Find Academic Supervisors

• Collective Animal Behavior
• Statistical Physics
• Biological Physics
• +5 more

James G. Puckett is a Professor in the Department of Physics and Astronomy at Gettysburg College, where he conducts research at the intersection of physics and biology. His work primarily focuses on collective behavior in biological systems, particularly insect swarms and fish schools, as well as granular materials and statistical physics. His research interests include collective animal behavior, statistical physics, biological physics, granular materials, and network analysis. Dr. Puckett employs advanced experimental techniques including multicamera imaging and tracking systems to study the motion of individual organisms within groups, developing mathematical models to explain emergent collective phenomena. His work has revealed important insights into pairwise interactions in insect swarms, adaptive long-range interactions, and thermodynamic analogies in collective animal behavior. Analysis of his publications shows a consistent focus on understanding how local interactions between individuals give rise to complex collective behavior. His research spans both biological systems (insect swarms, fish schools) and physical systems (granular materials), demonstrating the power of physics approaches to understand diverse phenomena. The interdisciplinary nature of his work bridges physics, biology, and mathematics. Throughout his career, Dr. Puckett has published in prestigious journals including Physical Review Letters, with research that has been cited over 45 times according to metrics shown in the repository. His collaborations include researchers from Yale University, Penn State, and other institutions, reflecting the collaborative nature of modern interdisciplinary research. Dr. Puckett's laboratory work involves sophisticated experimental setups for tracking individual organisms in controlled environments, combined with advanced data analysis techniques including time-frequency analysis, network analysis, and statistical modeling. His research has implications for understanding not only natural biological systems but also for developing principles applicable to robotics and artificial collective systems.

• Microfluidics
• Nanofluidics
• Biomedical Engineering
• +4 more

Dr Haotian Cha is a Research Fellow at Griffith University, affiliated with the School of Engineering and Built Environment - Civil and Environmental Engineering. He is currently a member of the Queensland Quantum and Advanced Technologies Research Institute (QUATRI) since 2025, and was previously affiliated with the Queensland Micro and Nanotechnology Centre from 2021 to 2025. Dr Cha's educational background includes a PhD in Engineering from Griffith University (January 2021-June 2024), a Master of Engineering in Mechanical Engineering from UNSW Sydney (July 2017-December 2019), and a Bachelor of Engineering from Nanjing University of Science and Technology in China (September 2012-June 2016). As an Early Career researcher, Dr Cha's primary research focuses on innovative Multiphysics Microfluidics technology, particularly inertial regime and dielectrophoresis (DEP), for micro/nano cell separation. His work spans several cutting-edge areas including bioparticle separation, circulating tumour cells (CTCs) liquid biopsy for cancer diagnosis and prognosis, flexible microfluidics for liquid transport, microfluidic nanoparticle synthesis, and the development of lab-on-a-chip biomedical applications. Recently, he has expanded his research into wearable devices, with emphasis on flexible microfluidic systems for liquid transport. Dr Cha's publication record demonstrates significant expertise in microfluidics and its biomedical applications, with over 20 journal articles in high-impact publications. His recent work shows a strong trend toward practical medical diagnostics applications, particularly for cancer detection through circulating tumor cell isolation and blood cell separation technologies. He has made notable contributions to inertial microfluidics, dielectrophoresis, viscoelastic microfluidics, and nanobubble technologies, with applications spanning from clinical diagnostics to environmental remediation. Dr Cha has received institutional support through the Griffith Sciences Early Career Researcher Travel Grant ($2,500), demonstrating recognition of his research potential. His collaborative publication pattern suggests active engagement with research teams across multiple institutions. Dr Cha maintains professional affiliations with two major research centers at Griffith University: the Queensland Micro and Nanotechnology Centre (2021-2025) and currently the Queensland Quantum and Advanced Technologies Research Institute (QUATRI). These affiliations position him at the forefront of advanced technology research in Australia, particularly in applying micro and nanotechnologies to solve complex biomedical and environmental challenges.

Ke AnView profile

Adjunct Professor

• Neutron Scattering
• Materials Science
• Residual Stress Analysis
• +7 more

Dr. Ke An serves as a Distinguished R&D Staff Scientist and Lead Scientist of the VULCAN instrument at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory while holding an Adjunct Faculty position in the Department of Materials Science at the University of Tennessee, Knoxville. With over two decades of experience in neutron scattering research, Dr. An leads cutting-edge investigations into material behavior under extreme conditions and develops advanced scientific instrumentation for materials characterization. Dr. An's educational background includes: Ph.D. in Engineering Science and Mechanics from Virginia Tech (2003) M.S. in Chemical Engineering from Tianjin University (2000) B.S. in Chemical Engineering from Tianjin University (1998) B.S. in Management from Tianjin University (1998) His research program focuses on neutron scattering studies of material systems under temperature extremes, magnetic fields, electrical currents, and complex mechanical loading. Dr. An investigates residual stress and deformation behavior in structural materials including high entropy alloys, additively manufactured alloys, high strength steel, and lightweight alloys. His work encompasses deformation mechanisms, structural phase transitions in magnetic shape memory materials, thermal mechanical integrity of engineering materials, and synthesis of energy storage and conversion materials. He has pioneered techniques for high spatial resolution neutron diffraction to study critical engineering components. Dr. An's publication record demonstrates consistent leadership in applying neutron diffraction to solve complex materials engineering challenges. His recent work shows increasing integration of machine learning with traditional neutron scattering methods, development of specialized instrumentation like the RICH system, and application of advanced characterization techniques to emerging materials including refractory high-entropy alloys and additively manufactured composites. His research bridges fundamental materials science with practical engineering applications across energy systems and advanced manufacturing sectors. Dr. An's scientific achievements have been recognized with numerous prestigious awards: Fellow of the Neutron Scattering Society of America (2024) RD 100 Award (2023) UT-Battelle Distinguished Researcher Award for career (2022) Nature Communications Metallurgy Paper Collection recognition (2023) Multiple Top 10 Neutron Scattering Achievements awards (2018-2022) Best Team Science Award for Additive Manufacturing (2023) As Lead Scientist of the VULCAN instrument, Dr. An directs significant research resources and collaborates extensively with industry partners through the Industry Applications Program. He coordinates the Materials & Engineering Science Initiative and serves as Point of Contact for the New Materials and Engineering Instrument at the Second Target Station. Dr. An also contributes to the scientific community as Associate Editor for Frontiers in Materials and Editorial Board Member for Scientific Reports, providing guidance on scholarly publications in materials science. Dr. An leads the VULCAN engineering materials diffractometer, a premier facility for in-situ and operando materials characterization at the Spallation Neutron Source. His team develops specialized equipment including the RICH (Robotic Interface Control & Handling) system for advanced sample manipulation during neutron experiments. He also oversees patent development related to neutron instrumentation, including the recently granted 'NEUTRONIC ENGINE' patent (US 11,768,128 B2, 2023), demonstrating his commitment to translating scientific discoveries into practical technological innovations.

Vahagn NikolianView profile

Assistant Professor

• Abdominal Wall Reconstruction
• Hernia Surgery
• Robotic Surgery
• +5 more

Dr. Vahagn Nikolian serves as an Assistant Professor in the Department of Surgery at Oregon Health & Science University (OHSU) School of Medicine. A board-certified general surgeon specializing in abdominal wall reconstruction and hernia management, he leads a multidisciplinary team at OHSU's Center for Health & Healing, advancing care through laparoscopic and robotic surgical techniques while integrating digital health innovations to improve patient outcomes. His educational journey includes a B.A. from the University of Southern California (2007), M.D. from Keck School of Medicine (2012), General Surgery residency at the University of Michigan (2019), and specialized fellowships in Trauma Research (University of Michigan, 2015-2017) and Complex Abdominal Wall Reconstruction (Columbia University, 2020). Board-certified by the American Board of Surgery (2020), he maintains active memberships in the Americas Hernia Society, European Hernia Society, and American College of Surgeons. Dr. Nikolian's research program focuses on transforming surgical care through technology, with three core pillars: optimizing hernia surgery outcomes via robotic and laparoscopic approaches, implementing telemedicine and digital health strategies across the surgical continuum, and advancing surgical education through AI-driven coaching systems. His work bridges clinical innovation with practical implementation, emphasizing patient-centered solutions for complex abdominal wall conditions. Analysis of his 60+ publications reveals a strategic evolution toward technology integration in surgery, with recent work establishing telemedicine frameworks for rural patient access, developing AI-assisted procedural assessment tools, and pioneering novel techniques like TAPPRA for incisional hernias. The research consistently targets high-impact areas: reducing surgical site infections, improving long-term surveillance, and validating textbook outcomes in emergency procedures. His distinguished recognition includes: National awards: ACS Excellence in Basic Science Research Award (2016), NY Presbyterian High Value Care Shark Tank Award (2020) Teaching honors: OHSU Faculty Flame Teaching Award (2021, 2022), Faculty Flame Mentor Award (2022) Prestigious fellowships: Coller Society Traveling Fellowship (2018), Alpha Omega Alpha Honor Society (2012) Specialized recognitions: Massey Conference Outstanding Poster Award (2015), Michigan Learning Environment Excellence Award (2017) As an active researcher and educator, Dr. Nikolian mentors surgical residents through OHSU's training programs while securing NIH funding for digital health initiatives. His collaborative approach extends to surgical societies and cross-departmental teams, developing standardized protocols for hernia care and telemedicine implementation. Current projects focus on AI-driven surgical coaching systems and expanding telesurgery applications for underserved populations. He operates within OHSU's integrated surgical ecosystem, collaborating with the Digestive Health Center and Center for Health & Healing teams to provide comprehensive care. His clinical practice emphasizes personalized treatment plans developed through patient-family-physician partnerships, with ongoing research conducted through the OHSU surgical innovation laboratory focused on technology-driven care transformation.

• Patient Safety
• Patient Engagement
• Human Factors Engineering
• +4 more

Dr. Amro N. Khasawneh serves as Assistant Professor of Industrial Engineering in Mercer University's School of Engineering since 2022. Previously, he held faculty positions at the University of North Carolina's Department of Radiation Oncology and was a Research Fellow at Johns Hopkins University's Armstrong Institute, establishing expertise in healthcare systems engineering. His educational credentials include: PhD in Industrial Engineering from Clemson University (2019) MS in Industrial Systems Engineering from Binghamton University (2016) BSE in Industrial Engineering from Jordan University of Science & Technology (2015) Dr. Khasawneh's research centers on human factors engineering applications in healthcare , with primary focus on patient safety and patient engagement . His work integrates Virtual Reality training systems , human-robot interaction , and behavioral modeling to optimize healthcare delivery, teleoperated systems, and online decision-making environments. This interdisciplinary approach bridges engineering principles with clinical practice. His extensive publication record (>30 articles) reveals strong trends in healthcare innovation, with recent work emphasizing VR applications for mental health, telemedicine systems, and web accessibility compliance. These publications span high-impact venues including Human Factors , JMIR , and Automation in Construction , demonstrating consistent contributions to engineering healthcare solutions. Notable recognitions include: Innovation Pilot Award from UNC Chapel Hill's Center for Health Innovation (2022) Student Member with Honors from Human Factors and Ergonomics Society (2019) Multiple Graduate Student Travel Awards from Clemson University (2018-2019) Best Paper Award from IISE's Supply Chain Division (2016) Dr. Khasawneh actively mentors undergraduate researchers through Mercer's service-learning initiatives and VR projects, with numerous student co-authors on publications. His Innovation Pilot Award demonstrates successful grant acquisition for healthcare system improvements. Current projects include international collaborations in Belize through Mercer on Mission and VR meditation applications for academic stress reduction. He leads interdisciplinary teams focused on healthcare technology development, including ADA compliance evaluations for telehealth platforms and field-based bacterial testing methodologies in developing regions, reflecting his commitment to practical engineering solutions for global health challenges.

Shalabh GuptaView profile

Associate Professor

• Cyber-physical Systems
• Data Analytics
• Information Fusion
• +9 more

Shalabh Gupta is an Associate Professor in the Department of Electrical & Computer Engineering at the University of Connecticut since August 2011. His research focuses on Cyber-physical Systems, Data Analytics, Information Fusion, Resilient Infrastructures, Distributed Intelligent Systems, Networked-control Systems, Swarm Robotics, Sensor Networks, Smart Grids, Unmanned Autonomous Vehicles, Adaptive Navigation & Path Planning, and Diagnostics & Prognostics in Complex Systems. Education: PhD in Mechanical Engineering (2006) - Pennsylvania State University MS in Electrical Engineering (2005) - Pennsylvania State University MS in Mechanical Engineering (2004) - Pennsylvania State University BTech in Mechanical Engineering (2001) - Indian Institute of Technology-Roorkee His research spans autonomous navigation in dynamic environments, sensor fusion for aerospace systems, and optimization in distributed networks. Recent work includes algorithms for adaptive motion planning (SMART-OC, SMART-3D), diver action recognition, and coverage path planning in unknown terrains. He has served as Associate Editor for Structural Health Monitoring - An International Journal (2010-present) and contributed to fault diagnosis frameworks in aerospace and electric drive systems. His lab, LinksLab (www.LinksLab.uconn.edu), develops technologies for resilient infrastructure and autonomous robotics.

• Human-Computer Interaction
• Augmented Reality
• Virtual Reality
• +6 more

Uwe Gruenefeld is an active researcher at the University of Duisburg-Essen, Germany, with a strong affiliation with OFFIS - Institute for Information Technology in Oldenburg. His primary research focuses on Human-Computer Interaction, particularly in the domains of Augmented Reality, Virtual Reality, and Mixed Reality systems. As a key contributor to the field, he has published extensively in top-tier venues including CHI, UIST, and IEEE Transactions. Dr. Gruenefeld's research primarily investigates visual and haptic techniques for improving user interaction in immersive environments. His work spans across multiple application domains including health technology, educational systems, and robotics. He has made significant contributions to understanding how users interact with cross-reality systems, developing novel interaction techniques for AR/VR, and exploring behavioral biometrics for continuous authentication in immersive environments. His recent publications demonstrate a strong trend toward practical applications of AR/VR technology, with emphasis on user identification through movement patterns, improving physical activity engagement, and developing more intuitive interaction methods for complex tasks. The research consistently shows a human-centered approach with practical implementations that address real-world challenges in immersive computing. Dr. Gruenefeld actively collaborates with numerous researchers and appears to mentor several PhD and Master's students, evidenced by his frequent co-authorship with junior researchers on significant publications. His work is characterized by strong empirical validation through user studies and technical innovation in interaction techniques.

Nasser Lashgarian AzadView profile

Professor

• Automation and Control Systems
• Autonomous Vehicles
• Reinforcement Learning
• +3 more

Nasser Lashgarian Azad is a Professor and Associate Chair (Graduate Studies) in the field of Automation and Control Systems at the University of Waterloo. His research focuses on advanced control strategies for autonomous and connected vehicles, including reinforcement learning, model predictive control (MPC), and cybersecurity. He specializes in vehicle dynamics, energy management systems, and decision-making algorithms for complex scenarios such as platooning, collision avoidance, and shared spaces. His work spans interdisciplinary applications in automotive, aerospace, and robotics, with contributions to hybrid electric vehicle optimization, cyber-physical systems security, and real-time trajectory control. Key areas of interest include autonomous navigation, resilient control systems, and the integration of AI with traditional control methodologies. Dr. Azad has published extensively on topics such as deep reinforcement learning for autonomous driving, secure vehicle platooning, and adaptive cruise control. His research emphasizes practical implementation, with experimental validations in domains like electric vehicle energy management, lane-changing algorithms, and roundabout navigation. He is actively involved in advancing control systems for connected and automated vehicles, addressing challenges in safety, efficiency, and scalability. His contributions have been applied to both ground vehicles and space systems, reflecting a broad expertise in dynamic systems and intelligent control.

• Artificial Intelligence
• Reinforcement Learning
• Machine Learning
• +3 more

Stuart Russell is a Professor at the University of California, Berkeley , affiliated with the Department of Electrical Engineering and Computer Sciences in the College of Engineering. His research spans Artificial Intelligence , Reinforcement Learning , and AI Ethics , focusing on safety, alignment, and theoretical foundations. Research Interests : Provably beneficial AI systems Human-compatible AI Reinforcement learning theory Language model interpretability AI safety and control mechanisms Recent Work Trends : 2025-2024: Safety frameworks (off-switch games, reversal curse analysis) 2024: Reward learning with partial observability, program synthesis via diffusion 2023: Societal risk taxonomy, human feedback coordination Collaborations include leading researchers like Anca D. Dragan (UC Berkeley), Yoshua Bengio (Mila), and Michael I. Jordan (UC Berkeley), with publications in venues such as NeurIPS , ICLR , and ICML .

• Marine Geology
• Coral Reef Ecology
• Submarine Geomorphology
• +3 more

Robin Jordan Beaman is a researcher at James Cook University (JCU) specializing in marine geology, coral reef systems, and submarine geomorphology. His work focuses on understanding coastal and marine processes, including sediment dynamics, sea-level changes, and the interaction between human activity and natural environments. He has contributed extensively to studies of the Great Barrier Reef's submerged geomorphic features, submarine landslides, and coral reef ecology. Research interests include carbonate platform evolution, deep-sea biodiversity, and the application of geospatial technologies for marine environmental monitoring. Collaborations span archaeology, ecology, and geophysics, reflecting interdisciplinary approaches to coastal and marine sciences. His fieldwork often integrates advanced mapping techniques such as LiDAR and underwater robotic surveys. Key contributions include: Mapping submerged reefs and shelf-edge geomorphic features in the Great Barrier Reef Investigating postglacial sedimentation and sea-level impacts Characterizing Halimeda bioherms and their role in carbonate budgets Studying submarine landslide hazards and their implications for coastal communities Recent projects involve interdisciplinary work on early human migration routes and coastal paleolandscapes, linking geological data with archaeological findings.

Thomas StastnyView profile

Researcher

• Unmanned Aerial Vehicles (UAVs)
• Autonomous Systems
• Control Theory
• +3 more

Dr. Thomas Stastny is affiliated with ETH Zürich's Autonomous Systems Department as a Researcher. His work focuses on advancing unmanned aerial vehicle (UAV) technologies, particularly in control systems, environmental monitoring, and autonomous navigation. Key research areas include fixed-wing UAV dynamics, solar-powered UAVs, wind-aware path optimization, and multi-agent robotic systems. His contributions span theoretical frameworks and experimental validations, with field applications in glacier monitoring and long-endurance aerial sensing. Research Highlights: Developed real-time wind prediction systems for UAVs (WindSeer project) Pioneered hybrid UAV designs like Soliro and Dipper for multimodal mobility Advanced control methodologies for high-angle-of-attack flight and VTOL transitions Explored solar-powered UAVs achieving multi-day endurance records Technical Expertise: Nonlinear model predictive control (MPC) Sensor fusion (radar/vision integration) Aerodynamic modeling and system identification Autonomous navigation algorithms His research integrates robotics, aerospace engineering, and environmental science to create robust airborne systems for challenging operational environments.

• Autonomous Systems
• Robotics
• Aerial Robotics
• +3 more

Dr. Michael Pantic is a Researcher in the Professorship for Autonomous Systems at ETH Zürich , affiliated with the Department of Mechanical and Process Engineering. His work focuses on advancing autonomous systems , particularly in aerial robotics , control systems , and sensor fusion . He specializes in developing innovative solutions for obstacle avoidance, navigation algorithms, and robotic manipulation in complex environments. His research emphasizes omnidirectional micro aerial vehicles (OMAVs) , reactive planning, and real-time obstacle avoidance techniques. Recent projects include corrosion inspection of infrastructure using autonomous robots and integrating radar with vision for robust depth prediction. Dr. Pantic's contributions bridge theoretical advancements with practical applications in industrial robotics and structural monitoring. Publications highlight trends in reactive navigation strategies , multi-resolution mapping , and physical interaction control . His work addresses challenges like local minima escape in path planning and minimizing actuator complexity in aerial manipulators. No scientific awards or student advisees are listed in the provided materials. Collaborative efforts include contributions to the MBZ International Robotics Challenge and the CleanSpace One Mission .

Robert LoftinView profile

Lecturer

• Ad Hoc Human-AI Cooperation
• Human-AI Alignment
• Human-in-the-loop Machine Learning
• +6 more

Dr. Robert Loftin is a Lecturer in Machine Learning at the University of Sheffield’s School of Computer Science. His research focuses on Ad Hoc Human-AI Cooperation, Human-AI Alignment, and Human-in-the-loop Machine Learning, with expertise in Deep Reinforcement Learning and Multi-Agent Systems. He holds a PhD from North Carolina State University (2019) and a Bachelor’s from Georgia Tech (2011). Postdoctoral work includes roles at Microsoft Research Cambridge and TU Delft, exploring AI applications in gaming and multi-agent cooperation. His research interests span AI ethics, human-robot interaction, and games, with a strong emphasis on practical applications of interactive learning. Recent work includes advancements in entropy-based coordination for multi-agent systems (2023–2025) and theoretical studies on cooperation in socially rational agent populations. He contributes to the Machine Learning research group and has published extensively in top venues like NeurIPS, AAMAS, and AAAI. Publications highlight innovations in curriculum design, exploration strategies, and adaptive feedback mechanisms. His work bridges theoretical foundations and real-world applications, particularly in cooperative and competitive multi-agent environments. Current projects explore safe team coordination and scalable strategies for high-dimensional state spaces.

Aaron WalsmanView profile

Research Fellow

• Artificial Intelligence
• Robotics
• Embodied AI
• +3 more

Aaron Walsman is a Research Fellow at the University of Washington working in Dieter Fox's Robotics and State Estimation lab and Ali Farhadi's RAIVN lab, focusing on how agents gather and utilize information in complex interactive environments where sensory input is limited. His academic background includes: PhD in Artificial Intelligence and Robotics from the University of Washington Master of Science in Robotics from Carnegie Mellon University's Robotics Institute (advised by Sidd Srinivasa) Prior industry experience as character technical director at Blue Sky Studios and Omation Studios on films including 'Horton Hears a Who', 'Ice Age III', and 'Rio' Walsman's research develops frameworks for AI systems to reason about information gaps in partially observable settings, strategically explore environments to acquire critical data, and retain only essential historical context for long-horizon planning. This work bridges embodied cognition with practical robotics applications requiring persistent environmental interaction. His ECCV 2022 publication demonstrates these principles through LEGO-based structural manipulation tasks, showing how agents learn to understand and modify 3D structures through trial-and-error interaction. This research direction emphasizes real-world applicability of memory-efficient exploration strategies in resource-constrained scenarios. No scientific awards are documented in available sources. Regarding mentorship and funding, no advised students or grant information appears in current records. Walsman actively supports his research through open-source tools including the ltron environment for structural reasoning and multiple GitHub repositories implementing reinforcement learning frameworks for interactive environments.

Guannan QuView profile

Assistant Professor

• Control Theory
• Optimization
• Machine Learning
• +7 more

Guannan Qu is an Assistant Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), affiliated with the College of Engineering. He holds a B.S. from Tsinghua University (2014) and a Ph.D. in Applied Mathematics from Harvard University (2019). Before joining CMU, he was a CMI and Resnick Postdoctoral Scholar at Caltech (2019–2021). His research focuses on control theory, optimization, and reinforcement learning (RL), with applications to power systems, multi-agent systems, IoT, and cyber-physical systems. Key areas include scalable RL for networked systems, stability-aware learning, and model-based RL for nonlinear control. Education: Ph.D., Applied Mathematics, Harvard University, 2019 B.S., Electrical Engineering, Tsinghua University, 2014 Research Interests: Machine learning and reinforcement learning for large-scale systems Control and optimization of networked systems (e.g., power grids, robotics) Model-based and model-free control synthesis Scalable distributed algorithms for decentralized decision-making Applications in smart grids, IoT, and transportation systems Awards: NSF CAREER Award (2023) Caltech Simoudis Discovery Award Amazon AI4Science Fellowship IEEE SmartGridComm Best Student Paper Award AAAIP 2025 Workshop Best Paper Award Advising & Grants: Advises PhD students in RL and control (e.g., Alex Deweese, Ziyi Zhang) Recipient of NSF EPCN, C3 AI Institute, and CMU CyLab grants Developed scalable RL frameworks for voltage control and inverter coordination Labs & Teams: Active in CMU’s robotics and power systems research groups, collaborating with industry partners on real-world applications of ML and control theory.