Find Academic Supervisors

Ronald C. ArkinView profile

Professor

• Artificial Intelligence
• Robotics
• Robot Ethics
• +6 more

Regents' Professor Ronald C. Arkin is a leading figure in robotics and AI at the School of Interactive Computing at the Georgia Institute of Technology . He directs the Mobile Robot Laboratory and serves as Associate Dean for Research in the College of Computing. His work bridges autonomy , ethical decision-making , and human-robot interaction . Ph.D. in Computer Science, University of Massachusetts, Amherst (1987) Former STINT Visiting Professor at KTH Stockholm (1997-1998) Sabbatical Chair at Sony Intelligence Dynamics Laboratory (2005) Member of Robotics and Artificial Intelligence Group at LAAS/CNRS (2005-2006) Arkin's research focuses on robot ethics , autonomous agents , and multi-robot coordination . He explores the integration of moral emotions and ethical frameworks in robotic systems, particularly for applications in patient-caregiver mediation and subterranean exploration . His work also addresses deception mechanisms and formal performance guarantees for autonomous missions. Recent publications highlight advancements in heterogeneous robot teams for DARPA challenges, multi-modal control interfaces , and bio-inspired deception . His research spans artificial circadian systems , robotic nudges , and legal mediation in human-robot interactions. Regents' Professor, Georgia Institute of Technology Arkin has advised numerous projects on robot ethics and autonomous systems , contributing to grants like the 2018 EAGER award for Misdirection in Robot Teams . He leads the Mobile Robot Laboratory , developing frameworks for robotic autonomy and ethical governance in diverse environments.

Fendy SantosoView profile

Academic

• cyber-physical systems
• cybersecurity
• artificial intelligence
• +6 more

Dr. Fendy Santoso is a Visiting Fellow at UNSW Canberra's School of Engineering and Information Technology, where he conducts cutting-edge research at the intersection of cyber-physical systems, cybersecurity, and artificial intelligence. His work focuses on developing robust security mechanisms for autonomous systems, particularly UAVs and robotics operating in adversarial environments. His educational background includes a PhD in Electrical Engineering from UNSW Sydney and a Master of Engineering (Electrical and Computer Systems) from Monash University. Dr. Santoso's research interests span cyber-physical systems security, adversarial machine learning, trustworthy autonomy, and AI-driven cybersecurity for autonomous platforms. His work specifically targets penetration-resistant architectures and secure decision-making frameworks for UAVs and robotic systems operating in dynamic, threat-prone environments. His approach integrates advanced fuzzy logic systems with deep learning techniques to create resilient control mechanisms that can withstand cyberattacks and operational uncertainties. Analysis of his recent publications reveals a consistent focus on applying type-2 fuzzy systems, deep learning, and negative imaginary control theory to solve critical challenges in autonomous systems security and control. His work demonstrates strong interdisciplinary connections between cybersecurity, control theory, and artificial intelligence, with particular emphasis on real-world implementation and experimental validation. Distinguished Early Career Travel Fellowship 2019, University of Wollongong ARC Linkage Project: Robust Defenses Against Adversarial Machine Learning for UAV Systems (2023) CSIRO Next Generation Grant for AgriTwins: Bridging Cyber-Secure Emerging Technologies and Data-Centric Twin Tech for Resilient Agriculture of the Future (2024) Dr. Santoso has secured over AUD 3 million in competitive research funding from prestigious sources including the Australian Research Council, U.S. Army Ground Vehicle Systems Centre, and Defence Science and Technology Group. He leads multi-disciplinary research teams and maintains strategic partnerships with defense and government agencies to translate theoretical advances into practical cybersecurity frameworks. His laboratory work centers around the Autonomous System Laboratory at UNSW Canberra, where he conducts experimental validation of security protocols for military ground robots and UAVs under realistic cyberattack scenarios.

Jorge CambaView profile

Associate Professor

• Intelligent Computer-Aided Design (CAD) Systems
• Digital Manufacturing Processes
• Digital Product Model Quality Assurance
• +5 more

Jorge Camba is an Associate Professor at the School of Engineering Technology and holds a courtesy appointment in the Department of Computer Graphics Technology at Purdue University . He also serves as a Senior Research Scientist (by courtesy) in the Department of Industrial Engineering at the University of Naples Federico II , Italy. PhD in Systems and Engineering Management (Universidad Politécnica de Valencia, Spain) MSc in Digital Media (East Tennessee State University) MSc in Computer Science (Universidad de Vigo, Spain) His research explores intelligent CAD systems , digital manufacturing , and mixed reality environments , focusing on model quality assurance , design intent communication , and collaborative design tools . Recent work investigates spatial cognition in CAD education , geometric variability analysis , and annotation-driven knowledge management . Key trends in his publications include parametric modeling strategies , 3D annotation systems , and XR applications in design evaluation. Awards include the Purdue Faculty Scholar (2021) and I3B Fellow (2021). He has presented at conferences on topics like Industry 4.0 , space habitat design , and digital product quality .

Haining WangView profile

Professor

• Cybersecurity
• Networking Systems
• Cloud Computing
• +5 more

Haining Wang is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His research focuses on cybersecurity, networking systems, cloud computing, and cyber-physical systems. He holds a Ph.D. from the University of Michigan (2003). His work addresses critical challenges in network security, IoT device fingerprinting, drone navigation security, and 5G/6G infrastructure vulnerabilities. Notable contributions include developing frameworks for detecting deceptive reviews, securing industrial IoT devices, and enhancing geofencing systems with 6G technologies. Wang's IEEE Fellow award (2020) recognizes his contributions to network and cloud security. His research also explores cloud gaming security, data center thermal vulnerabilities, and DNS privacy risks. He actively publishes on topics like container registry typosquatting, acoustic indoor localization, and encrypted DNS censorship analysis. Education: Ph.D., University of Michigan, 2003 Awards: IEEE Fellow (2020) Key Research Areas: Cybersecurity, Network Measurement, IoT Security, 5G/6G Systems Wang's recent work emphasizes securing emerging technologies like drone navigation systems and optimizing sensor placements in indoor environments. His projects often bridge theoretical frameworks with practical implementations in real-world networks and cloud infrastructures.

Venkat N. KroviView profile

Professor

• Robotics
• Autonomous Vehicles
• Human-Robot Interaction
• +5 more

Prof. Venkat N. Krovi serves as the Michelin Endowed Chair Professor of Vehicle Automation in the Departments of Automotive Engineering and Mechanical Engineering at Clemson University's College of Engineering, Computing and Applied Sciences (CECAS). He directs the Automation, Robotics and Mechatronics Laboratory (ARMLab) at the International Center for Automotive Research (CU-ICAR), focusing on smart embedded systems for autonomy in challenging environments. He earned his Ph.D. in Mechanical Engineering and Applied Mechanics from the University of Pennsylvania in 1998. His research leverages distributed autonomy and human-robot synergy to extend human capabilities, with applications spanning plant automation, consumer electronics, automobile, defense, and healthcare. The work emphasizes lifecycle treatment (design through verification) of robotic systems under uncertainty. Recent publications (2024-2025) demonstrate strong trends in digital twin frameworks for autonomous vehicle validation, sim2real transfer via reinforcement learning, and integration of large language models for editable simulations. Key themes include scalable cloud-based architectures, Koopman operator theory for robustness, and containerization for reproducible robotics development. His accolades include: National Science Foundation (NSF) CAREER Award Petro-Canada Young Innovator Award Multiple best paper awards at conferences and journals ASME Dedicated Service Award (2024) Prof. Krovi has advised doctoral students including Dr. Srivatsan Srinivasan (2024). His research receives substantial funding from NSF, DARPA, ARO, and industrial partners like Michelin. He leads the NSF I/UCRC RoSeHuB center and the AutoDRIVE ecosystem for autonomous driving education. As ARMLab director, he oversees projects including OpenCAV, the Robotics for AV Systems Bootcamp, and containerized terramechanics simulations. The lab specializes in mechatronic design, verification/validation frameworks, and human-autonomy coexistence studies for next-generation mobility solutions.

Nicola BezzoView profile

Associate Professor

• Robotics
• Autonomous Systems
• Control Barrier Functions
• +5 more

Nicola Bezzo serves as an Associate Professor at the University of Virginia with dual appointments in the Department of Systems Engineering and the Department of Electrical and Computer Engineering. He leads research through the AMR Lab and is affiliated with the university's Link Lab, focusing on autonomous systems safety and resilience. His work bridges theoretical control frameworks with practical robotic implementations, particularly in constrained and uncertain environments. Bezzo's research centers on developing fundamentally new approaches for safe and resilient autonomous operations, with three core thrusts: (1) Control Barrier Functions integrated with Lyapunov stability theory for provably safe navigation; (2) Epistemic planning frameworks that enable robots to reason under uncertainty using active inference principles; (3) Sim-to-real transfer techniques leveraging conformal mapping for robust deployment. His work consistently addresses the critical challenge of maintaining system integrity when operating under sensor limitations, communication constraints, and unexpected environmental disturbances. Recent publications demonstrate increasing focus on heterogeneous multi-robot coordination for emergency response scenarios and human-robot teaming where predictability is paramount. Analysis of Bezzo's 15 most recent publications reveals a strong trend toward adaptive safety frameworks that dynamically adjust to environmental uncertainty. Over 70% of his 2024-2025 work incorporates machine learning components (particularly Gaussian Processes and reinforcement learning) within traditional control architectures, creating hybrid approaches for resilient navigation. The research spans both aerial (UAV) and ground (UGV) platforms with growing emphasis on cross-domain coordination. A distinctive pattern is the development of 'recovery-first' paradigms that prioritize system restoration after failures rather than solely preventing failures. Bezzo directs the Autonomous Mobile Robotics (AMR) Lab and collaborates extensively with UVA's Link Lab, a cross-disciplinary research center focused on cyber-physical systems. His lab develops experimental testbeds for evaluating navigation algorithms in physically realistic environments, including constrained indoor spaces and communication-denied scenarios. Current projects involve robotic triage systems for disaster response and resilient swarm operations for infrastructure inspection, often featuring heterogeneous robot teams combining aerial and ground vehicles.

Alexander BrownView profile

Lecturer

• Robotics
• Vehicle Dynamics
• Human-Robot Interaction
• +5 more

Alexander Brown is a Lecturer in the Department of Mechanical Engineering at Lafayette College, specializing in dynamic systems and controls. His research bridges robotics, vehicle dynamics, and bio-inspired modeling, with a focus on human-robot and animal-robot interactions. B.S., Pennsylvania State University (2008) M.S., Pennsylvania State University (2012) Ph.D., Pennsylvania State University (2013) Research interests include robotics, vehicle dynamics, and mathematical modeling of physical systems. His work explores interactions between robots, vehicles, humans, and animals, with applications in autonomous driving and ethorobotics. Alexander's recent publications highlight trends in fish-robot interaction studies, autonomous vehicle safety, and simulation platforms like Webots. He emphasizes interdisciplinary collaboration and hands-on student engagement in his research and teaching. Outside academia, he builds and restores motorcycles, surfs in Monmouth County, N.J., and plays music with his band 'Imposters In Rome'.

• Edge Computing
• Fog Computing
• Cloud Computing
• +7 more

Riccardo Lancellotti is an Associate Professor at the Department of Engineering 'Enzo Ferrari' of the University of Modena and Reggio Emilia. His research focuses on Edge/Fog/Cloud Computing, Cyber Security, and Resource Management in distributed systems. He has extensive contributions in optimizing infrastructure performance, load balancing, and energy efficiency in cloud and fog environments. His work often combines theoretical models with practical simulations, addressing challenges like stale information in edge systems and heterogeneous resource allocation in smart cities. Key research areas include: Fog/Edge computing infrastructure design and optimization Cloud resource provisioning and SLA compliance Security for Industry 4.0 and automotive systems Genetic algorithms for service placement Scalable VM clustering and resource allocation Publications highlight trends in cloud/fog integration, robust game theory for microservices, and distributed load balancing under dynamic conditions. His work emphasizes practical applications, such as pharmaceutical distribution routing and smart city sensor management. No awards are explicitly listed, but his extensive publication record reflects recognition in the field.

• Artificial Intelligence
• Robotics
• Autonomous Systems
• +5 more

Nisar Ahmed is an Associate Professor at the University of Colorado within the Aerospace Engineering Sciences department. His research focuses on the intersection of Artificial Intelligence , Robotics , and Autonomous Systems , emphasizing decision-making under uncertainty, sensor fusion, and human-machine collaboration. Key research interests include: Active Inference for autonomous planning Decentralized Data Fusion in multi-robot systems Machine Self-Confidence and competency assessment Reinforcement Learning for spacecraft and robotic guidance Uncertainty Quantification in dynamic environments Recent publications highlight trends in Pareto-optimal decision-making , Bayesian optimization , contextual bandits , and trust calibration for UAS and planetary rovers. His work integrates probabilistic modeling with real-time autonomy , ensuring robustness in applications like search-and-rescue missions and lunar exploration. Contact: Nisar.Ahmed@Colorado.EDU

• Automation Engineering
• Mechanical Engineering
• Robotics
• +4 more

Pauli Mustalahti is a Research Fellow at Tampere University's Automation Technology and Mechanical Engineering department. His expertise lies in advanced control systems for heavy-duty robotic manipulators, hydraulic systems, and model-based control design. Mustalahti holds a Master of Science (Technology) in Automation Engineering from Tampere University (2016) and a Bachelor of Science (Technology) in the same field (2013). His research focuses on optimizing automated operations for industrial manipulators through innovative control strategies, including bilevel optimization frameworks, vision-aided positioning, and robust safety-constrained systems. Key contributions include improving long-reach manipulator accuracy via local calibration and enhancing electric linear actuator performance with safety protocols. Research interests: Robotics, Hydraulic Systems, Model-Based Control, Industrial Automation Notable achievements: Doctoral thesis on modular model-based control design for heavy-duty manipulators (2023) Collaborations: Global Fluid Power Society, IEEE, and international researchers in automation Mustalahti's work aligns with UN Sustainable Development Goals related to Industry, Innovation, and Infrastructure. His publications span peer-reviewed journals like IEEE Transactions on Automation Science and Engineering and conferences such as PEMC, addressing challenges in actuator safety, real-time control, and energy efficiency.

Ammar MianView profile

Associate Professor

• Statistical Signal Processing
• Machine Learning
• Riemannian Geometry
• +4 more

Ammar Mian is an Associate Professor at Université Savoie Mont Blanc, affiliated with the LISTIC lab and Polytech Annecy-Chambéry. He holds a PhD from CentraleSupélec (2016-2019) and conducted postdoctoral research at Aalto University (2019-2020). His research focuses on statistical signal processing, machine learning, and Riemannian geometry with applications in remote sensing and frugal computations. He leads the Qanat project, an experiment tracking tool for reproducible research. Research interests include covariance-based methods for SAR image analysis, robust detection algorithms for sonar and GPR systems, and optimization on Riemannian manifolds. His work emphasizes reproducibility in ML and efficient computational techniques for resource-constrained environments. Key contributions include real-time SAR time-series change detection, robust classification using second-order deep learning models, and novel methods for handling missing data in EEG signals. His recent articles (2023-2025) explore reproducibility frameworks, GPR-based object classification, and Riemannian geometry applications. No awards listed, but maintains active collaborations through LISTIC and industry partnerships. Advises students via internship programs (e.g., Federated ML energy cost analysis). Lab work involves developing open-source tools like Qanat for experiment management and reproducibility.

• Bio-inspired Sensors
• MEMS
• Neuromorphic Engineering
• +3 more

Claudia Lenk serves as Full Professor at Ulm University since 2024, leading the Biomedical Sensor Systems and Microsystems research group. Her work focuses on developing bio-inspired acoustic sensors to enhance human and machine hearing capabilities, particularly for speech processing in noisy environments through MEMS-based adaptive technologies. Education: Technical Physics, TU Ilmenau PhD in Biophysics (specializing in numerical/chemical modeling of atrial fibrillation mechanisms) Postdoctoral research developing MEMS-based artificial hair cells for hearing enhancement Her research integrates bio-inspired engineering with acoustic sensor design to create noise-robust systems that mimic biological hearing mechanisms. Key innovations include tunable MEMS resonators, neuromorphic auditory processing, and integrated signal pre-processing for hearing aids and robotics. This interdisciplinary approach bridges microsystems engineering, neuroscience, and auditory perception to address limitations in current speech processing technologies. Analysis of her 15 most recent publications (2020-2025) reveals a consistent trajectory toward adaptive neuromorphic acoustic systems. Dominant themes include resonance frequency control, dynamic range expansion through nonlinear dynamics, and bio-inspired feature extraction for low signal-to-noise ratio environments. These advancements target practical implementations in energy-constrained devices like hearing aids and autonomous systems. Scientific Awards: No awards documented in source materials Advising and Grants: Source materials contain no information regarding student supervision, research grants, or collaborative funding initiatives. Labs and Teams: She directs Ulm University's Biomedical Sensor Systems and Microsystems group, which develops cutting-edge sensor technologies for hearing applications, robotics, and speech processing systems through MEMS fabrication and neuromorphic computing approaches.

• Acoustic Signal Processing
• Blind Source Separation
• Digital Signal Processing
• +6 more

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

Hengky ChandrahalimView profile

Associate Professor

• Optics and Photonics
• Microelectromechanical Systems (MEMS)
• RF and Microwave Engineering
• +12 more

Hengky Chandrahalim is an Associate Professor of Electrical and Computer Engineering at the U.S. Air Force Institute of Technology (AFIT) , where he also serves as Faculty Director of the AFIT Nanofabrication & Characterization Facility . He is affiliated with the Graduate School of Engineering & Management and leads the Microsystems Laboratory. Education: Ph.D., Electrical and Computer Engineering, Cornell University M.Sc., Electrical and Computer Engineering, Cornell University M.Eng., Electrical and Computer Engineering, Cornell University B.Sc., Electrical and Computer Engineering, The Ohio State University His research interests span optics and photonics, MEMS, RF/microwave systems, optical sensing, and micro/nanosystems . He specializes in integrating microscale sensors with optical fibers, radiation-hardened MEMS, and optofluidic systems. His work combines advanced fabrication techniques like two-photon nanomachining with applications in aerospace, defense, and biomedical sensing. The trends in his recent publications emphasize optical fiber tip sensors, nonlinear damping in flow sensing, and radiation effects on MEMS resonators . His research demonstrates a strong focus on miniaturization, robustness under extreme environments, and novel transduction mechanisms in photonic and mechanical systems. Scientific Awards: Fellow, Institute of Physics (IOP) (2024) Fellow, Institution of Engineering & Technology (IET) (2023) IEEE Dayton Section Harrell V. Noble Award (2025) AFIT Civilian of the Year (2024) Arthur S. Flemming Award, Applied Science & Engineering (2024) SASE Professional Achievement Award (2022) Dean’s Distinguished Teaching Professor Award (2020–2021) He advises multiple graduate and undergraduate researchers , including Jeremiah C. Williams and David D. Lynes, and has secured significant recognition for both research and teaching. He has served as a mentor for national fellowship programs and student competitions. His lab, the Microsystems Laboratory , fosters innovation in sensor design, microfabrication, and photonics integration, contributing to both military and civilian technological advancement.

Polycarpou MariosView profile

Professor

• Neural networks
• Cyber-physical security
• Fault diagnosis
• +4 more

Professor Marios Polycarpou is a leading academic in intelligent systems and control engineering at the University of Cyprus, serving as Director of the KIOS Research and Innovation Center. He holds concurrent roles as Visiting Professor at Imperial College London and Founding Member of the Cyprus Academy of Sciences. His expertise spans neural networks, cyber-physical security, and critical infrastructure systems. Education: B.A. Computer Science & B.Sc. Electrical Engineering, Rice University, 1987 M.S. & Ph.D. Electrical Engineering, University of Southern California, 1989-1992 Research Interests: Intelligent systems and networks Adaptive learning control systems Fault diagnosis methodologies Machine learning applications Critical infrastructure resilience Awards: IEEE Neural Networks Pioneer Award (2016) ERC Advanced and Synergy Grants IEEE/IFAC Fellowships Cyprus Distinguished Researcher Award (2015) Grants & Leadership: Directed over 40 research projects Presidency roles in IEEE Computational Intelligence Society and European Control Association Edited prestigious journals including IEEE Transactions on Neural Networks Led major conferences: 2020 IEEE World Congress on Computational Intelligence and 2018 European Control Conference. Labs & Teams: Founder of KIOS Center (EU-funded excellence center) Developed SEMIoTICS semantic control framework