Find Academic Supervisors

• Computer Vision
• Robotics
• Computer Graphics
• +5 more

Ioannis Stamos is a Professor of Computer Science at Hunter College, City University of New York (CUNY), within the School of Arts and Sciences. His research focuses on Computer Vision, Robotics, Computer Graphics, and 3D Visualization, with emphasis on 3D modeling using range and image data. He earned his Ph.D. in Computer Science from Columbia University (2001), followed by an M.S. and M.Phil. from Columbia's Computer Science Department, and a Diploma of Engineering from the University of Patras, Greece. Dr. Stamos has received prestigious awards including the NSF CAREER Award (2003) and Google Research Awards (2014, 2017). His work integrates 2D images and 3D range data for urban scene modeling, sensor fusion, and real-time object detection. Notable contributions include advancements in 6DoF pose estimation, LiDAR-based curb detection, and Kronecker product models for repeated patterns in urban imagery. He leads the Computer Vision & Robotics Lab and teaches graduate courses in 3D Computer Vision and Photorealistic Modeling. His research is supported by NSF grants, including MRI awards for mobile robotics and large-scale 3D modeling. He serves as Area Editor for the Journal of Computer Vision and Image Understanding and has co-chaired conferences like 3DV 2013. His lab collaborates on projects involving procedural modeling of urban environments and online classification of 3D point clouds.

Jean PonceView profile

Professor

• Computer Vision
• Machine Learning
• Robotics
• +3 more

Jean Ponce is a Professor of Computer Science at Ecole Normale Superieure (ENS) in Paris and a Part-Time Global Distinguished Professor at New York University's Courant Institute of Mathematical Sciences and Center for Data Science (CDS). He previously served as Director of the ENS Computer Science Department (2011-2017) and held positions at Inria (2017-2022), University of Illinois at Urbana-Champaign (1998-2006), MIT, Stanford, and Inria (1982-1985). Academic Leadership: Scientific Director of PRAIRIE Interdisciplinary AI Research Institute in Paris Startup Involvement: Co-founder and CEO of Enhance Lab (2022) Editorial Roles: Senior Editor-in-Chief of International Journal of Computer Vision (2019-2022) Conference Leadership: Chair of IEEE CVPR (1997,2000), ECCV (2008), and upcoming ICCV (2023) Research Focus: Computer vision, machine learning, robotics, and AI with applications in exoplanet imaging, 3D reconstruction, and image quality assessment. His work bridges statistical learning and deep learning approaches. Awards: IEEE Fellow (2003) ELLIS Fellow (2019) ERC Advanced Grant (2011) IEEE CVPR Longuet-Higgins Prizes (2016,2020) ICML Test-of-Time Award (2019) Patents & Publications: Co-author of influential textbook Computer Vision: A Modern Approach (translated into Chinese, Japanese, Russian). Holds two US patents and one pending French patent. Google Scholar h-index of 78 with over 55,000 citations.

Wil van der AalstView profile

Professor

• Business Process Management
• Data Mining
• Simulation
• +6 more

Wil van der Aalst is a full professor at RWTH Aachen University since 2018, leading the Process and Data Science (PADS) group. He serves as Chief Scientist at Celonis and is part-time affiliated with Fraunhofer FIT . Additional roles include deputy CEO of the Internet of Production Cluster of Excellence , co-director of the RWTH Center for Artificial Intelligence , and speaker of the RWTH ICT Profile Area . Previously, he led the Architecture of Information Systems group at Eindhoven University of Technology (TU/e) until 2017 and was a member of Tilburg University's Board of Governors (2015–2023). Research interests focus on process mining , business process management , Petri nets , and model-based analysis . His work bridges formal methods with real-world applications, influencing software development, standardization committees, and commercial tools like Celonis, SAP, and YAWL. Developed foundational WorkFlow nets (WF-nets) and soundness criteria for workflow modeling Pioneered the Workflow Patterns initiative (with Arthur ter Hofstede and Nick Russell), impacting process modeling standards Founded the YAWL open-source workflow system and ProM process mining framework Chaired steering committees for major conferences (Business Process Management, IEEE Task Force on Process Mining) Scientific honors include IEEE, ACM, and IFIP fellowships, the Alexander von Humboldt Award (2018), and memberships in prestigious academies such as Academia Europaea and the German Academy of Science and Engineering. He has an H-index of 182 (Google Scholar) and over 155,000 citations. He has served on the editorial boards of journals including Business & Information Systems Engineering , IEEE Transactions on Services Computing , and Transactions on Petri Nets and Other Models of Concurrency . He also co-founded the BPM User Group Foundation and led the Data Science Center Eindhoven (DSC/e) until 2017.

Will FleesonView profile

Professor

• Personality Psychology
• Moral Behavior Dynamics
• Dynamic Personality Models
• +4 more

Will Fleeson is a Professor of Psychology at Wake Forest University, specializing in personality dynamics, moral behavior, and the integration of trait theories with dynamic systems. His research focuses on understanding how personality traits manifest in real-world behaviors, particularly in contexts involving morality, psychopathology, and virtue ethics. He leads the Fleeson Lab, exploring topics such as honesty, virtue profiles, and the interplay between personality and psychological well-being. Central to his work is the Whole Trait Theory, which emphasizes the dynamic nature of personality as both structural and process-oriented. Fleeson employs methodologies like experience sampling and multilevel modeling to examine intra-individual variability and situation-based contingencies. His studies often bridge philosophical and psychological perspectives, particularly in defining moral exceptionalism and intellectual virtues. Key research themes include the dynamics of borderline personality disorder symptoms, the measurement of honesty and virtue, and the motivational underpinnings of moral behavior. Fleeson’s contributions challenge traditional static trait models, advocating for frameworks that account for temporal fluctuations and situational influences. Despite the absence of listed awards or grants in the provided text, his extensive publication record underscores his influence in advancing dynamic personality theory and moral psychology. His lab’s website (linked) highlights ongoing projects and collaborations, though specific advisees or teams are not detailed here. Fleeson’s work consistently emphasizes the practical implications of personality research for understanding mental health, ethical behavior, and individual flourishing.

• Autonomous Systems
• Signal Processing
• Vehicle Health Management
• +7 more

Dr Ivan Petrunin is a Research Professor in Signal Processing for Autonomous Systems and a DARTeC Fellow at Cranfield University's School of Aerospace, Transport and Manufacturing. His work focuses on advancing sensor technologies, data fusion, and decision-making systems for Cyber-Physical Systems, with applications in aerospace, ground-based autonomous systems, and urban air mobility. Key areas include Position, Navigation and Timing (PNT), vehicle health management, and AI-driven fault detection. He leads research at facilities like the Muti-User Environment for Autonomous Vehicle Innovation (MUEAVI) and collaborates with industry partners like Airbus, Rolls-Royce, and Thales. Education: BSc and MSc in Design of Electronic Equipment from National Technical University of Ukraine (1996–1998), followed by a PhD in Signal Processing for Condition Monitoring from Cranfield University (2013). Prior to Cranfield, he was a Lecturer in Digital Signal Processing at NTU Ukraine (2001–2005). Research Interests: Autonomous Systems & Sensor Fusion Machine Learning in Navigation and Safety GNSS Integrity & Urban Air Mobility Condition Monitoring & Structural Health Multi-Agent Reinforcement Learning Publications: Over 100 journal/conference articles and book chapters, with recent works emphasizing hybrid sensor fusion, resilient navigation architectures, and AI-driven solutions for GNSS-denied environments. Notable contributions include multi-sensor fusion frameworks for UAVs and Bayesian filter innovations. Awards: FRIN Fellowship, SMAIAA Membership, IEEE and ION Fellowships, and FHEA recognition. His work is supported by ESA, Innovate UK, and EPSRC. Advising & Labs: Supervises PhD students in UAV navigation and machine learning. Leads Cranfield's facilities for autonomous systems experimentation and advanced timing node infrastructure.

Shivanjali KhareView profile

Assistant Professor

• Internet of Things (IoT) Data Security
• Hybrid Cryptography
• Wireless Sensor Technologies
• +3 more

Dr. Shivanjali Khare is an Assistant Professor in the Computer Science department at the University of New Haven, affiliated with the Tagliatela College of Engineering. She leads the SARI (Security and ARtificial Intelligence) Research Lab and teaches courses in Artificial Intelligence and Data Mining. Her research focuses on enhancing cybersecurity through hybrid cryptography, IoT data security, machine learning, and wireless sensor technologies to empower user protection in the digital age. Education: Ph.D. and M.S. in Computer Science from the University of Louisiana at Lafayette (2021 and 2016, respectively). Research Interests: IoT Data Security Hybrid Cryptography Systems Wireless Sensor Networks Big Data Sharing Mechanisms AI-Driven Cybersecurity Solutions Publications highlight contributions in IoT security protocols, cryptographic algorithm optimization, and machine learning applications. Notable work includes energy-efficient secure IoT drone systems (ESIoD) and ensemble learning for anomaly detection in smart homes. Recent outreach includes conducting cybersecurity seminars for senior citizens through the New Haven Free Public Library, demonstrating her commitment to societal impact and public education.

Tsung-Yi HoView profile

Professor

• Design Automation for Microfluidic Biochips
• Nanometer Integrated Circuits
• Embedded Systems
• +3 more

Tsung-Yi Ho is a Professor in the Department of Computer Science at National Tsing Hua University, Taiwan. He holds the Hans Fischer Fellowship at the Technical University of Munich's Institute for Advanced Study (TUM-IAS). His primary research focuses on design automation for microfluidic biochips and nanometer integrated circuits, emphasizing reliability, optimization, and interdisciplinary applications in bioengineering. Ho received his Ph.D. in Electrical Engineering from National Taiwan University in 2005. He has held positions at National Cheng Kung University and National Chiao Tung University before joining National Tsing Hua University. His work bridges algorithmic design with practical biochip fabrication, addressing challenges like contamination control, routing optimization, and fault tolerance in microfluidic systems. His research interests span design automation for emerging technologies, including paper-based biochips and 3D microfluidic architectures. He has pioneered methods for integrating hardware-software co-design principles into biochip development, enhancing both functionality and reliability. His contributions include novel routing algorithms, contamination mitigation techniques, and reliability-aware synthesis frameworks. Ho has authored over 100 publications, including influential papers in IEEE Transactions on CAD and ACM journals. He serves on the editorial boards of multiple top-tier journals and chairs professional chapters for ACM and IEEE. His awards include the Humboldt Research Fellowship, Dr. Wu Ta-You Memorial Award, and Best Paper Awards at VLSI Test Symposium and IEEE Transactions on CAD. His current projects involve optimizing control-fluidic co-design for paper-based biochips and developing AI-driven frameworks for microfluidic functionality prediction. He collaborates widely, leading cross-disciplinary initiatives at TUM-IAS and Taiwan's academic institutions.

• Control Systems
• Machine Learning
• Robotics
• +6 more

Marko Tanasković is a researcher at Singidunum University's Faculty of Informatics and Computing, specializing in control systems, robotics, and electrical engineering. He holds a PhD from ETH Zurich (2015) in Information Technology and Electrical Engineering, following degrees from University of Belgrade (BEng, 2009) and ETH Zurich (MEng, 2011). His research focuses on adaptive control systems, machine learning applications in engineering, and sensorless motor control. Key contributions include: Development of predictive algorithms for traffic systems and industrial automation Innovations in rotor orientation determination for PMSM motors Integration of AI in fraud detection and building climate control Recent work includes a 2024 study on wearable health monitoring devices and a 2022 paper on drone forensics. He has authored/co-authored over 15 peer-reviewed articles and holds patents in motor control technologies. Current affiliations include Singidunum University's Department of Electrical Engineering and Collaboration with ETH Zurich alumni networks. Active in international conferences such as Sinteza and IEEE events.

Luca MottolaView profile

Professor

• Battery-less IoT
• Mobile Space Robotics
• Smart Cities
• +3 more

Luca Mottola is a Full Professor at Politecnico di Milano and Senior Researcher at RI.SE Sweden. He leads the Networked Embedded Software Lab (NESLab), focusing on next-generation IoT, battery-less systems, and mobile robotics. His work bridges embedded computing, wireless networks, and cyber-physical systems, with applications in smart cities and space robotics. Education: No explicit details provided in texts. Research interests include energy-harvesting IoT, drone communication, and real-time systems. Notable awards include the ACM SENSYS Test of Time Award (2022) and multiple Best Paper Awards at top conferences like MOBICOM and RTCSA. Grants/Projects: Overseen projects on battery-less IoT, drone localization, and energy-efficient systems. Editorial roles include IEEE Transactions on Mobile Computing and ACM Transactions on Sensor Networks. Labs/Teams: NESLab, FlyZone Testbed for aerial drones, and collaborations with NXP Technologies, TU Graz, and USC.

Damir IsovicView profile

Associate Professor

• Real-Time Systems
• Embedded Systems
• Scheduling Algorithms
• +3 more

Damir Isovic is an Associate Professor and Vice-Chancellor for Internationalization at Mälardalen University's Academy of Innovation, Design and Technology. Previously, he served as Dean of the School of Innovation, Design and Engineering. His roles include leadership in academic administration and participation in national boards. He holds a PhD and has extensive international teaching experience. Research focuses on real-time systems, embedded systems design, and scheduling algorithms. Notable contributions include seminal work in real-time scheduling recognized by the IEEE Technical Community on Real-Time Systems. He has organized major conferences and delivered keynotes globally. His publications emphasize hybrid scheduling approaches, real-time operating systems (RTOS), media processing in resource-constrained systems, and MPEG standards. Recent work integrates memetic algorithms with fuzzy controllers and explores multi-core scheduling fairness. His research bridges theoretical scheduling models with practical embedded system implementations. No scientific awards explicitly listed in the text. Advising activities include supervising PhD students, though specific names are not provided. Lab affiliations include the Division of Networked and Embedded Systems, where he develops frameworks like GENESIS for embedded system engineering. His work emphasizes cross-disciplinary collaboration and industry partnerships in education and technology development.

• Sound Design
• Audiovisual Art
• Multisensory Experience
• +7 more

Associate Professor Darrin Verhagen is an award-winning sound designer and composer at RMIT University's School of Design, where he teaches in the Sound Design specialization within the Digital Media Program and directs the Audiokinetic Experiments (AkE) Lab. His academic work bridges creative practice with scientific inquiry into multisensory perception. Verhagen's research centers on the neurobiology of aesthetic experience, particularly exploring how sound interacts with vision, movement, and vibration. His work in the AkE Lab utilizes motion simulators, 4D cinema seating, and light to create installations that investigate the relationship between hearing, vision, movement and vibration. His academic background includes postgraduate research on musical extremes - lowercase sound for his Masters and Noise for his Doctorate. His creative output spans sound design for contemporary dance, theatre, installation, film, television and computer games. Verhagen has released over 20 albums internationally and performs audiovisual live shows globally. He was founder and curator of Dorobo records, which showcased Australian sound art for 15 years. Industry collaborations include work with Melbourne Theatre Company, Malthouse, Chunky Move, Australian Dance Theatre, and others. Notable awards include multiple Green Room Awards for Sound Design, Australian Academy of Cinema & Television Arts award finalist status, APRA Art Music awards finalist for experimental music, RMIT Research Award for technical innovation, and RMIT Teaching Award for excellence in teaching practice. Verhagen's supervision projects reveal a trajectory toward increasingly sophisticated explorations of sound in relation to space, perception, and human experience, with recent work focusing on transdisciplinary design, spatial sound applications, distributed audio systems, and vocal ecology. His work consistently bridges artistic practice with technological innovation and scientific inquiry into perceptual phenomena.

Mustafa HajijView profile

Assistant Professor

• Topological Deep Learning
• Graph Neural Networks
• Computational Topology
• +2 more

Mustafa Hajij is an Assistant Professor in the Data Science program at the University of San Francisco. He holds a PhD in Mathematics from Louisiana State University, an MS in Computer Science, and completed postdoctoral training at University of South Florida and Ohio State University. Previously, he served as Assistant Professor at Santa Clara University and as an AI Research Scientist at KLA Corporation. His research develops foundational frameworks for topological deep learning, including cell complex neural networks and geometric learning architectures that operate beyond graph domains. He leads the NSF-funded project 'A Unifying Deep Learning Framework Using Cell Complex Neural Networks' (DMS-2134231, $547,626). Recent publications establish new paradigms for topological representation learning, including combinatorial complexes and simplicial networks, with applications in computational biology, 3D vision, and drug discovery. He organized the ICML Topological Deep Learning Challenges and develops open-source tools like TopoX for topological learning.

Shashi Raj PandeyView profile

Assistant Professor

• Network Economics
• Game Theory
• Wireless Networks
• +7 more

Shashi Raj Pandey serves as Assistant Professor in the Department of Electronic Systems at Aalborg University's Technical Faculty of IT and Design, Denmark. His research is anchored in the Connectivity section and Connectivity Classique-Center for Classical Communication in the Quantum Era, with office location at Fredrik Bajers Vej 7C, C1-111, 9220 Aalborg Øst. His core research spans Network Economics, Game Theory, and Wireless Networks, with specialization in Decentralized Machine Learning and Semantic/Goal-oriented Communications. Current work integrates Digital Twin technologies with 6G systems for industrial automation and earth observation, emphasizing resource-efficient protocols for Internet of Things and edge intelligence applications. Recent publications (2024-2025) reveal a clear trajectory toward AI-6G convergence, featuring semantic communications for satellite imaging, game-theoretic network resource allocation, and digital twin implementations for autonomous systems. Key themes include communication efficiency in distributed learning and physical-digital world integration. Notable recognitions include: Best PhD Thesis Nominee (2021) Excellent Paper at Korea Software Congress, KIISE 2021 Student Best Paper Award at APNOMS 2019 Best Paper at Korea Software Congress, KIISE, 2018 Brain Korea 21st Century Plus Fellowship Academic service includes external PhD examination for EU SNS projects and peer review for premier conferences (AAAI, ICLR, ICML). His lab work within the Connectivity Classique-Center explores classical communication frameworks applicable to quantum-era networks, with focus on semantic information theory and decentralized network architectures.

George BosilcaView profile

Research Professor

• Distributed Algorithms
• Parallel Programming Paradigms
• High Performance Computing
• +3 more

George Bosilca is a Research Professor at the University of Tennessee, Knoxville, affiliated with the Department of Electrical Engineering and Computer Science and the Innovative Computing Laboratory. He holds a PhD in Computer Science (University of Paris XI, 2004) and an MS in Math and Computer Science (University of Paris XI, 1999). His research focuses on distributed algorithms, parallel programming paradigms, performance modeling/optimization, and resilience in programming models. He contributes to exascale computing initiatives through projects like PaRSEC and Open MPI. Key research areas include task-based runtimes, MPI standardization for exascale systems, and fault-tolerant distributed computing. His work emphasizes scalable and portable constructs for high-performance applications. Bosilca is involved with the Innovative Computing Laboratory (ICL) and collaborates on projects like the EPEXA ecosystem and Argobots threading framework. Recent publications highlight advancements in asynchronous many-task systems, GPU-accelerated collective operations, and resilience strategies for HPC platforms. His contributions span theoretical frameworks and practical implementations, bridging algorithmic innovation with real-world HPC challenges.

• Cyber-Physical Systems
• Internet of Things (IoT) Security
• Computer Architecture
• +5 more

Hokeun Kim is an Assistant Professor in the School of Computing and Augmented Intelligence (SCAI) at Arizona State University (ASU), part of the Ira A. Fulton Schools of Engineering. He previously held positions at Hanyang University (2021-2023) and worked in industry roles at Google, LinkedIn, and HP Labs. His research focuses on cyber-physical systems, IoT security, and computer architecture, with a particular emphasis on safety and security aspects of time-sensitive systems. Education: Ph.D. in EECS, University of California, Berkeley (2017) M.S. in EECS, Seoul National University (2012) B.S. in Computer Science and Engineering, Seoul National University (2010) Research Interests: Kim’s work spans secure IoT frameworks, real-time embedded systems, and edge computing. He develops tools like the Secure Swarm Toolkit (SST) and Lingua Franca, addressing challenges in distributed system security, interoperability, and performance. Key Contributions: Authored over 30 peer-reviewed publications in top venues like IEEE Transactions, ACM Conferences, and DATE. Received the ACM/IEEE Best Paper Award (IoTDI 2017) and IEEE Micro Top Picks Honorable Mention (2017). Active in organizing conferences (e.g., DATE, FDL) and serves on technical committees for top journals/conferences. Teaching: Courses include Computer Architecture I/II, Real-Time Embedded Systems, and IoT design at both undergraduate and graduate levels.