Find Academic Supervisors

Fabien MoutardeView profile

Professor

• Machine Learning
• Deep Learning
• Computer Vision
• +8 more

Fabien Moutarde is a Full Professor and Director of the Center for Robotics at MINES ParisTech (PSL University, Paris, France). He holds a PhD in Physics and an Habilitation to Direct Research in Engineering Sciences. Dr. Moutarde coordinates French engineering education at ParisTech_Shanghai (SPEIT) in China. Research Areas Deep Learning & Reinforcement Learning Computer Vision for Intelligent Vehicles Collaborative Robotics Traffic Analysis & Forecasting Human Gesture Recognition Recent Article Trends His work focuses on autonomous driving using Deep Reinforcement Learning, pedestrian trajectory prediction with spatio-temporal attention, and multi-modal localization techniques combining vision with Wi-Fi. Key applications include urban traffic analysis, collaborative robotics, and end-to-end driving systems. Leadership & Teaching Co-created specialized Machine Learning courses Pioneered Deep Reinforcement Learning lectures Led French-Chinese academic coordination Former UML/Java curriculum developer Publications With 28 h-index, his research includes 30+ IEEE/ACM publications on autonomous vehicles, gesture recognition, and traffic mining. Representative conferences: CVPR, NeurIPS, IROS, ITSC.

Andrew WestView profile

Researcher

• Robotics
• Nuclear Engineering
• Radiation Detection
• +3 more

Andrew West is a researcher affiliated with the University of Manchester, contributing to the Dalton Nuclear Institute. His work focuses on advancing robotics and autonomous systems for nuclear environments, particularly in radiation detection, mobile robot navigation, and hazardous environment exploration. Key areas include radiation mapping, sensor integration, and risk assessment in nuclear facilities. He has developed specialized robots like CARMA II and Vega for nuclear surveying and decommissioning tasks. Collaborations span international institutions such as JSI and LUNL, with datasets publicly available via Figshare. His research aligns with UN Sustainable Development Goals related to sustainable energy and industry innovation. Education: Background in robotics and nuclear engineering, though specific degrees are not detailed in the text. Research interests emphasize the practical application of robotics in nuclear decommissioning, including real-time radiation avoidance, sensor fusion, and multi-robot ecosystems. His work bridges theoretical modeling (e.g., Gaussian process regression) with practical field deployments, ensuring robots can safely operate in high-risk environments. Publications highlight advancements in radiation localization, sensor calibration (e.g., angular responses), and safety protocols for autonomous systems. The top-cited works focus on multimodal sensing and digital twin platforms for nuclear robot fleets, showcasing industry-academia partnerships. Grants & Projects: Contributions to projects like TORONE (Total Characterisation of Nuclear Environments) and the development of open-source platforms like Mona robot. West’s lab focuses on creating affordable, robust robotic solutions for nuclear challenges, with datasets publicly accessible to foster collaborative research.

Michael C. LuView profile

Professor

• Maternal and Child Health
• Public Health
• Health Equity
• +3 more

Dr. Michael C. Lu is currently the Dean of the School of Public Health at the University of California, Berkeley. Previously, he served as Director of the federal Maternal and Child Health Bureau under the Obama Administration, where he received the U.S. Department of Health and Human Services’ Hubert H. Humphrey Service to America Award in 2013. His academic career includes roles as a professor of obstetrics-gynecology and public health at UCLA, with research focused on racial-ethnic disparities in birth outcomes. As an obstetrician, he attended over 1,000 births and was repeatedly named a Best Doctor in America since 2005. He has contributed to National Academy of Medicine committees and co-authored the report Vibrant and Healthy Kids: Aligning Science, Practice, and Policy to Advance Health Equity . His education includes degrees from Stanford University, UC Berkeley, and UCSF. Research interests emphasize improving maternal and child health equity through life-course perspectives and advancing medical imaging technologies. He has pioneered innovations in MRI motion sensing, wireless implant communication, and computational imaging algorithms. His work bridges clinical practice, public health policy, and biomedical engineering. Awards include teaching recognition and federal service accolades. He collaborates on interdisciplinary teams to address global health challenges, leveraging both clinical expertise and technological advancements. Publications span maternal health equity frameworks and cutting-edge MRI methodologies, reflecting his dual focus on societal health disparities and medical technology. Current efforts at UC Berkeley aim to integrate public health strategies with emerging imaging and data science tools. Despite no listed advisees, his mentorship is evident through residency program leadership and training grants in maternal and child health.

Paola FlocchiniView profile

Professor

• Distributed Computing
• Distributed Algorithms
• Sense of Direction
• +3 more

Paola Flocchini is a Professor and University Research Chair on Intruder Agents and the Decontamination of Communication Networks at the University of Ottawa's School of Electrical Engineering and Computer Science. She also serves as Associate Director of the OCICS Program. Her PhD is from an unspecified institution. Her research focuses on distributed computing, algorithms for autonomous robots, distributed systems, and cellular automata. She has contributed to advancing theoretical frameworks for mobile robotic networks, fault-tolerant systems, and dynamic network exploration. Research Interests: Distributed Computing Mobile Entities and Autonomous Robots Algorithm Design for Dynamic Networks Black Hole Detection and Network Decontamination Asynchronous Algorithms and Schedulers Her recent work emphasizes computational power of energy-constrained robots, pattern formation under sequential schedulers, and fault localization in dynamic topologies. She has published extensively in venues like ICALP, IWOCA, and DISC. Her research bridges theory and application, addressing challenges in distributed systems, robotics, and network security.

Miles HansardView profile

Senior Lecturer

• Computer Vision
• 3D Scene Reconstruction
• Robotics
• +6 more

Dr. Miles Hansard is a Senior Lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science. His research focuses on 3D scene reconstruction, multi-view imaging, depth cameras, radar localization, and human vision. He specializes in geometric aspects of vision, image processing, and robotics applications. His teaching includes modules on Computer Graphics (for both postgraduate and undergraduate students) and Introduction to Multimedia Systems. These courses cover topics like 3D graphics algorithms, human perception of color, and multimedia system fundamentals. Dr. Hansard's work integrates sensor technologies such as time-of-flight cameras and millimeter-wave radar to improve 3D reconstruction and robotic systems. He contributes to projects like the GRIP software framework for robotic grasping and has published extensively in journals like IEEE Transactions on Image Processing and the International Journal of Neural Systems. He is affiliated with the Centre for Multimodal AI, where he collaborates on research involving sensor fusion, autonomous systems, and visual perception. His expertise bridges computer vision, robotics, and multimedia engineering.

Alberto Quattrini LiView profile

Associate Professor

• Robotic Exploration
• Multi-Agent Systems
• Underwater Robotics
• +1 more

Alberto Quattrini Li is Associate Professor of Computer Science at Dartmouth College, directing the Reality and Robotics Laboratory. His research develops autonomous systems for aquatic environments with applications in environmental monitoring and underwater archaeology. Current NSF-supported projects focus on multi-robot aquatic exploration and archaeological inspection systems. Research thrusts include surface vehicle obstacle avoidance in waterways, low-cost underwater sensing solutions, autonomous underwater construction, and laser-based air-underwater communication. Recent innovations include buoyancy-enabled manipulation systems and multi-sensor SLAM techniques for underwater operations. Quattrini Li advises six PhD students and collaborates with archaeologists through NSF grants. His laboratory prototypes systems using custom surface and underwater robotic platforms. No scientific awards are documented in the source materials.

Sivakumar RathinamView profile

Professor

• Motion Planning
• Autonomous Vehicles
• Collaborative Decision Making
• +3 more

Dr. Sivakumar Rathinam is a Professor in the Department of Mechanical Engineering at Texas A&M University, affiliated with the College of Engineering and the Computer Science & Engineering department. He holds certifications as a Fellow of ASME (2021) and Senior Member of IEEE (2019). His research focuses on motion planning for autonomous vehicles, collaborative decision-making, combinatorial optimization, and vision-based control systems. He leads the Autonomy Lab, addressing challenges in multi-agent systems, path planning, and rural autonomous vehicle accessibility. Education: Ph.D., Civil Systems Engineering, University of California, Berkeley (2007) M.S., Electrical Engineering & Computer Science, UC Berkeley (2006) M.S., Mechanical Engineering, Texas A&M University (2001) B.Tech., Mechanical Engineering, Indian Institute of Technology Madras (1999) Research Highlights: Dr. Rathinam's work spans autonomous vehicle navigation, UAV coordination, and sensor fusion for adverse conditions. His lab develops algorithms for multi-agent pathfinding and persistent monitoring missions. Recent efforts include rural road detection datasets (R2D2) and thermal/LIDAR sensor fusion for safety in challenging environments. Awards: Outstanding Faculty Contribution Award (2021) Best Paper Runner-Up, ICAPS (2021) Teaching Excellence Award (2012) Labs & Teams: Directs the Autonomy Lab, collaborating with industry partners through the Mechanical Engineering Industry Advisory Council. Active in NSF-funded projects on equitable rural autonomy and multi-UAV recharging frameworks.

• Communication Technologies and Culture
• Ethical and Societal Considerations of Technology
• Artificial Intelligence Governance
• +5 more

Dr. Pauline Hope Cheong is a **President's Professor** at Arizona State University (ASU), holding appointments in the **Hugh Downs School of Human Communication** and affiliated roles across multiple centers including the **Center on Technology, Data and Society** and **Center for Asian Research**. She is a **Senior Global Futures Scientist** and a **Global Futures Scholar**, reflecting her interdisciplinary focus on technology, culture, and society. **Education**: Dr. Cheong earned her Ph.D. from the Annenberg School for Communication and Journalism at the University of Southern California. She has also held a visiting postdoctoral fellowship jointly awarded by the US and UK research councils. **Research Focus**: Her work examines how emerging technologies like AI, robotics, and digital media reshape community interactions, governance, and religious practices. Key areas include smart cities, digital equity, and the intersection of technology with religious authority. Recent projects explore AI governance in nonprofits and faith communities, as well as cross-cultural digital divides. **Awards**: Among her honors are the **Master Teacher Award (Western States Communication Association)**, **Outstanding Faculty Mentor Award (ASU)**, and recognition as **The Great 48 in Arizona** for educational contributions. She is also a **President's Professor**, one of ASU's highest faculty accolades. **Service & Mentorship**: Dr. Cheong chairs doctoral colloquiums for the **Association of Internet Researchers** and **International Society of Media, Religion & Culture**. She co-directed the **Promoting Digital Equity in Tempe** initiative and advises undergraduates, graduate students, and international scholars. Her editorial roles span journals like the *Journal of Communication* and *Western Journal of Communication*. **Teaching**: She teaches courses on intercultural communication, research methods, and honors thesis supervision, emphasizing global and ethical dimensions of technology.

Connor McCannView profile

Assistant Professor

• Robotics Engineering
• Soft Robotics
• Wearable Robotics
• +3 more

Connor McCann is an Assistant Professor in the Robotics Engineering department at Worcester Polytechnic Institute (WPI). He leads the PRiSM Lab, which focuses on hybrid-stiffness mechanisms blending rigid and soft robotics to enhance robotic capabilities. His work integrates first-principles modeling with application-driven design for areas like robotic grasping, wearable robotics, and bioinspired systems. Education: Ph.D. and M.S. in Mechanical Engineering from Harvard University (2025, 2021), and B.S. in Mechanical Engineering from Yale University (2018). Research interests include the mechanics of rigid-soft material interactions, soft wearable robotics, bioinspired systems, and robotic manipulation. His lab emphasizes translating mechanical principles into functional prototypes for real-world applications. Key research trends in his articles include advancements in wearable robotics for industrial/medical use, aerodynamic control via textile metamaterials, and autonomous robotic exploration using low-cost hardware. His work bridges material science and robotics to create adaptive, high-performance systems. Labs/Teams: Director of the PRiSM Lab at WPI, focused on rigid-soft robotics innovation.

Fernando E. CasadoView profile

Researcher

• Machine Learning
• Robotics
• Human-Robot Interaction
• +5 more

Dr. Fernando E. Casado is a Researcher at the Personal Robotics Lab (PRL) within the Department of Electrical and Electronic Engineering at Imperial College London since March 2023. He holds a BSc in Computer Science (2017, University of Santiago de Compostela) with awards for academic excellence, an MSc in Artificial Intelligence Research (2018, Menéndez Pelayo International University), and a PhD in Computer Science (2022, USC) with Cum Laude distinction for his work on continual federated learning strategies. His research focuses on multi-robot and multi-user machine learning to enhance trustworthy human-robot interaction, addressing challenges such as concept drift, non-stationary data, and personalized robotic behavior. Key contributions include federated learning frameworks for assistive robotics, adaptive algorithms for heterogeneous data, and eye-gaze tracking for trust assessment in HRI. Publications span topics like federated learning, continual learning, and human-robot trust, with applications in assistive devices and smart environments. Awards include the Best Academic Record and Thesis Award (BSc) and the highest honors in his PhD. Casado’s work bridges theoretical machine learning with practical robotics, emphasizing privacy-aware systems and user-centered design. He collaborates internationally, including visits to PRL in 2021, and contributes to advancing adaptive algorithms for real-world robotic applications.

• Networking
• Operating Systems
• Distributed Systems
• +6 more

Kang Shin is a Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan's College of Engineering. His research spans multiple domains in computer science and engineering, focusing particularly on automotive security, wireless communications, and distributed systems.

• Human-Robot Interaction
• Explainable Robotics
• Assistive Robotics
• +5 more

Dr. Maryam Banitalebi Dehkordi is a Senior Lecturer in Robotics and AI at the University of Hertfordshire, UK. She holds a PhD in Perceptual Robotics from Scuola Superiore Sant'Anna (Italy) and a master's in Mechatronics from University Technology Malaysia. Her career spans academia and industry, with roles at institutions like Technical University of Munich and NavVis GmbH, as well as industry projects such as the Innovate UK-funded AgriRobot. Her research focuses on Human-Robot Interaction (HRI) , Explainable Robotics , Assistive Robotics , and autonomous systems . Key projects include DOC (navigation aid for visually impaired individuals) and AgriRobot (precision agricultural robotics). She has expertise in activity recognition via smartphone sensors, navigation systems, and social robotics interfaces. Publications (2012–2025) emphasize explainable AI in robotics, feature selection for activity recognition, and social behavior interpretation. Her work bridges theoretical robotics with real-world applications in healthcare, agriculture, and accessibility. No awards are explicitly listed, but her extensive collaboration network (Italy, Germany, UK) reflects interdisciplinary impact. She advises on robotics projects and has contributed to both academic journals and industry collaborations.

Thomas E. AhleringView profile

Professor

• Urologic Oncology
• Robotic Surgery
• Prostate Cancer
• +7 more

Dr. Thomas E. Ahlering is a Professor and Vice Chairman in the Department of Urology at the University of California, Irvine (UCI) School of Medicine. He is a leading expert in urologic oncology, specializing in robotic radical prostatectomy for prostate cancer, with over 2,500 surgeries performed. He previously served as Chief of Urologic Oncology at City of Hope and Chief of Urology at UC Irvine. His clinical and research work has earned him recognition as one of America’s Best Doctors since 1994 and as a Top 2% Medical Scientist globally. Dr. Ahlering's research interests center on urologic oncology , particularly robotic surgery , functional recovery after prostatectomy , and patient-reported outcomes . He has pioneered techniques in nerve-sparing and urinary anastomosis to improve continence and potency. His work has significantly contributed to the adoption and refinement of da Vinci robotic systems in urologic surgery. His scholarly output includes over 400 publications, with recent work focusing on surgical innovation, international training, patient selection, and long-term oncological outcomes. The articles reflect a strong emphasis on improving surgical precision, minimizing complications, and enhancing quality of life. Themes include technological evolution, global dissemination of robotic techniques, and patient-centered care. Scientific recognition includes: Lifetime Achievement Award in Robotic Surgery (North American Robotic Urology Symposium) Outstanding Faculty Achievement – Lauds and Laurels (UCI Alumni Association) Mentor of the Year (UCI Institute of Clinical and Translational Science) Top 2% of Medical Scientists in the World (Stanford Study) Consistently listed in America’s Best Doctors since 1994 Dr. Ahlering has mentored numerous trainees and residents, contributing significantly to education in urologic oncology. His lab and surgical team, often referred to as "The A-Team," operate at MiVIP Surgical Center and are known for their high coordination, patient-centered approach, and expertise in robotic prostatectomy. He continues to lead innovation in urinary diversion techniques such as the Indiana pouch and ileal neobladder.

Dirk ArnoldView profile

Professor

• Evolutionary Computation
• Optimization
• Constraint Handling
• +12 more

Dirk Arnold is a Professor in the Faculty of Computer Science at Dalhousie University, Halifax, Canada. His research focuses on evolutionary computation, optimization, and surrogate modeling, with applications in machine learning and digital media. He is actively involved in teaching and research, contributing to major conferences and journals. PhD, University of Dortmund (2001) MSc, Simon Fraser University (1997) Diplom, University of Dortmund (1995) His research interests lie in evolutionary algorithms, particularly evolution strategies, and their application to noisy and constrained optimization. He investigates constraint handling, surrogate modeling, and parameter adaptation mechanisms. His work bridges theoretical analysis and practical applications in image processing, tone mapping, and robotics. Recent publications show a strong trend toward surrogate-assisted optimization, constrained evolutionary algorithms, and applications in computer vision and graphics. His work is consistently published in top venues such as GECCO, PPSN, and IEEE Transactions on Evolutionary Computation. Scientific Awards: Best Paper Award, Continuous Optimization Track, GECCO 2015 Best Paper Award, ES/EP Track, GECCO 2013 Best Paper Award, PPSN XII 2012 Best Paper Award, ES/EP Track, GECCO 2010 Best Paper Award, PPSN IX 2006 Best Student Paper Award, ACM Symposium on Document Engineering 2014 Arnold has advised numerous students, many of whom are co-authors on his publications. He has received research grants supporting work in evolutionary computation and optimization, though specific grant details are not listed. He is a key member of research clusters in Human-Computer Interaction, Visualization & Graphics, and Algorithms & Bioinformatics. He leads a research group focused on evolutionary algorithms and optimization, collaborating with researchers such as H.-G. Beyer, N. Hansen, and S. Brooks. Future work includes advancing constrained and mixed-integer evolutionary optimization, improving surrogate models, and expanding applications in computer vision and HCI.

Evangelos E. MiliosView profile

Professor

• Visual Text Analytics
• Modelling and Mining of Networked Information Spaces
• Text Mining
• +8 more

Evangelos E. Milios is a Professor in the Faculty of Computer Science at Dalhousie University , Halifax, Nova Scotia. He has been a faculty member since 1998 and leads the MALNIS (Machine Learning and Networked Information Spaces) research group. He is affiliated with the Institute of Big Data Analytics and served as Scientific Director of DeepSense , an innovation hub for ocean data analytics. Education: PhD in Electrical Engineering and Computer Science, MIT (1986) SM & EE, MIT (1983) Dipl. Eng. in Electrical Engineering, NTUA, Greece (1980) His research focuses on visual text analytics, text mining, graph mining, social network analysis, and machine learning . He has made significant contributions to modeling and mining of networked information spaces, with applications in data science and AI. The recent publications reflect a strong trend in data mining, robotics, pattern recognition, and semantic analysis , particularly in log analysis, pose estimation, and information retrieval. His work bridges theoretical algorithms with practical applications in robotics and web technologies. Scientific Awards and Honors: Distinguished Research Professor (2017–2022) Killam Chair in Computer Science (2006–2011) Senior Member, IEEE Professional Engineer, Ontario (1998–2024) He has served in key administrative roles including Associate Dean, Research (2008–2017) and Director of the Graduate Program (1999–2002) . He has supervised numerous graduate students and taught a wide range of courses in AI, machine learning, data science, and networking. His research is supported by major grants and collaborations, including NSERC and industry partnerships. Research Labs and Teams: MALNIS – Focuses on machine learning and networked information spaces. DeepSense – Ocean data analytics and AI innovation. Institute of Big Data Analytics – Cross-disciplinary big data research.