Find Academic Supervisors

• Surgical Robotics
• Minimally Invasive Surgery
• Virtual Reality in Medical Training
• +3 more

Caroline Giai Ly Cao serves as Professor in Industrial and Enterprise Systems Engineering, Bioengineering, and Biomedical and Translational Sciences at the University of Illinois Urbana-Champaign's Grainger College of Engineering. She directs both Engineering Innovation and Medical Simulation and Applied Health Technology Initiatives, driving interdisciplinary medical technology development. Her research focuses on surgical robotics and medical simulation, specializing in laparoscopic training systems with haptic feedback integration. Key interests include virtual reality applications for clinical practice, operator fatigue modeling in robot-assisted surgery, and stress response analysis in virtual environments. The fingerprint analysis confirms dominant expertise in minimally invasive surgery (76% weight) and virtual reality applications (25% weight). Recent publications reveal strong trends in mixed-reality medical imaging integration and neural network applications for surgical instrumentation. Her team develops decision support systems for robotic procedures while advancing human factors engineering in healthcare settings through fatigue modeling and stress induction studies. Scientific recognition includes: IEA Fellow (2024) As director of two major initiatives, Dr. Cao leads teams developing medical simulation tools that bridge engineering innovation with clinical practice. Her Applied Health Technology Initiatives program specifically creates translational solutions for surgical training and patient care enhancement through advanced simulation technologies.

Ann SychterzView profile

Assistant Professor

• Structural Engineering
• Sustainable and Resilient Infrastructure Systems
• Adaptive and Deployable Structures
• +5 more

Ann Sychterz is an Assistant Professor in the Department of Civil and Environmental Engineering and a Faculty Affiliate in Mechanical Science and Engineering at the University of Illinois Urbana-Champaign (UIUC). She holds multiple affiliations, including Faculty Fellow at the National Center for Supercomputing Applications and the Beckman Institute for Advanced Science and Technology. Her research focuses on adaptive, deployable structures and resilient infrastructure systems, leveraging geometrically nonlinear systems like tensegrity and origami. She leads the SMARTI lab, which develops innovative solutions for civil infrastructure challenges. Education: Ph.D. (2018) from Swiss Federal Institute of Technology Lausanne (EPFL), M.A.Sc. (2014) and B.A.Sc. (2012) from the University of Waterloo. Postdoctoral research at the University of Michigan. Research interests include optimized sensor placement, structural dynamics, machine learning in civil engineering, damage mitigation, and adaptive structures. Her work emphasizes sustainability and resilience against climate change impacts. Awards include the 2024 SEAOI Outstanding Young Engineer Award, ASCE SEI Future Leaders Award, and the 2023 ASCE SEI Futures Fund Young Professionals Award. She is actively involved in editorial roles and professional committees, including ASCE Structural Control and Sensing Technical Committee. Her lab's projects include deployable anchors for coastal erosion prevention and VR-based engineering education tools. She collaborates internationally, including a 2024 visiting professorship at the University of Stuttgart.

Sasan GooranView profile

Academic

• Digital Halftoning
• Image Reproduction
• Color Reproduction
• +3 more

Sasan Gooran is a Senior Associate Professor at Linköping University's Department of Science and Technology (ITN), specializing in Media and Information Technology (MIT). He holds a PhD in Media Technology from Linköping University (2001), following M.Sc. (1994) and Licentiate (1998) degrees in related fields. His research focuses on digital halftoning, image reproduction, and 3D printing technologies. He has supervised seven PhD students and over 50 M.Sc. theses, contributing significantly to graphic technology and appearance modeling. Teaching includes courses in Graphic Arts, Computer Graphics, Image Processing, and Python programming. His work integrates theory and application in visual information technology, with collaborations in interdisciplinary projects like material appearance digitization and BRDF modeling. He actively participates in research groups exploring 3D printing materials and visualization technologies. Recent research highlights include 3D printing material analysis via spectrophotometry, empirical BRDF models for reflective inks, and adaptive halftoning algorithms. His contributions span over 20 years, emphasizing quality enhancement in printing and digital imaging.

Krisjanis SteinsView profile

Lecturer

• Healthcare Logistics
• Emergency Response Systems
• Transportation Systems
• +3 more

Krisjanis Steins is a Lecturer at Linköping University's Department of Science and Technology (ITN), affiliated with the Communications and Transport Systems (KTS) division. His research focuses on healthcare logistics, emergency response systems, and quantitative modeling of transportation and healthcare systems. He specializes in applying discrete-event simulation to optimize emergency department accessibility, disaster response logistics, and healthcare resource planning. His work addresses challenges such as bleeding control kit placement, ICU resource allocation, and hospital operational efficiency. Key research affiliations include the Center for Advanced Research in Emergency Response (CARER). His publications span topics like resilient transport systems, crisis management, and sensor technology integration in emergency logistics. He actively collaborates with institutions on projects involving simulation-based solutions for healthcare and transport infrastructure.

• Aerospace Engineering
• Structural Dynamics
• Finite Element Analysis
• +3 more

Dr. Maria Ribeira Vicent is a Research Fellow at the University of Surrey, focusing on spacecraft finite element modeling and structural dynamics. Her work addresses the correlation between computational finite element models (FEMs) and physical spacecraft structures, ensuring accuracy in predicting launch and flight loads. She investigates modal parameter estimation techniques, sensor placement strategies, and FEM reduction methods to enhance efficiency in model validation. Her research employs two large scientific spacecraft as case studies, analyzing vibration test data from base-shake sine-sweep campaigns. Key contributions include identifying optimal pre-test sensor configurations, addressing inaccuracies in FEM reduction, and improving target mode selection criteria aligned with mission-specific loading scenarios. These findings aim to streamline correlation processes and reduce time-to-accuracy in spacecraft structural analysis.

Kailai LiView profile

Assistant Professor

• Robotic Perception
• Sensor Fusion
• State Estimation
• +2 more

Kailai Li is a tenure-track Assistant Professor at the University of Groningen's Bernoulli Institute, where he leads the Agile Sensing and Intelligence Group (ASIG). His research develops novel methods for robotic perception, including continuous-time state estimation, sensor fusion, and visual navigation. Recent publications focus on Gaussian process representations for motion estimation and multi-robot collaboration using vision-language models. Dr. Li's lab maintains open-source projects like LiLi-OM (LiDAR-inertial odometry) and SFUISE (UWB-inertial fusion). Collaborations include Linköping University and industry partners. Current projects investigate trustworthy perception for autonomous systems under uncertainty and efficient representations for high-dimensional state estimation.

Gijs L. DerksView profile

Researcher

• Fusion Energy
• Plasma Physics
• Control Systems
• +2 more

Gijs L. Derks is a doctoral researcher in the Mechanical Engineering school at Eindhoven University of Technology (TU/e) , affiliated with the Dutch Institute for Fundamental Energy Research (DIFFER) . His work focuses on Fusion Energy and Plasma Physics , particularly Tokamak Device optimization and Control Systems . Key Research Areas : Tokamak power exhaust, scrape-off layer dynamics, real-time plasma control, and sensor placement in fusion reactors. Collaborations : Eurofusion Tokamak Exploitation Team, MAST Upgrade team, TCV team. Notable Contributions : Development of physics-based models for divertor plasma detachment and feedback control systems for fusion reactor stability. His recent publications highlight innovations in neutral baffling and density feedback mechanisms in tokamaks.

Mircea LazarView profile

Associate Professor

• Constrained Control
• Model Predictive Control
• Hybrid Systems
• +4 more

Mircea Lazar is an Associate Professor in the Control Systems group at Eindhoven University of Technology. His research spans constrained control, model predictive control (MPC), and stability analysis of hybrid systems, with applications in power systems, smart grids, and precision mechatronics. Research highlights include: Development of data-driven predictive control methods Stability guarantees for nonlinear and hybrid systems Applications in water networks, power converters, and mechatronics He has received the EECI PhD Award and NWO VENI grant. Recent publications focus on real-time MPC implementations, physics-guided neural networks, and optimization for large-scale systems. Collaborations include ASML, DAF, Philips, and Ford. He chairs the IEEE CSS Technical Committee on Hybrid Systems and has supervised 9 PhD students.

Anna LeeView profile

Lecturer

• Environmental Psychology
• Environmental Education
• Human-Nature Relationships
• +1 more

Anna Lee is a Lecturer at Stanford University, where she researches how people form relationships with nature and the environment through the lens of environmental education and social psychology. Her work examines mental models of environmental systems and pro-environmental behaviors. Education: BS and MS in Earth Systems, Stanford University BS in Anthropological Sciences, Stanford University Certificate in Ecological Horticulture, UC Santa Cruz MS in Agroecology, University of Wisconsin-Madison Her research integrates environmental education with social psychology to understand human-nature connections and behavioral change. Current interests include environmental meaning-making, educational approaches to sustainability, and psychological barriers to eco-friendly behaviors. Her publications focus on medical diagnostics using novel technologies, particularly electrical impedance tomography applications in stroke detection and skin cancer diagnosis through wearable sensors. Research demonstrates a consistent focus on biomedical innovation and computational modeling. No scientific awards or student advising relationships are documented in available materials.

Nora LüthenView profile

Lecturer

• Uncertainty Quantification
• Computational Science and Engineering
• Stochastic Simulators
• +3 more

Dr. Nora Lüthen is a Lecturer at ETH Zürich's Department of Civil, Environmental and Geomatic Engineering. She holds a post-doctoral position at the Chair of Risk, Safety and Uncertainty Quantification. Her current responsibilities include co-developing and teaching the first-semester Bachelor course Programming for Engineers and the Master-level interdisciplinary course Uncertainty Quantification in Engineering . Education: Studied Mathematics with emphasis on Numerical Mathematics at the University of Bonn (Germany). Master's degree in Mathematics (2016). Research Interests: Nora focuses on uncertainty quantification, stochastic simulators, surrogate modeling, polynomial chaos expansions, and optimal sensor placement. Her work integrates analytical and numerical methodologies, particularly in engineering contexts. She has contributed to projects like the SNF-funded SAMOS initiative, exploring efficient computational techniques for stochastic systems. Courses Taught: Programming for Engineers (Autumn Semester 2025). Uncertainty Quantification in Engineering (Spring 2023). Professional History: Prior to her post-doc role, Nora was a PhD student (2018-2022) at the same Chair, where she developed novel surrogate models for stochastic systems. Earlier, she worked at the Computational Science and Engineering Lab on optimal sensor placement for artificial swimmers. She has collaborated extensively with researchers like Prof. Bruno Sudret and Xujia Zhu. Labs & Teams: Affiliated with the Chair of Risk, Safety and Uncertainty Quantification and previously contributed to the Computational Science and Engineering Lab. Her research group emphasizes bridging advanced mathematical theory with practical engineering applications.

Christian Cabrera JojoaView profile

Lecturer

• Artificial Intelligence
• Data-Oriented Architectures
• Service-Oriented Computing
• +3 more

Christian Cabrera Jojoa is a Senior Research Associate and Affiliated Lecturer at the University of Cambridge's Department of Computer Science and Technology, and an Academic Associate at Pembroke College. His research focuses on deploying AI systems in real-world scenarios, emphasizing self-sustaining architectures, interpretability, and human control. He holds a PhD in Computer Science from Trinity College Dublin (2020) and a Master's from Universidad de los Andes (2014). Education: PhD: Trinity College Dublin, 2020 MSc: Universidad de los Andes, 2014 Research Interests: Dr. Cabrera Jojoa explores challenges in AI system deployment, including: Self-adaptive systems for dynamic environments Data-oriented architectures for machine learning Service-oriented computing in IoT and smart cities Key Contributions: Recent work includes: Developing MAACO for smart city service placement Empirical studies on flow-based programming for ML systems Survey on real-world ML systems from a data-centric perspective Labs & Collaborations: Collaborates with the ml@cl research group at Cambridge and actively contributes to open-source projects like Cities-Board and Auto-ai-doa.

• Smart Cities
• Data Analytics
• Artificial Intelligence
• +6 more

Dr. Anish Jindal is an Associate Professor at Durham University's Department of Computer Science, with affiliations to the Durham Energy Institute and visiting fellowships at Princeton University. His research focuses on smart cities, energy optimization, AI, and cyber-physical systems. He holds a Ph.D. from India (2018) and has authored/co-authored over 100 publications in top-tier journals/conferences like IEEE Transactions and ACM MobiHoc. Notable awards include IEEE TCSC's Outstanding Ph.D. Dissertation Award (2019) and the IEEE Communication Society's Outstanding Young Researcher Award (2019). Research interests include resource-aware computing, programmable networking, wireless security, and energy-efficient AI. He leads major grants such as the £3M EPSRC CHEDDAR hub (EP/X040518/1) and the £10M National Edge AI Hub (EP/Y028813/1). His work spans 6G networks, edge computing, and IoT applications in smart grids and healthcare. Recent articles emphasize digital twins for IoT security, energy-efficient AI frameworks, and UAV-assisted vehicular edge computing. He actively organizes workshops like IEEE CSR's Data Science for Cyber Security and serves on editorial boards of journals like IET Smart Cities and Software: Practice and Experience.

Haruko Murakami WainwrightView profile

Assistant Professor

• Environmental Informatics
• Nuclear Waste Management
• Radiation Monitoring
• +5 more

Haruko Murakami Wainwright is an Assistant Professor at the Massachusetts Institute of Technology (MIT), affiliated with the Department of Nuclear Science and Engineering. Her research focuses on environmental informatics, integrating mechanistic modeling and machine learning to address challenges in nuclear waste management, radiation monitoring, and environmental resilience. She leads interdisciplinary projects such as the DOE’s Advanced Long-term Environmental Monitoring Systems (ALTEMIS) and the Artificial Intelligence for Earth System Predictability (AI4ESP) initiative. Education: BEng in Engineering Physics from Kyoto University (2003), MS and PhD in Nuclear Engineering and Statistics from UC Berkeley (2006–2010). Research emphasizes Bayesian geostatistical methods, real-time environmental monitoring systems, and applications in watershed science. Notable contributions include radiation dose rate mapping post-Fukushima, groundwater contamination modeling, and sustainable remediation strategies. Her work bridges nuclear engineering, environmental science, and data science, with a focus on resilience to environmental disasters and sustainable energy waste management.

• Sustainable and Resilient Environments
• Workplace Safety and Health Risk Monitoring
• Digital Transformation in Project Management
• +6 more

Dr. Hoonyong Lee is a Lecturer at the School of Project Management, Faculty of Engineering, University of Sydney. His research focuses on building sustainable and resilient environments through advanced safety and health risk management frameworks. PhD in Construction Science, Texas A&M University Postdoctoral Fellow, University of Michigan Member, Net Zero Institute and Brain and Mind Centre Research spans human sensing technologies , data analytics , and behavioral intervention design , with applications in: Construction Safety Management Smart Home Healthcare Fall Risk Assessment Household Energy Conservation His work combines wearable biosensors , Wi-Fi CSI , and machine learning for proactive risk identification. Recent projects focus on team cohesion in project management using physiological data analytics. 2024 Best Paper Award, Construction Research Congress 2024 Best Data Award Honorary Mention, ASCE DSA Committee Multiple award-winning publications (2012–2024) Teaching includes Project Acceptance and Project Planning courses. Leads Team L in developing adaptive intervention systems.

• Theoretical Computer Science
• Combinatorial Optimization
• Algorithms
• +4 more

Dr. Julian Mestre is an Associate Professor in the School of Computer Science at the University of Sydney. He holds a BE from the Universidad Católica de Argentina (UCA), and MSc and PhD degrees in Computer Science from the University of Maryland (UMD, USA). His research focuses on theoretical computer science, particularly the design and analysis of efficient algorithms for combinatorial optimization problems such as scheduling, routing, and matching. He previously served as a postdoctoral fellow at the Max Planck Institute for Informatics in Germany. **Education**: PhD in Computer Science, University of Maryland (2000s) MSc in Computer Science, University of Maryland Bachelor of Engineering (BE), Universidad Católica de Argentina **Research Interests**: Julian specializes in algorithms for combinatorial optimization, including approximation algorithms, scheduling, graph theory, and discrete mathematics. His work often bridges theoretical foundations with practical applications in areas like mobile app optimization, sensor networks, and distributed systems. **Grants**: 2015: Local Reoptimization for Turbocharging Heuristics (ARC Discovery Project) 2013: Universal Solutions for Scheduling Problems (ARC DECRA) 2012: Algorithms for Combinatorial Optimization on Uncertain Inputs (Group of Eight/Germany Grant)