Find Academic Supervisors

John O. DabiriView profile

Professor

• Fluid Mechanics
• Biological Fluid Dynamics
• Renewable Energy
• +4 more

John O. Dabiri is the Centennial Professor of Aeronautics and Mechanical Engineering at the California Institute of Technology (Caltech). He holds dual appointments in the Division of Engineering and Applied Science. His academic journey includes a B.S. from Princeton University (2001), and M.S. and Ph.D. from Caltech (2003, 2005). He has served as a faculty member at Caltech since 2005, advancing through ranks from Assistant to Centennial Professor. He also served as Dean of Undergraduate Students at Caltech (2014–2016) and held a professorship at Stanford University (2015–2019). His research focuses on fluid mechanics, bio-inspired engineering, and renewable energy. Key areas include biological fluid dynamics in oceans, next-generation wind energy systems, and experimental methods. Notable contributions include developing biohybrid robotic jellyfish for ocean exploration and improving wind farm efficiency through unsteady flow dynamics. Dr. Dabiri has received prestigious awards such as the National Medal of Science (2025), Alan T. Waterman Award (2020), and MacArthur Fellowship (2010). He leads major grants, including projects on biohybrid robotics and wind energy optimization. His work spans interdisciplinary collaborations, bridging engineering, biology, and environmental science. Advising over 30 students and postdocs, Dabiri’s lab has produced leaders in academia and industry. Ongoing projects include visual anemometry, vortex ring propulsion, and ethical biohybrid systems. He actively contributes to national policy through roles on the President’s Council of Advisors on Science and Technology and the Secretary of Energy Advisory Board.

• Robotics
• Environmental Monitoring
• Drone Technology
• +3 more

Kazi Sanim is a Researcher at the Department of Computer Science and Technology, University of Cambridge. Their work focuses on developing autonomous systems, particularly drones and sensor technologies for environmental monitoring, water sampling, and assistive technologies. Key research interests include robotics, sensor integration, and low-cost solutions for resource-constrained environments. Recent projects involve creating drone-based systems for water quality analysis and tactile displays for visually impaired learners. Research contributions span environmental engineering (e.g., fluorometer calibration for water sampling) and humanitarian applications (e.g., low-cost search-and-rescue robots). Their interdisciplinary approach combines computer science, mechanical engineering, and environmental science to address practical challenges in autonomous systems and accessibility. No scientific awards or grants are explicitly mentioned in the provided texts. While no formal advisees are listed, their publications suggest active collaboration with teams in robotics and environmental technology. No specific labs or teams are named, though their work aligns with the University's focus on applied computer science and engineering.

Ajay ShankarView profile

Research Fellow

• Robotics
• Multi-Robot Systems
• Autonomous Control
• +3 more

Dr. Ajay Shankar is a Post-Doc Research Fellow in the Department of Computer Science and Technology at the University of Cambridge. His primary research focuses on control, planning, and automation for robotic systems and teams, with a strong emphasis on multi-robot systems, autonomous control, and machine learning applications in robotics. He is affiliated with the Mobile Systems, Robotics and Automation research theme within the department. His work integrates robotics, machine learning, and systems engineering to address challenges in multi-agent coordination, trajectory optimization, and real-time control. Key projects include the development of the Cambridge RoboMaster platform and studies on dynamics-aware trajectory planning using diffusion models. He also explores downwash modeling for multirotor flight in dense environments and heterogeneous multi-robot reinforcement learning frameworks. Dr. Shankar's contributions span academic conferences and journals, with recent publications focusing on aerial robotics, autonomous systems, and multi-agent learning. His research has practical applications in environmental monitoring (e.g., UAS profiling during LAPSE-RATE campaigns) and agile robotics systems design. Department: Computer Science and Technology University: University of Cambridge Affiliations: Cambridge Ring Initiative, Accelerate Programme for Scientific Discovery

• Translanguaging
• Multilingual Repertoires
• Multilingual Identities
• +6 more

Nuria Polo Perez is a Lecturer in Spanish at Durham University’s School of Modern Languages and Cultures, based in the Centre for Foreign Language Study (CFLS). She holds a PhD from Durham University and has taught Spanish since 2010 across UK institutions, including the University of Leeds and the Instituto Cervantes in Leeds. Her research focuses on multilingual identities, translanguaging, and intercultural communication, particularly through the lens of language cafés as informal learning spaces. Education: PhD in Multilingual Identities and Interculturality from Durham University MA in Teaching Spanish as a Foreign Language (Universidad Internacional Menéndez Pelayo) Bachelor’s in Translation and Interpreting Studies (Autonomous University of Madrid) Her work explores the 'multilingual social self'—a concept emphasizing how identities are co-constructed through multilingual social interaction. Research methods include ecological approaches and ethnographic data collection, highlighting how languages are 'lived' intersubjectively beyond traditional skill-based frameworks. Key research outputs analyze language cafés as sites for emotion work, identity negotiation, and intercultural exchange. She advocates for translanguaging methodologies to study multilingual data authentically. No awards are explicitly mentioned, but her contributions to applied linguistics are notable through peer-reviewed publications. Advising and grants: While no advisees are listed, her teaching roles include teacher training courses. She actively engages in pedagogical translation and reflexivity in multilingual research. Labs/Teams: Affiliated with the CFLS and contributes to interdisciplinary research on multilingualism within the School of Modern Languages and Cultures.

Ian M. MitchellView profile

Professor

• Hybrid Systems
• Robotics
• Optimal Control
• +3 more

Ian M. Mitchell is a Professor in the Computer Science Department at the University of British Columbia. His research focuses on hybrid and embedded systems, level set methods, Hamilton-Jacobi PDEs, and applications in robotics and autonomous systems. He has contributed to path planning, safety-critical control systems, and assistive technologies such as wheelchair navigation systems. Education includes a PhD in Computer Science from Stanford University under advisors Claire Tomlin and Ronald Fedkiw, and postdoctoral work at UC Berkeley and Stanford. He has taught courses like Computational Robotics (CPSC 515), Parallel Computation (CPSC 418), and Computing in the Life Sciences (CPSC 301). Key research interests span optimal control, verification of hybrid systems, and reproducible research practices. His work bridges theory and application, with projects on safety systems for anesthesia delivery and telehealth interventions for mobility-impaired populations. Collaborations include CanWheel Research Team and interdisciplinary efforts in robotics, healthcare, and computational mathematics. His open-source Toolbox of Level Set Methods supports numerical solutions for reachability and control problems.

Paolo MengoniView profile

Lecturer

• Artificial Intelligence
• Complex Network Analysis
• Natural Language Processing
• +3 more

Dr. Paolo Mengoni is a Lecturer I at Hong Kong Baptist University (HKBU), specializing in Artificial Intelligence and Complex Network Analysis. Originally from Italy, he brings over 20 years of experience as an IT consultant and researcher. His work focuses on AI applications in education, natural language processing, emotion recognition, and autonomous agents. He holds a Ph.D. in Computer Science from the University of Florence and MSc/BSc degrees from the University of Perugia (Italy). Teaching responsibilities include courses like AI and Digital Communication , Basic Programming for Data Science , and Recommender Systems for Digital Media . His research explores topics such as learning analytics, sentiment analysis in social networks, and community detection in collaborative environments. He actively contributes to academic activities, including organizing international workshops like the 2020 Global Virtual Hack and Design Challenge and the HKBU-University of Perugia exchange program. His publications span journals and conferences including IEEE/WIC/ACM Web Intelligence, Future Generation Computer Systems, and IEEE International Symposia. He serves as a reviewer for venues such as IEEE Congress on Evolutionary Computation and the International Conference on Computational Science and Its Applications.

• Computer Networks
• Network Security
• Multimedia Communication
• +4 more

Christos Papadopoulos is a Professor and Sparks Family Chair of Excellence in Global Research Leadership in the Department of Computer Science at the University of Memphis. He joined the university in Fall 2020, coming from Colorado State University where he held a professorial position. His expertise spans computer networks, network security, multimedia communication, and distributed systems. He holds a DSc in Computer Science from Washington University in St. Louis (1999). Dr. Papadopoulos' research focuses on advancing secure and efficient network architectures, particularly in vehicular networks and Named Data Networking (NDN). He has led collaborative projects to create open platforms for sharing vehicle telematics data and improving cybersecurity in automotive systems. His work often bridges theoretical contributions with practical implementations, addressing challenges in data privacy, network scalability, and real-time communication. His recent publications reflect a strong emphasis on autonomous systems, cybersecurity datasets, and innovative applications of NDN in scientific data management. He has contributed to foundational work in internet measurement, traffic analysis, and privacy-preserving techniques for wide-area networks. Notable grants include collaborative NSF-funded initiatives on privacy in internet measurements, open telematics data platforms, and NDN-based solutions for big science projects. His research has implications for transportation safety, environmental monitoring, and secure communication protocols. Dr. Papadopoulos is actively involved in academic leadership, including editorial roles and conference organization. His interdisciplinary approach integrates computer science with environmental and automotive engineering, fostering cross-sector innovation.

Young ChangView profile

Assistant Professor

• Precision agriculture automation
• Cost-effective camera/sensor systems
• Biosystems robotics
• +4 more

Young Chang is an Assistant Professor in the Department of Agricultural and Biosystems Engineering at South Dakota State University. He holds a Ph.D. in Agricultural Biotechnology from Seoul National University. His academic journey includes postdoctoral research at UC Davis, North Dakota State University, and Nova Scotia Agricultural College, alongside roles at Samsung Electronics' Living System Laboratory. He founded the Bio-systems Automation and Robotics Lab at Dalhousie University, Canada. His research focuses on precision agriculture automation, cost-effective sensor systems, and agricultural robotics. He actively collaborates on projects like cybersecurity in smart agriculture (Cyber-Ag-Law, $249k) and edge computing for agroecosystems (SDAES, $125k). Education: Ph.D./M.S./B.S. in Food Engineering (Seoul National University) Key Labs: Bio-systems Automation and Robotics Lab (Dalhousie), Raven Precision Ag Center (SDSU) Grants: Over $1M in funded projects including USDA grants and industry partnerships Research interests span precision agriculture automation, drone/UAV systems, and IoT-driven livestock management. His work integrates machine learning (e.g., YOLOv4 for strawberry counting) and FPGA-based real-time image processing. Recent articles emphasize cybersecurity for agricultural data and phenotypic trait analysis in soybeans. Awards include NSERC Discovery Grants and Mitacs Accelerate funding. Patents: Variable rate sprayer systems and kimchi ripening control Teaching: Courses on precision agriculture tech (AST-426) and farm machinery diagnostics (PRAG-304)

Tim KraskaView profile

Associate Professor

• Machine Learning
• Data Systems
• Database Systems
• +3 more

Tim Kraska is an Associate Professor of Electrical Engineering and Computer Science at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). He co-leads the Data Systems Group and is the founding co-director of the Data System and AI Lab (DSAIL). He is also a co-founder of Einblick Analytics. His research focuses on integrating machine learning into data systems (Systems for ML) and enhancing systems using machine learning (ML for Systems). Notable projects include SageDB, which explores ML-enhanced database systems, and Northstar, aimed at democratizing data science through interactive tools. His work spans learned indexes, video processing, and instance-optimized systems. Kraska has received research funding from NSF, DARPA, the Air Force, and industry partners like Google and Microsoft. He advises graduate and undergraduate students, with Erfan Zamanian being a notable advisee who completed his PhD in 2020. Key contributions include pioneering 'learned systems' concepts, such as adaptive indexes and query optimizers. His labs and teams focus on rack-scale computing, transaction processing, and AI-driven database systems. Kraska's research bridges the gap between theoretical advancements and practical industry applications, with his work being commercialized and influencing cloud products.

Kasra KhosoussiView profile

Senior Lecturer

• Robot Perception
• Robotic Autonomy
• Mathematical Foundations
• +3 more

Dr. Kasra Khosoussi is a Senior Lecturer (equivalent to US Associate Professor) at the University of Queensland's School of Electrical Engineering and Computer Science. He leads research on mathematical and algorithmic foundations of robot perception and autonomy, with prior roles including Robotic Mapping Team Leader at CSIRO and Research Scientist at MIT. His research focuses on: Robotic perception systems including SLAM and multi-sensor fusion Autonomous navigation in extreme environments Distributed optimization for multi-robot collaboration Probabilistic modeling for robotic decision-making Recent publications demonstrate strong emphasis on resilient SLAM systems, energy-aware robotics, multi-agent coordination, and real-time perception algorithms for challenging environments like subterranean spaces and marine contexts. Awards include: Hilti SLAM Challenge Winner (ICRA 2022) IEEE Transactions on Robotics Best Paper Honorable Mention (2021) ICRA Best Paper Finalist (2018) Professional activities include Associate Editorship for IEEE Robotics and Automation Letters and committee roles at leading robotics conferences including ICRA and RSS.

• Systems Engineering
• Web Performance Analysis
• Data Mining
• +5 more

Prof. Leszek Borzemski is a Professor at the Department of Computer Science and Systems Engineering, Wrocław University of Science and Technology. His research focuses on web performance analysis, distributed systems, data mining, and quality of service (QoS) management. He has organized international conferences such as the 28th International Conference on Systems Engineering (ICSEng 2021) and contributed to proceedings like Advances in Systems Engineering . His work encompasses spatio-temporal forecasting of web performance using methods like Turning Bands and Sequential Gaussian Simulation, as well as algorithm design for request distribution in cluster-based systems. He has also explored business-oriented admission control for e-commerce websites and fuzzy logic-based adaptive systems. Prof. Borzemski's publications span over two decades, with notable contributions in IEEE Transactions, Cybernetics and Systems, and conference proceedings. His research bridges theoretical data analysis with practical applications in networking and web infrastructure optimization.

Volker LüdemannView profile

Professor

• Business Law
• Competition Law
• Data Protection
• +2 more

Prof. Dr. Volker Lüdemann is a Professor of Business and Competition Law at Osnabrück University of Applied Sciences, leading the Chair of Business and Competition Law. He is also Director of the Niedersächsisches Datenschutzzentrum (Lower Saxony Data Protection Center) since 2015. His roles include board membership at Städtische Bühnen Osnabrück and chairmanship of the university's Ethics Commission. He holds a law degree from Heidelberg and Osnabrück Universities, with a doctorate focusing on Russian corporate law. His career spans legal roles at Volkswagen Group in Germany and Russia, including executive positions in financial services and syndication law. Research interests include data protection, automotive industry regulation, competition law, and technology governance. He frequently engages in media discussions about emerging legal challenges in autonomous vehicles, driver data privacy, and regulatory compliance for connected cars. Notable contributions include analyses of the EU Data Act, eCall systems, and ethical implications of automotive data harvesting. Media contributions highlight his expertise in automotive law, appearing in WDR, ARD, ZDF, and publications like Wirtschaftswoche. His work bridges legal frameworks with technological innovation, addressing corporate liability and public policy in rapidly evolving sectors.

Marc CompereView profile

Associate Professor

• Nonlinear Dynamic Systems
• Controls
• Hardware-in-the-Loop Control
• +8 more

Dr. Marc Compere is an Associate Professor of Mechanical Engineering at Embry-Riddle Aeronautical University’s College of Engineering in Daytona Beach, Florida. His research focuses on nonlinear dynamic systems and controls, hybrid-electric power systems, and solar-powered water purification. He also explores self-driving vehicles, Advanced Driver Assistance Systems (ADAS), and diesel emissions controls. Dr. Compere teaches courses such as Dynamics, Vehicle Dynamics, and Instrumentation and Data Acquisition. He co-founded a small business to transition laboratory technology to market and advocates for sustainable micro-business creation in developing countries, particularly through projects in Haiti’s Artibonite Valley. His research interests span energy systems, electro-mechanical systems, and acoustics, with a strong emphasis on applying technological solutions to real-world challenges. He has developed the Mobility Virtual Environment (MoVE), an open-source framework for coordinating multi-vehicle systems to collect and visualize atmospheric data. His work also includes environmental monitoring using low-cost sensors on unmanned aerial vehicles and hyper-local weather prediction tools. Dr. Compere’s contributions to education include pioneering hands-on learning modules, such as desktop Rankine cycle systems and bio-diesel plug-in hybrid electric vehicles. He has led projects like Project Haiti, integrating technical solutions with community development to address water scarcity and promote sustainability. His research and teaching reflect a commitment to bridging academic innovation with practical, socially impactful applications.

Jason ForsythView profile

Associate Professor

• Wearable Computing
• Ubiquitous/Pervasive Computing
• Engineering Education
• +3 more

Jason Forsyth is an Associate Professor of Engineering at James Madison University's College of Integrated Science & Engineering. He holds a Ph.D., M.S., and B.S. in Computer Engineering from Virginia Tech. His research focuses on wearable computing, ubiquitous/pervasive computing, and engineering education through project-based service learning. He teaches courses in embedded systems, engineering modeling, and circuits/instrumentation. Dr. Forsyth's scholarly work bridges technology and human interaction, with notable projects like GymSense (analyzing athletic form) and haptic feedback systems for braille learning. His studies often emphasize interdisciplinary approaches, such as arts-informed pedagogy and trust assessment in autonomous systems. He has pioneered community engagement initiatives, including a bike project that integrates engineering with social impact. His research trends highlight advancements in wearable technologies, sensor-driven activity analysis, and innovative educational strategies. While no specific awards are listed, his contributions to engineering education and applied technology are evident through his prolific publications and course development. He actively involves students in real-world projects, fostering entrepreneurship and problem-solving skills. Dr. Forsyth collaborates with interdisciplinary teams on projects such as drone-based environmental monitoring and smart sensor networks for agriculture. His work emphasizes both technical innovation and societal relevance, aligning with JMU's commitment to applied research and community outreach.

• Software Defined Networking
• Network Security
• Artificial Intelligence
• +6 more

Raja Majid Ali Ujjan is a Lecturer at the School of Computing, Engineering and Physical Sciences, Mehran University of Engineering and Technology. His research focuses on cybersecurity, artificial intelligence, and software-defined networking (SDN). He explores applications in e-government, smart logistics, drone technology, and healthcare digitalization. His work addresses challenges such as DDoS mitigation, intrusion detection, and privacy preservation in IoT and blockchain contexts. He has contributed to chapters on Industry 4.0 healthcare digitalization, AI-driven drone safety, and blockchain-enhanced e-government security. His recent publications (2024) highlight innovations in phishing detection, weapon identification systems, and cybersecurity for intelligent transportation systems. He actively supervises PhD students in areas like neural networks and big data analytics. His research integrates machine learning with edge computing for real-time threat detection and promotes secure IoT implementations in critical infrastructure. Collaborations span cybersecurity modeling in SDN, drone cyber-physical systems, and sustainable electric vehicle frameworks.