA, contributing to interdisciplinary AI research groups.

Chris Eliasmithمشاهده پروفایل

استاد

• Theoretical Neuroscience
• Computational Neuroscience
• Neuromorphics
• +۶ مورد دیگر

Chris Eliasmith is a Professor jointly appointed in the Systems Design Engineering and Philosophy departments at the University of Waterloo, with a cross-appointment to Computer Science. He is the Founding Director of the Centre for Theoretical Neuroscience and holds the Canada Research Chair in Theoretical Neuroscience. His research focuses on mathematical modeling of neural systems, including the Neural Engineering Framework (NEF) and Semantic Pointer Architecture (SPA), which underpin the world’s largest functional brain simulation, Spaun. He leads the Computational Neuroscience Research Group (CNRG), advancing neuromorphic computing, spiking neural networks, and cognitive modeling. Education: PhD in Neuroscience & Psychology (2000), Washington University in St. Louis MA in Philosophy (1995), University of Waterloo BASc in Systems Design Engineering (1994), University of Waterloo Research: His work integrates theoretical neuroscience with practical applications in robotics, AI, and neuromorphic hardware. Key contributions include the NEF, Spaun, and innovations like the Legendre Memory Unit (LMU) and Spatial Semantic Pointers (SSPs). His lab explores adaptive neural systems, decision-making models, and biologically plausible machine learning algorithms. Teaching: Recent courses include SYDE 556 (Simulating Neurobiological Systems), SYDE 750 (Topics in Systems Modelling), and PHIL 356 (Intelligence in Machines, Humans, and Other Animals). Awards: 2015 NSERC Polanyi Prize Labs & Projects: The CNRG develops tools like Nengo for simulating large-scale neural systems and collaborates on neuromorphic hardware platforms such as Loihi. Current projects span neural robotics, cognitive architectures, and biologically inspired AI systems.

• Robotics
• Machine Learning
• Tactile Sensing
• +۴ مورد دیگر

Adam Spiers is an Assistant Professor in Robotics and Machine Learning at the Department of Electrical and Electronic Engineering, Imperial College London. He leads the Manipulation and Touch Lab, focusing on bio-inspired robotic manipulation, prosthetics, and haptic interfaces for navigation assistance. Focuses on robot manipulation inspired by biological systems Develops robotic hand hardware, sensing, and control frameworks Researches upper-limb prosthetics and shape-changing haptic interfaces His work spans hardware design, sensor development, and machine learning techniques applied to robotic manipulation and human-robot interaction. Current projects include tactile sensing systems and prosthetic limb analysis. Recent publications emphasize tactile perception, object recognition, and haptic navigation systems. Key trends include barometric sensor applications, diffusion-based imitation learning, and proprioceptive feedback mechanisms. His career includes previous positions at Max Planck Institute for Intelligent Systems, Yale University, Bristol Robotics Laboratory, JET, and University of Reading.

• Computer Vision
• Artificial Intelligence
• Robotics
• +۴ مورد دیگر

Randal C. Nelson is an Associate Professor in the Department of Computer Science at the University of Rochester , where he has been employed since 1988, transitioning from Assistant to Associate Professor in 1994. His research focuses on Computer Vision , Artificial Intelligence , and Robotics , with a particular emphasis on motion analysis, object recognition, and real-time visual systems. Education: Ph.D. in Computer Science from the University of Maryland (1988), thesis on Visual Navigation M.S. in Computer Science from the University of Maryland (1985) B.S. in Physics with Honor from the University of Wyoming (1981), and a second B.S. in Mathematics (1982) Research Interests span Computer Vision , Machine Learning , and Robotics , with key contributions in temporal texture analysis , perceptual grouping hierarchies , and appearance-based 3D object recognition . His work explores how visual behavior can inform intelligent systems, emphasizing efficiency through selective information processing. Recent Publications highlight advancements in tracking objects using temporal cues, recognizing non-rigid motion, and developing robust visual systems for cluttered environments. Collaborations with students like Andrea Selinger, Ramprasad Polana, and Brandon Sanders have produced pioneering studies in 3D recognition and robotic manipulation .

Siddhartha Dattaمشاهده پروفایل

پژوهشگر ارشد

• Distributed Machine Learning
• Model Adaptation
• Cybersecurity
• +۴ مورد دیگر

Siddhartha Datta is a Researcher at the University of Oxford's Department of Computer Science, specializing in distributed machine learning and adaptive systems. His research develops end-to-end solutions for model training, security, and deployment. Key research areas include: Adaptive learning algorithms for dynamic environments Defense mechanisms against adversarial attacks Human-centered AI interfaces and tools Cross-reality systems blending digital/physical spaces Efficient model compression techniques Current projects investigate prompt engineering for generative models, online learning under data drift, and 3D object detection refinement. His work combines theoretical frameworks with practical implementations, resulting in tools like GreaseTerminator for digital sovereignty and DeepObfusCode for source protection. Datta has collaborated with Google and Cornell University during his doctoral studies. His open-source contributions include neurocogpy (ECoG processing) and Polysemy Word Tagging Tool, demonstrating commitment to accessible research tools.

• Applied Mathematics
• Engineering Education
• Computational Mathematics
• +۳ مورد دیگر

Ana M. Puig Montada is a researcher at the Universitat Politècnica de Catalunya (UPC), affiliated with the Departament de Matemàtica Aplicada II and the GRAA research group. Her roles include academic research and teaching in applied mathematics, engineering education, and computational methods. She is part of the ETSEIAT engineering school in Terrassa, Spain. Her educational background includes a doctoral thesis on textual corpus analysis, demonstrating interdisciplinary expertise in both mathematics and linguistics. She has led or participated in numerous research projects focused on energy efficiency, thermal management, and robotics. Notable projects include 'Innovative cooling system for embedded power electronics' (2020) and 'Processes and living lab for industry energy efficiency' (2019). Her research interests span applied mathematics, engineering pedagogy, and computational tools. She has authored textbooks on mathematical software like Maple and contributed to conferences on educational methodologies in engineering. She received the 'III CONCURS DE MATERIAL DOCENT DE L'ETSEIT' award in 1994 for educational materials. Her work integrates engineering education with technical innovation, emphasizing practical applications of mathematics in robotics, thermal systems, and sustainable technologies. She collaborates with departments like Enginyeria Mecànica and Màquines i Motors Tèrmics, reflecting her cross-disciplinary approach.

• Event-Driven Control
• Cyber-Physical Systems
• Robotics
• +۶ مورد دیگر

Sylvain Durand Chamontin serves as an Associate Professor at INSA Strasbourg, affiliated with the ICube research laboratory (UMR 7357) and the AVR (Automation, Vision, Robotics) team. His teaching encompasses advanced automation (anti-windup, Smith predictor, LQ control), embedded systems/IoT, motorization/axis control, linear automation (state feedback, observers), and sequential automation (GRAFCET, GEMMA) for electrical engineering, mechatronics, and mechanical engineering students across 2nd–5th year programs. His research centers on frugal design and control of embedded cyber-physical/robotic systems under resource constraints, with a dedicated focus on non-periodic sampling and event-driven techniques . Key domains include event-driven control architectures, dynamic vision sensor-based visual servoing, aerial robotics (UAVs/aerial manipulators), and swarm robotics. This work systematically reduces computational load, communication overhead, and energy consumption while maintaining robust performance in resource-limited environments—critical for embedded implementations in drones and cyber-physical systems. Analysis of Durand's 15 most recent publications (2022–2025) reveals a dominant trend in event-driven control for robotics, increasingly integrating machine learning for adaptive tuning. His work targets practical applications in aerial robotics, including UAV stabilization under ground effects, elastic-suspension aerial manipulation, and event-based visual servoing. A strong emphasis on frugality permeates techniques like non-periodic sampling and resource-aware control strategies, directly addressing hardware limitations in embedded platforms. Durand mentors award-winning PhD students including M. Pivert (Best Student Paper Award, IFAC Robotics 2025), T. Paul (i-PhD Innovation Contest 2022), and A. Yiğit (Best PhD Award in French Robotics 2021). He leads multiple ANR-funded projects: e-VISER (event-driven visual control, 2018–2021), DexterWide (cable robots, 2015–2018), and current initiatives eSWARM (modular UAVs, 2023–2025), muteSWARM (acoustic swarm control, 2023–2027), STRAD (street art drone, 2022–2026), TIR4sTREEt (urban micro-climatology, 2022–2026), and dark-NAV (GPS-denied navigation, 2021–2025). Within ICube's AVR team, Durand drives laboratory development of the dextAIR robot (omnidirectional aerial manipulator with elastic suspension) and embedded control systems for cable-driven parallel robots and swarm robotics. His experimental work emphasizes real-time implementation, energy efficiency, and frugal engineering principles—translating theoretical event-driven control into hardware solutions for resource-constrained robotic applications.

• Autonomous Mobile Robots
• Computer Vision
• Reinforcement Learning
• +۵ مورد دیگر

Dr. Jaime Boal Martín-Larrauri is an Associate Professor at the School of Engineering (ICAI) of Comillas Pontifical University, affiliated with the Electronics, Control and Communications Department. He holds a PhD in Engineering Systems Modeling (2014) and coordinates the M.Eng. in Intelligent Industry since 2019. His research focuses on robotics, computer vision, reinforcement learning, IoT, energy efficiency, and Industry 4.0 applications. He co-founded Stemy Energy (2018–2024) as CTO, developing energy efficiency solutions. Education: PhD in Research in Engineering Systems Modelling, Comillas Pontifical University (2014) M.Sc. in Research in Engineering Systems Modelling, Comillas Pontifical University (2012) Industrial Engineer (Electronics), Comillas Pontifical University (2010) Research Interests: His work integrates hardware-software systems, emphasizing robotic control, energy-efficient IoT platforms, and AI-driven solutions for industrial automation. Key projects include drone detection systems, smart energy grids, and reinforcement learning for industrial robots. Publications & Trends: Recent articles emphasize robotic learning, energy efficiency, and AI interpretability. Notable contributions include reinforcement learning robustness improvements and IoT energy platform architectures. Awards: Multiple Chair for Smart Industry Awards (2021–2024) for outstanding student projects under his supervision Extraordinary End-of-Degree Award (2011) Grants & Labs: Lead projects funded by ENDESA, Ferrovial, MIT, and the Madrid Regional Government. Active in the Institute for Research in Technology (IIT), collaborating on robotics and energy systems. Labs/Teams: Contributes to the IIT’s robotics and IoT research groups, focusing on autonomous systems and smart industry applications.

• Virtual Reality Applications
• Human-Computer Interaction
• Medical Technology
• +۳ مورد دیگر

Margarita Vinnikov is an Assistant Professor in the Department of Informatics at the New Jersey Institute of Technology (NJIT), part of the College of Computing Sciences. Her research focuses on immersive technologies such as Virtual Reality (VR) and Augmented Reality (AR), with applications in medical assistance, education, and human-computer interaction. She explores topics including gaze-contingent displays, visual fatigue mitigation, and the integration of VR into surgical training and K-12 education. Her work emphasizes user-centered design principles and interdisciplinary collaboration. Notable collaborations include studies on AR surgery assistance using HoloLens and VR-based ontology systems for biomedical education. Her research has been featured in media coverage related to VR crime scene technology, forensic conferences, and AI in education. Key research interests include improving spatial attention through multimodal displays, optimizing visual comfort in head-mounted devices, and leveraging VR for cognitive learning efficiency. Recent projects highlight the application of VR in teaching binary counting to middle school students and analyzing urban devotion through gaze-tracking studies. Vinnikov has advised undergraduate projects on interdisciplinary VR development and contributed to courses like IT 485: Cross Reality (XR) Design. Her work frequently intersects with medical technology, such as AR anatomical visualization for surgical support, and human factors engineering, including studies on quadcopter piloting latency effects.

Hasan Poonawalaمشاهده پروفایل

استادیار

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

Hasan Poonawala is an Assistant Professor in the Department of Mechanical Engineering at the University of Kentucky since 2018. His research focuses on autonomy and control systems for robotic and mechanical systems, integrating artificial intelligence (AI) and machine learning (ML) for safe and stable operation in uncertain environments. Appointments: 2018–Present: Assistant Professor, University of Kentucky 2015–2018: Postdoctoral Fellow, University of Texas at Austin 2014–2015: Postdoctoral Researcher, University of Texas at Dallas Research Interests: His work emphasizes the feedback between robot dynamics and AI/ML tools, with applications in autonomous control, barrier function design, invariant set estimation, and stability verification for dynamical systems. Specific areas include ReLU neural networks, hybrid systems, and sensor-driven control. Scientific Awards: Notable recognition includes the EAGER grant for robust robotic manipulation (2023).

• Robotics
• Human-Robot Interaction (HRI)
• Machine Learning
• +۵ مورد دیگر

Weria Khaksar is an Associate Professor at the Department of Mechanical Engineering and Technology Management at the Norwegian University of Life Sciences (NMBU), Faculty of Engineering, Science and Technology. Her research focuses on advanced robotics applications, particularly in healthcare, navigation, and sensor technologies. She specializes in Human-Robot Interaction (HRI), Machine Learning, and SLAM (Simultaneous Localization and Mapping) systems. Her work addresses ethical challenges in care robotics, privacy-preserving algorithms, and the integration of autonomous systems in healthcare and agriculture. Key research interests include: Development of care robots for elderly healthcare environments Integration of vision-based sensors and multi-modal datasets for human monitoring Optimization of motion planning algorithms using reinforcement learning and MPC Ethical and privacy considerations in human-robot collaboration Agricultural robotics for precision farming and forest mapping Her recent work (2021–2025) emphasizes: A qualitative review of 20 European elderly care robotics projects Advances in privacy-preserving HRI through multi-modal data Real-time SLAM systems for GNSS-interrupted environments Collision-free manipulation strategies for robotic arms No scientific awards are explicitly mentioned, but her extensive publication record demonstrates significant contributions to robotics research. She has advised no formally listed students, but her work engages interdisciplinary teams across engineering, healthcare, and environmental science. Her research is applied in: Robotics labs focusing on care systems and precision agriculture Multi-sensor integration for autonomous navigation Development of ethical frameworks for care robots

John Yao-Chon Chenمشاهده پروفایل

استاد

• Control Systems
• Robotics
• Optimal Control
• +۳ مورد دیگر

John Yao-Chon Chen is a Professor at Toronto Metropolitan University, where he has been since 1988. He holds a B.A.Sc. from the University of Ottawa and M.A.Sc./Ph.D. degrees from the University of Waterloo. He is a Professional Engineer (P.Eng.) licensed in Ontario. His research focuses on robotics control systems, including optimal control methodologies, fault diagnosis in robotic systems, trajectory planning, and obstacle avoidance strategies. He has contributed to foundational work in the application of numerical methods like B-splines for robot motion control. Key publications span topics from neural network-based fault diagnosis (1996) to time-optimal control structures (1989), demonstrating consistent engagement with core robotics challenges. His work bridges theoretical control systems and practical robotic implementation.

• Music Technology
• Interactive Media
• Digital Sound Design
• +۳ مورد دیگر

Nick Hwang is an Assistant Professor of Communication at the University of Wisconsin-Whitewater, affiliated with the Department of Communication within the College of Arts and Communication. His research focuses on music technology, interactive media, and collaborative performance systems, emphasizing innovations in sound diffusion, telematic music, and digital instrument design. He actively engages in interdisciplinary projects such as the Collab-Hub system for remote musical collaboration and the RhumbLine project exploring zoomorphic musical robots. Dr. Hwang’s academic contributions span over a decade, with notable work on the Actuated Embedded Musical Instrument (AEMI) and web-based creative coding education. His teaching philosophy prioritizes student-centered learning, tailoring material to individual backgrounds while pushing technical and artistic boundaries. Though no awards or grants are explicitly documented here, his publications reflect a commitment to advancing technologies at the intersection of music, computing, and human interaction. His lab environments and collaborative projects foster experimentation with emerging tools like mobile node controllers (MoNoDeC) and spatial audio systems. While specific student advisees or grant details are not listed, his teaching within media and game development programs underscores a dedication to preparing students for evolving creative industries.

Md Sultan Mahmudمشاهده پروفایل

استادیار

• Precision Agriculture
• Computer Vision
• Artificial Intelligence
• +۵ مورد دیگر

Md Sultan Mahmud is an Assistant Professor of Precision Crop Protection in the Department of Plant Pathology at the University of Georgia (UGA), with a courtesy faculty appointment in the School of Environmental, Civil, Agricultural, and Mechanical Engineering (College of Engineering). He holds a Ph.D. in Agricultural and Biological Engineering from Pennsylvania State University (2022), an M.Sc. in Agriculture (Engineering) from Dalhousie University (2019), and a B.Sc. in Agricultural Engineering from Hajee Mohammad Danesh Science and Technology University (2016). His research focuses on integrating computer vision, AI, robotics, and sensor technologies to develop precision solutions for plant disease and pest management. Key areas include smartphone applications, drone-based monitoring, early disease prediction models, and autonomous robotic systems for agricultural applications. He has received notable awards such as the Boyd-Scott Graduate Research Award (ASABE, 2022) and the Outstanding Dissertation Award from Penn State. Dr. Mahmud leads the Precision Crop Protection Laboratory and has secured grants from organizations like USDA NIFA, Southern SARE, and commodity boards. He actively publishes in journals like Sensors , Computers and Electronics in Agriculture , and AgriEngineering , with a focus on precision spraying systems, disease detection algorithms, and automation in crop production. Education: Ph.D., Agricultural and Biological Engineering, Penn State, 2022 M.Sc., Agriculture (Engineering), Dalhousie, 2019 B.Sc., Agricultural Engineering, Bangladesh, 2016 Research Themes: Computer vision for crop health monitoring AI-driven disease prediction models Autonomous robotic systems in agriculture Drone-based precision spraying Recent Grants: Optimizing Pecan Orchard Health via Drone Imagery (GA Commodity Board) Autonomous Laser-Based Weed Management (Southern SARE) UVC Light for Turfgrass Disease Control (USDA NIFA)

• Computer Vision
• Robotics
• Mixed Reality
• +۳ مورد دیگر

Zuria Bauer is a Lecturer in the Department of Computer Science at ETH Zürich. Her research focuses on advancing computer vision, robotics, and mixed reality technologies with applications in human-robot interaction, scene understanding, and assistive technologies. Key areas include monocular depth estimation, 3D scene reconstruction, and neural rendering techniques. Her work integrates theoretical advancements with practical implementations, such as enhancing robotic perception systems for real-world environments and developing intuitive mixed reality interfaces. Bauer has contributed to datasets like UASOL and frameworks like MaRINeR, which address challenges in novel view synthesis and object manipulation. Research trends in her articles emphasize cross-disciplinary approaches, combining deep learning with robotics to solve problems in healthcare accessibility (e.g., COMBAHO system) and environmental perception for autonomous systems. She explores both hardware-software co-design (e.g., low-cost wearable sensors) and algorithmic innovations (e.g., NeRF-based augmentation). While no formal awards are listed, her publications reflect sustained contributions to advancing perception technologies across dynamic scenes, robotic interaction, and assistive applications.