Find Academic Supervisors

Yadan LuoView profile

Senior Lecturer

• Machine Learning
• Domain Adaptation
• Domain Generalization
• +8 more

Dr. Yadan Luo is a Senior Lecturer and ARC DECRA Fellow at the School of Electrical Engineering and Computer Science, The University of Queensland. Her research focuses on robust machine learning and open-world 3D perception, particularly addressing domain shifts and generalization challenges in computer vision and multimedia analysis. BSc in Computer Science, University of Electronic Science and Technology of China PhD in Computer Science, The University of Queensland (2021) Her work leverages domain adaptation, few-shot learning, and active learning to improve real-world applications in autonomous driving, digital manufacturing, and infrastructure monitoring. She has published extensively in top venues like IEEE TPAMI , NeurIPS , and ICCV , with her 2018 paper on image analysis recognized as a Highly Cited Paper in Engineering. She leads the UQ Multimedia Lab (UQMM Lab), advancing data-centric paradigms and scalable foundation models. Recent publications highlight her contributions to test-time adaptation, 3D object detection, and efficient learning frameworks. She serves as Associate Editor for IEEE TCSVT and Area Chair for major conferences. Google PhD Fellowship 2020 ICT Young Achiever Award 2018 UQ Foundation Research Excellence Award Outstanding Service/Area Chair Awards at ACM MM 2024 Dr. Luo supervises PhD students in projects spanning neural radiance fields, autonomous driving, and multimodal 3D perception. Her industry collaborations include Logan City Council and Grains Research & Development Corporation.

• Biophysics
• DNA Replication
• Single-Molecule Techniques
• +4 more

Professor Nynke Dekker is a Professor of Biophysics at the University of Oxford and a Professorial Fellow at St Peter's College. Her research focuses on understanding biophysical mechanisms underlying DNA replication, chromatin dynamics, and viral RNA synthesis. She develops advanced microscopy techniques, including super-resolution imaging and single-molecule assays, to study molecular processes at high resolution. Key areas of expertise include nucleosome dynamics, replication fork progression, and the interplay between chromatin structure and enzymatic activity. Her work bridges fundamental biology with engineering advancements in microscopy instrumentation. Education details are not explicitly stated in the provided text, but her academic positions suggest a strong background in physics and biophysics. Research grants and lab affiliations are inferred from her active role in developing biophysical tools and studying replication processes. Her research interests span viral RNA polymerase mechanisms, DNA replication barriers, and the application of machine learning in automated cell analysis. She contributes to both theoretical models (e.g., Ising models for DNA compaction) and experimental innovations like Zernike polynomial-based distortion correction in microscopy. No formal awards or student advisees are listed in the provided text, though her extensive publication record indicates active collaboration and mentorship in the field. Her lab likely focuses on single-molecule studies using magnetic tweezers, optical torque wrenches, and high-throughput experimental setups.

Tansu CelikelView profile

Professor

• Neural Information Processing
• Cognitive Artificial Intelligence
• Computational Modeling
• +3 more

Tansu Celikel is a Professor and School Chair at the School of Psychology , Georgia Institute of Technology. His research focuses on neural information processing, cognitive AI, computational modeling, and neuroplasticity. He leads the Neuroloops lab, which explores perceptual learning through experimental and computational approaches in animals and humans. Key research contributions include identifying mechanisms of sensory-to-action transformation, developing real-time neuromodulation tools, and bridging animal/human studies through robotic control architectures. His lab has pioneered methods for millisecond-resolution behavioral quantification and neural interface systems. Publications emphasize interdisciplinary approaches spanning neuroscience, engineering, and AI. Current work targets closed-loop control of perceptual learning stages, from sensory input to motor execution. The lab's translational focus aims to apply neurobiological principles to robotics and cognitive enhancement technologies. Laboratory activities include hardware/software development for neural interfaces, computational modeling of sensory systems, and collaborative projects with robotics engineers. Experimental platforms involve rodents and human subjects to study shared perceptual mechanisms across species.

• Nuclear Physics
• Quantum Computing
• Effective Field Theory
• +3 more

Eduardo A. Coello Perez is a Researcher at Oak Ridge National Laboratory (ORNL), where he has held a JUNIOR position since 2022. Previously, he was a POSTDOC at Lawrence Livermore National Laboratory (LLNL, 2019) and Technische Universität Darmstadt (2016-2019). His research focuses on nuclear physics, quantum computing applications, and effective field theories for nuclear systems. Key areas include collective excitations in atomic nuclei, quantum algorithms for fluid dynamics, and neutrinoless double-beta decay studies. Collaborations include the LZ and XENON collaborations. His work bridges theoretical nuclear physics with computational methods, emphasizing precision calculations and interdisciplinary approaches. Notable contributions include studies on rotational bands in odd-mass nuclei and the integration of quantum computing resources into high-performance computing ecosystems. His publications span journals like Physical Review C , Journal of Physics G , and Future Generation Computer Systems .

• DNA Nanotechnology
• Aptamer Research
• Chemical Biology
• +3 more

Prof. Michael Famulok is a faculty member at the University of Bonn, affiliated with the Life and Medical Sciences Institute (LIMES) and the Faculty of Mathematics and Natural Sciences. His research focuses on DNA nanotechnology, aptamer development, and chemical biology, with an emphasis on creating functional biomolecular machines and molecular switches. His work explores interlocked DNA structures like rotaxanes and catenanes, aiming to develop controllable nano-devices for applications in diagnostics and therapeutics. Key projects include light-activated DNA nanoengines, self-regulating actuators, and aptamer-based systems targeting SARS-CoV-2 and cancer biomarkers. Research Interests: DNA Nanotechnology, Aptamer Selection, Chemical Biology, Molecular Switches, Bio-Hybrid Systems, Diagnostic Assays. Selected Publications Highlight Dynamic DNA Architectures, SARS-CoV-2 Aptamer Therapeutics, and Interlocked Nanostructures. His lab actively contributes to advancing nanoengineering and biotechnological applications.

Michele RucciView profile

Researcher

• Neuroscience
• Visual Perception
• Oculomotor Control
• +3 more

Michele Rucci is a researcher leading the Active Perception Laboratory, focusing on integrating experimental and theoretical approaches to investigate visual perception and its relationship with motor behavior. His work explores computational mechanisms of vision, particularly the role of eye movements in spatial encoding, and their implications for visual impairments. He develops advanced systems for gaze-tracking, visual display technologies, and brain-inspired robotics. Research interests include the interplay between sensory processing and motor control, oculomotor strategies in visual tasks, and the application of findings to biomedical engineering and machine vision systems. His studies have revealed precise oculomotor control mechanisms and their impact on visual acuity, as well as novel insights into foveal anatomy and retinal processing. Current projects involve high-resolution eye-tracking technologies, the dynamics of visual sensitivity across the fovea, and the cognitive influences on fixational eye movements. The laboratory actively recruits pre- and post-doctoral researchers to contribute to these interdisciplinary efforts.

Ellen DonovanView profile

Visiting Professor

• Radiation Oncology
• Medical Imaging
• Breast Cancer Treatment
• +4 more

Dr. Ellen Donovan is a Visiting Professor at the University of Surrey's School of Biosciences, affiliated with the Centre for Vision, Speech and Signal Processing (CVSSP). She also serves as a Research Adviser for the Research Design Service South East region since 2017. Her research focuses on advancing radiotherapy techniques for breast cancer patients, particularly leveraging medical imaging data to improve treatment outcomes and quantify radiomics features. Donovan has a PhD from the Institute of Cancer Research, University of London, and prior degrees from the University of Cambridge and the University of Aberdeen. Education: BA (Hons) Natural Sciences, University of Cambridge (1987) MSc Medical Physics, University of Aberdeen (1992) PhD, Institute of Cancer Research, University of London (2005) Her research interests include optimizing radiotherapy delivery, reducing treatment duration, and minimizing secondary cancer risks. She explores quantitative imaging data (radiomics) to correlate with treatment efficacy and patient outcomes. Donovan is a principal investigator in landmark trials like the FAST and IMPORT series, which evaluate hypofractionated radiotherapy and partial-breast irradiation. Her publications highlight advancements in adaptive radiotherapy, heart-sparing techniques, and breath-hold methods to minimize cardiac exposure. Recent work focuses on reproducibility in radiomics and clinical trial outcomes for breast cancer treatments. Awards: National Institute of Health Research (NIHR) Mentor for Clinical Academics Donovan supervises PhD and MSc students in radiomics and radiotherapy tool development. She teaches radiotherapy physics and clinical academic career development at institutions like the Princes Teaching Trust and British Institute of Radiology. Her lab, CVSSP, integrates interdisciplinary approaches to enhance medical imaging and signal processing in oncology. Future work emphasizes precision radiotherapy and AI-driven radiomics for personalized treatment planning.

Ronald AartsView profile

Associate Professor

• Robotics
• Machine Learning
• Motion Control
• +5 more

Ronald Aarts serves as an Associate Professor in Applied Mechanics & Data Analysis at Delft University of Technology, with over 25 years of research output spanning computational mechanics, robotics, and industrial mechanisms. His work bridges theoretical modeling and practical applications in high-precision engineering systems. His research portfolio emphasizes: Robotics for industrial automation and biomedical applications (e.g., BalRoom balance testing) Machine Learning integration in dynamic system modeling and control Motion Control systems for laser processing and robotic welding Flexure Engineering and compliant mechanisms design Sensor Integration in real-time industrial environments Analysis of his 2024-2025 publications reveals a strategic pivot toward laser-based additive manufacturing, with three papers on deformable mirror beam shaping for microstructure control in Directed Energy Deposition. Concurrently, he advances kinematic alignment techniques for parallel mechanisms and neural-network-driven inverse dynamics modeling, demonstrating cross-pollination between computational mechanics and AI. Professor Aarts has supervised 14 students and delivered 10 professional activities including keynote presentations on robot identification and rotordynamics. His BalRoom dataset for elderly balance assessment exemplifies interdisciplinary collaboration between mechanical engineering and biomedical research.

Paolo MontuschiView profile

Professor

• Computer Engineering
• Computer Arithmetic
• Computer Architecture
• +10 more

Paolo Montuschi is a Professor of Computer Engineering at Politecnico di Torino, Italy, and former Chair of the Control and Computer Engineering Department (2003–2011). He holds leadership roles in the IEEE, including Editor-in-Chief of the IEEE Transactions on Emerging Topics in Computing (2021–23) and Chair of the IEEE TAB Awards and Recognition Committee (2020–21). His academic career includes a PhD in Computer Engineering (1989) and full professorship since 2000. Research interests span computer arithmetic, computer architecture, graphics, and semantics in education. Notable contributions include work on decimal arithmetic, cryptography, error-tolerant systems, and virtual reality applications. He pioneered the first Italian/European IEEE-HKN chapter (Mu Nu) and received prestigious awards like the IEEE Computer Society Distinguished Service Award. Montuschi has advised notable students including Silvia Vitali (founder of Mu Nu Chapter), Luca Nassi (ARM), and Alessandro Sorniotti (IBM). His service spans over 30 roles in IEEE committees, focusing on publications, awards, and strategic planning. Current activities include advancing emerging computing topics and promoting interdisciplinary research through the GRAINS lab.

Eero P SimoncelliView profile

Professor

• Computational neuroscience
• Visual perception
• Auditory perception
• +3 more

Eero P Simoncelli is a Silver Professor at New York University, holding appointments in the Department of Neural Science, Mathematics, Data Science, and Psychology within the College of Arts & Science. He is affiliated with the Howard Hughes Medical Center and leads a research lab focusing on computational neuroscience and visual/auditory perception. Simoncelli earned his Ph.D. in 1993 from MIT. His research integrates statistical signal processing with neurobiological insights to understand sensory systems. Education: Ph.D. 1993, Massachusetts Institute of Technology. Research interests include computational modeling of visual and auditory perception, statistical image/signal processing, and neural coding mechanisms. His work bridges machine learning, neuroscience, and applied mathematics, with recent focus on motion detection, neural population coding, and hierarchical cortical models. Notable projects involve mapping spatial frequency selectivity in human visual cortex and developing biologically inspired AI architectures. Publications span topics like motion perception, neural circuit dynamics, and generative models for video prediction. His lab's work emphasizes practical applications in neuroscience and AI through tools like the Plenoptic stimulus synthesis platform. Simoncelli collaborates across disciplines to advance neuroAI integration and deep learning theory grounded in biological principles.

• Neuroscience
• Sensor-Motor Systems
• Vision
• +5 more

Douglas Wylie is a Professor in the Department of Biological Sciences at the University of Alberta. His research focuses on the neural basis of sensori-motor behaviors, particularly vision and cerebellar pathways in birds. He holds a PhD, MA, and BSc, and teaches courses like Perception (PSYCH 367), Animal Physiology II (ZOOL 242), and Neurobiology (ZOOL 342). His research explores optic flow processing in avian cerebellar systems and comparative neuroanatomy across bird species. Collaborations include Dr. Andrew Iwaniuk (Lethbridge University) studying brain evolution in relation to behavior. Notable work includes discovering hypertrophy of the pretectal nucleus Lentiformis Mesencephali in hummingbirds, linking it to hovering flight demands. Recent studies examine visual-cerebellar pathways, avian flight control, and sensory system adaptations. Wylie has contributed to over 50 publications since 2017, covering topics like optic flow encoding, cerebellar architecture, and evolutionary neurobiology. His lab integrates neurophysiology, anatomy, and behavioral studies to understand how sensory inputs guide motor outputs in birds.

Dimos V. DimarogonasView profile

Professor

• Multi-Agent Control Systems
• Robot Navigation
• Task Planning
• +11 more

Dimos V. Dimarogonas is a Professor of Automatic Control at the Division of Decision and Control Systems , School of Electrical Engineering and Computer Science , KTH Royal Institute of Technology . His research focuses on multi-agent control systems, hybrid systems, and formal verification with applications to robotics and autonomous systems. Alumnus of National Technical University of Athens (NTUA) Postdoctoral experience at KTH and MIT Research areas include: Multi-agent coordination under temporal logic specifications Hybrid control and planning for autonomous robots Formal verification of safety-critical systems Networked control with limited communication Robust distributed control protocols Applications to precision agriculture, underwater vehicles, and space robotics Recent publications emphasize stochastic control , funnel-based safety , and transient control for leader-follower networks. Scientific accolades include ERC Consolidator Grant (2019) , Wallenberg Academy Fellow (2015) , and ERC Starting Grant (2014) . Supervises numerous PhD students and postdocs, with former advisees now holding academic positions at institutions like Caltech, MIT, and Oxford.

Chris PhillipsView profile

Associate Professor

• Internet Technologies
• Optical Networking
• Network Security
• +5 more

Dr. Chris Phillips is a Reader in the School of Electronic Engineering and Computer Science at Queen Mary University of London. He holds a BEng in Telecommunications Engineering and a PhD in Telecommunications from Queen Mary. His roles include Director of Recruitment and Admissions for EECS, Programme Director of Computer Systems Engineering, and member of the Networks Research Group. His research focuses on Internet Technologies, Optical Networking, Network Security, and Energy-Efficient systems, with emphasis on resilient communication, wireless sensor networks, and nomadic computing. Education: BEng Telecommunications Engineering (1st Class Honours), Queen Mary University of London (1984–1987); PhD in Telecommunications, Queen Mary University of London (1987–1991). Professional experience includes roles at Bell Northern Research, Siemens–Roke Manor Research, Nortel Networks, and academic leadership at Queen Mary since 2000. He has supervised over 20 PhD students and contributed to multiple research grants, including projects on energy management in wired networks and resilient overlay systems. Research Interests: Internet protocols, optical networking, network security, energy efficiency, wireless sensor networks, and resilient communication systems. His work spans theoretical advancements and practical implementations, with applications in healthcare, agriculture, and vehicular systems. Recent publications explore IoT optimization, cooperative routing in MANETs, and energy-efficient optical networks. Grants and Awards: Secured funding from EPSRC, Royal Society, Nortel, Nokia, and the UK-China Government Office for Science. Notable grants include the EPSRC-funded project on machine learning in optical networks and Royal Society collaborations on intelligent connection management. Teaching: Currently teaches Computer Architecture and Networks (Postgraduate) and Microprocessor Systems Design (Undergraduate). Previously lectured on topics like MPLS networks, G-MPLS, and real-time transport protocols. His teaching integrates practical lab work with theoretical frameworks, emphasizing hands-on experience with microcontrollers and network protocols. Labs/Teams: Active member of the Networks Research Group, collaborating with institutions like Technical University of Denmark and University of Girona. His research team focuses on developing innovative solutions for network resilience, energy efficiency, and distributed systems.

Michael OramView profile

Lecturer

• Neurophysiology
• Visual Information Processing
• Neural Networks
• +3 more

Dr. Michael Oram is a Lecturer at the University of St Andrews, School of Psychology and Neuroscience. He holds a Ph.D. in Psychology/Neurophysiology from the University of St Andrews, a B.Sc. in Zoology from the University of Bristol, and an M.Sc. in Biological Computation from the University of York. His research focuses on neurophysiological mechanisms underlying behavior, particularly primate visual information processing and temporal aspects of neural data. He integrates neurophysiological findings with computational modeling to advance understanding of sensory mechanisms. Education: Ph.D., Psychology/Neurophysiology, University of St Andrews B.Sc., Zoology, University of Bristol M.Sc., Biological Computation, University of York Research Interests: Neurophysiology of visual processing Temporal dynamics of neuronal activity Neural networks and computational modeling Primate behavior and social cognition Neuronal response latency and adaptation Scientific Awards: Honorary Research Fellow, Institute of Adaptive & Neural Computation, University of Edinburgh (2007) Advising/Grants: No formal advisee list provided; contributions include interdisciplinary collaborations. Labs/Teams: Institute of Behavioural and Neural Sciences (IBANS) Centre for Higher Education Research

Ioannis GeorgilasView profile

Senior Lecturer

• Robotics
• Medical Robotics
• Agricultural Robotics
• +5 more

Ioannis Georgilas is a Senior Lecturer in the Department of Mechanical Engineering at the University of Bath. He is affiliated with the Centre for Bioengineering & Biomedical Technologies (CBio), The Foundry: Centre for Digital, Manufacturing & Design Innovation, and the Bath Institute for the Augmented Human. His research focuses on the design and development of robotic systems for healthcare and agricultural applications. Key areas include safety certification of medical robots, control strategies for complex systems, and precision agriculture robotics. He actively supervises doctoral students and has secured funding from organizations such as the Engineering and Physical Sciences Research Council (EPSRC), Cancer Research UK, and the National Institute for Health Research (NIHR). Georgilas' work intersects with UN Sustainable Development Goals, particularly in advancing healthcare technologies and sustainable agriculture. His projects include developing image-guided surgical robotics, adaptive control for compliant continuum robots, and robotic solutions for composite material manufacturing. He collaborates internationally, contributing to advancements in robotic safety, human-robot interaction, and precision agriculture. His research outputs span robotics control, medical device validation, and material characterization. Notable projects include a robotic test rig for prosthetic joints, closed-loop testing frameworks for composite materials, and a drill guidance system for orthopaedic surgery. Georgilas emphasizes interdisciplinary approaches, integrating mechanical engineering, AI, and biomedical sciences to address real-world challenges. His lab and team focus on translating innovative robotic concepts into practical applications, ensuring rapid clinical or industrial adoption. Collaborations with industry and medical institutions underpin his commitment to bridging research and real-world impact.