جست‌وجوی استاد و پژوهشگر

Travis Mandelمشاهده پروفایل

دانشیار

• Human-In-the-Loop AI
• Computer Vision
• Human-Computer Interaction (HCI)
• +۳ مورد دیگر

Travis Mandel is an Associate Professor in the Department of Computer Science at the University of Hawaii at Hilo (UH Hilo), serving as the Data Science Program Coordinator within the College of Natural and Health Sciences. He holds a PhD from the University of Washington's Paul G. Allen School of Computer Science and Engineering and a Bachelor's degree from Carnegie Mellon University. His research focuses on Human-In-the-Loop AI, bridging AI and Human-Computer Interaction (HCI), with applications in Computer Vision for environmental and climate science. He leads NSF-funded initiatives such as the NSF CAREER Award (2020) and NSF EPSCoR CHANGE HI (2022). His prior work includes reinforcement learning for educational games and error correction in wireless networks. Teaching includes courses like Python for Data Analysis (DATA 172), Artificial Intelligence (CS 440), and Computer Vision (DATA/CS 483). He has advised numerous undergraduate and graduate students, emphasizing interdisciplinary collaboration. Key awards include the Pattern Recognition Editor's Choice Award (2023) and Best Paper nominations in educational data mining (2013). His contributions span over 20 peer-reviewed publications, with a focus on AI ethics, human-AI collaboration, and environmental applications. He actively develops data science programs at small institutions and explores AI's role in democratizing scientific tools.

Ting Leiمشاهده پروفایل

دانشیار

• Geographic Information Science
• Transportation Geography
• Remote Sensing
• +۳ مورد دیگر

Ting Lei is an Associate Professor in the Department of Geography at the University of Kansas, located in Malott Hall #1021. His primary research interests focus on Geographic Information Science (GIS), including algorithmic development, geospatial computational methods, network analysis, location theory, and web GIS. He also explores remote sensing applications and advancements in GIS technology such as data structures, databases, computational geometry, and open-source software. His teaching covers GIS principles, transportation geography, and geo-computational methods. Dr. Lei's publications emphasize spatial data conflation, transportation network vulnerability, and optimization models for facility location. Recent works include studies on optimal spatial data matching, hub center interdiction problems, and unified location-allocation approaches integrating GIS and distributed computing. His research addresses real-world challenges in urban planning, water resources management, and celestial imaging analysis. Key research trends in his articles include computational GIS advancements, transportation infrastructure resilience, and interdisciplinary applications of geospatial technologies. No specific scientific awards are listed, though his extensive publication record highlights scholarly contribution. Advising and grants details are not provided in the text, but his active research in multiple geospatial domains indicates engagement with academic and applied projects.

Golnaz Habibiمشاهده پروفایل

استادیار

• Robotics
• Autonomous Driving
• Computer Vision
• +۴ مورد دیگر

Golnaz Habibi is an Assistant Professor in the School of Computer Science at the University of Oklahoma. She holds a PhD in Computer Science from Rice University and MS/BS degrees in Electrical and Control Engineering from Tarbiat Modares University. Her research focuses on robotics, autonomous driving, computer vision, multi-agent systems, machine learning, and reinforcement learning. She previously served as a Research Scientist at MIT's Department of Aeronautics and Astronautics and was affiliated with the Laboratory for Information and Decision Systems (LIDS). Education: Ph.D., Computer Science, Rice University M.S., Electrical and Control Engineering, Tarbiat Modares University B.S., Electrical and Control Engineering, Tarbiat Modares University Her research emphasizes visual navigation, autonomous control systems, and reliable communication in autonomous agents. Notable contributions include work on multi-agent coordination, neural network robustness, and human-robot interaction. Awards include the K2I Fellowship (2013) and a best student paper nomination at DARS 2012. Scientific Awards: Best Student Paper Nomination (DARS 2012) K2I Fellowship Award (2013) Her work bridges theoretical foundations and practical applications, with a focus on safety-critical systems. She has contributed to open-source robotics education initiatives and serves on the program committees of top conferences like AAAI and RSS. Labs & Teams: Her research group (AIR Lab) at OU develops solutions for autonomous systems, leveraging interdisciplinary approaches in robotics and AI.

Mingi Jeongمشاهده پروفایل

استادیار

• Computer Science
• Robotics
• Artificial Intelligence
• +۷ مورد دیگر

Mingi Jeong is a Ph.D. candidate in Computer Science at Dartmouth College and a member of the Reality and Robotics Lab under Prof. Alberto Quattrini Li. Starting December 2025, he will join Virginia Tech as a tenure-track Assistant Professor in the Aerospace and Ocean Engineering Department. His research focuses on autonomous systems for maritime environments, specifically robust decision-making in unstructured aquatic scenarios. Education: B.S. in Nautical Science (Korea Maritime and Ocean University), M.E. in Maritime Safety Engineering (Korea Maritime and Ocean University), and Ph.D. candidate at Dartmouth College. Key research interests include autonomous navigation for ASVs, obstacle detection/avoidance, multi-robot systems, and environmental monitoring. He has developed the SeePerSea dataset—the first multi-modal in-water object perception dataset—and pioneered intention-aware collision avoidance algorithms. His work combines robotics, AI, and ocean engineering for societal impact in search-and-rescue, cargo transport, and environmental surveillance. Notable awards include the 2025 Neukom Prize and MIT Postdoctoral Fellowship (declined). He has presented at top venues like IROS, RSS, and IEEE conferences globally. His lab emphasizes hands-on fieldwork and interdisciplinary collaboration.

• Computer Graphics
• 3D Computer Vision
• User Interaction
• +۵ مورد دیگر

Chi-Wing FU, Philip is a Professor in the Department of Computer Science and Engineering at The Chinese University of Hong Kong (CUHK). He holds dual roles in research and education, including Associate Editor-in-Chief of IEEE Computer Graphics and Applications. His research focuses on computer graphics, 3D vision, and human-computer interaction, with over 100 publications in top venues like SIGGRAPH, CVPR, and IEEE Visualization. Education: B.Sc. (1st Hons), Computer Science & Engineering, CUHK M.Phil., Computer Science & Engineering, CUHK PhD, Indiana University, Bloomington Research Interests: Dr. Fu's work spans 3D shape generation, computational LEGO design, AR visualization, and robotic interaction. He has pioneered projects like Make-A-Shape (large-scale 3D modeling) and DreamStone (text-driven 3D creation). His team also develops tools for medical data visualization and hand-object pose estimation. Recent Trends in Articles: Recent work emphasizes AI-driven creativity (e.g., LEGO art, text-to-3D systems) and real-time AR applications. His publications often bridge theory (e.g., generative models) with practical systems (e.g., user interfaces for design). Awards: Postgraduate Research Output Award (2023) MSRA Fellowship Nomination (2022) Best Associate Editor (IEEE CG&A) Outstanding Reviewer (ICCV 2021, CCF CAD/CG 2023) Advising & Grants: Supervised over 40 PhD/Master students and postdocs. Active in securing grants for projects like computational LEGO design (with Autodesk), medical AR visualization, and 3D generative AI. Collaborates with industry partners like Adobe and Huawei. Labs & Teams: Leads the Computational Design and Visualization Lab, focusing on 3D systems, robotics, and creative AI. Key projects include the LEGO Sketch Art toolchain and the HandShadowPoser AR system.

Amit K. Roy-Chowdhuryمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Robot Autonomy
• +۳ مورد دیگر

Amit K. Roy-Chowdhury is a Professor and UC Presidential Chair at the University of California, Riverside (UCR), where he chairs the Robotics Program and co-directs the UC Riverside AI Research (RAISE) Institute and the Center for Networked Configurable Command, Control, and Communications (NC4). He previously chaired the Department of Electrical and Computer Engineering at UCR. His research focuses on computer vision, machine learning, and robotics, with applications in autonomous systems and AI for science. Education: He holds a PhD in Electrical and Computer Engineering from the University of Maryland, College Park (2000), an MS in Systems Science and Automation from the Indian Institute of Science, Bangalore (1995), and a BEng in Electrical Engineering from Jadavpur University, Kolkata (1993). Research Interests: His work spans foundational areas of computer vision, image processing, and machine learning, with a focus on robot autonomy, statistical signal processing, and AI applications in science. His Vision and Learning Group has published over 250 peer-reviewed papers and leads DoD-funded research in AI and robotics. Recent Research Trends : His articles emphasize AI safety, domain adaptation, 3D scene understanding, and embodied agents. Themes include robustness to occlusion, ethical AI, and cross-modal learning. Awards : IEEE Fellow (2020), NAAI Fellow (2022), IAPR Fellow (2023), UCR Doctoral Mentoring Award (2019), UMD Distinguished Alumni (2020). Grants & Leadership : Leads a DoD Center of Excellence, oversees AI initiatives at RAISE, and collaborates with industry/government on AI, robotics, and medical imaging projects. His work on plant cell tracking and face recognition has gained media attention, including a PBS/National Geographic documentary. Labs & Teams : Directs the Vision and Learning Group (formerly Video Computing Group) and co-leads RAISE and NC4, fostering interdisciplinary research in AI and robotics.

Robert Howieمشاهده پروفایل

پژوهشگر ارشد

• Space Systems
• Small Spacecraft
• Intelligent Imaging Systems
• +۳ مورد دیگر

Dr. Robert Howie is a Research Fellow at Curtin University's School of Earth and Planetary Sciences, affiliated with the Faculty of Science and Engineering. He holds roles as Engineering Project Lead for the FireOPAL Space Domain Awareness Partnership and Unit Coordinator for the AERO3000 Space Systems Design course. Previously, he served as Research Engineer and DFN Technician for the Desert Fireball Network (DFN). His primary research focuses on Space Systems, Small Spacecraft, Intelligent Imaging Systems, Space Domain Awareness, Planetary Science, and Fireball Camera Networks. Robert's work bridges engineering expertise with interdisciplinary collaboration at Curtin's Space Science and Technology Centre. His research interests center on advancing space technology and planetary science through projects like the Desert Fireball Network, which tracks meteorites to understand solar system dynamics. He has contributed to CubeSat propulsion systems, meteoroid trajectory modeling, and global fireball observation networks. His engineering leadership in FireOPAL aims to enhance Australia's space domain awareness capabilities. Key contributions include developing automated observatories for the DFN and Global Fireball Observatory, as evidenced by his PhD thesis. His publications span meteorite recovery techniques, orbital analysis, and CubeSat thruster design. While no awards are explicitly listed, his involvement in high-impact collaborations like FireOPAL and the Desert Fireball Network underscores his scholarly impact. Robert advises projects in space systems design and mentors students through coursework. His work interfaces with global initiatives like the Hayabusa-2 mission and OSIRIS-REx observations, demonstrating cross-border scientific collaboration. He is actively engaged in advancing Australia's space sector through research and educational outreach.

Hadrien Devillepoixمشاهده پروفایل

پژوهشگر

• Planetary Science
• Meteoritics
• Astrophysics
• +۳ مورد دیگر

Hadrien Devillepoix is a Researcher at the School of Earth and Planetary Sciences (EPS) within Curtin University's Faculty of Science and Engineering. His work focuses on meteoritics, planetary science, and impact processes, with particular emphasis on meteoroid dynamics, atmospheric entry mechanics, and the origins of meteorites. He is a core member of the Desert Fireball Network (DFN), a large-scale observational project tracking meteorite falls globally. Research interests include analyzing fireball trajectories, reconstructing meteorite orbital histories, and investigating the composition and dynamics of cometary and asteroidal materials. Key contributions include the recovery of the Winchcombe meteorite (2020), a pristine carbonaceous chondrite, and studies on Oort Cloud material detected via atmospheric impacts. His work bridges laboratory analysis, observational astronomy, and computational modeling to understand Solar System evolution. Publications highlight innovations in meteorite recovery techniques (e.g., drone-based searches) and collaborations with international networks like FRIPON and CAMS. His research also addresses planetary protection protocols, impact hazard assessments, and the role of binary asteroids in shaping planetary cratering records.

Olov Anderssonمشاهده پروفایل

استادیار

• Autonomous Systems
• Robotics
• Artificial Intelligence
• +۵ مورد دیگر

Olov Andersson is an Assistant Professor and WASP Fellow in AI for Autonomous Systems at KTH Royal Institute of Technology, leading the Division of Robotics, Perception and Learning. His research focuses on Embodied AI for autonomous robots and vehicles, combining advancements in Vision-Language Models (VLM), Large Language Models (LLM), and real-world navigation challenges. Key projects include the DARPA SubT Challenge-winning team CERBERUS and the EU H2020 Heron project for robotic road repair. He supervises multiple PhD students and postdocs, including Timon Homberger, Finn Lukas Busch, and Jesper Eriksson. Research interests emphasize full-stack autonomy in dynamic environments, including planning, mapping, and navigation. Notable contributions include the OneMap real-time open-vocabulary mapping system and self-supervised scene flow methods like Seflow. He has been recognized for technical leadership in autonomous systems through awards like the WASP Fellowship. Professional activities include co-chairing the 2024 IROS workshop on robot perception in dynamic environments and advising the Swedish Prime Minister’s AI initiative. Teaching roles span multiple graduate courses in machine learning, robotics, and systems engineering at KTH.

• AI Ethics
• Network Analysis
• Machine Learning
• +۳ مورد دیگر

Dr. Doina Bucur is a prominent academic in the Electrical Engineering, Mathematics and Computer Science (EEMCS) faculty at the University of Twente. Her work bridges interdisciplinary research in AI ethics, network science, and computational sustainability. She leads the DECIDE project, which focuses on transparent AI decision-making systems impacting public services, healthcare, and insurance sectors. Her research spans machine learning applications in ecological networks, fault detection in sensor systems, and multi-objective optimization in social networks. She has pioneered methods for analyzing microbial community structures (e.g., gFlora), automated fault tree learning, and bias reduction in AI systems. Grants & Collaborations: Recipient of NWA ORC funding (2024) for the DECIDE initiative. Collaborates with over 50 researchers across disciplines including computer science, philosophy, law, and psychology. Active in developing evolutionary algorithms for network vulnerability analysis and multi-objective optimization. Labs & Teams: Core member of the Twente AI Ethics Lab and the Network Science Research Group. Leads interdisciplinary teams addressing real-world challenges through computational methods.

Boyu Kuangمشاهده پروفایل

پژوهشگر ارشد

• Semantic Segmentation
• Object Detection
• Weakly Supervised Learning
• +۹ مورد دیگر

Dr. Boyu Kuang is a Research Fellow in Computer Vision and Artificial Intelligence at Cranfield University, affiliated with the Centre for Computational Engineering Sciences. His work bridges academic research with industrial applications in aviation, robotics, and energy systems. Current role: Research Fellow in Computer Vision and AI Key affiliations: Centre for Computational Engineering Sciences Research interests include semantic segmentation , object detection , weakly and self-supervised learning , multi-modal perception , and vision-language foundation models . His methodology emphasizes robust AI systems for low-resource industrial environments , with applications in aviation maintenance , robotics , and energy infrastructure monitoring . He leads the Artificial Intelligence and Machine Learning module at Cranfield. Key activities include the UKRI, ATI, and Airbus-funded ONEHeart project on autonomous systems and intelligent inspection. Collaborations span Stanford University , King’s College London , Civil Aviation University of China , and industry partners like Airbus and Leidos . Publications focus on vision-language models , multi-modal perception , and industrial AI . As an Editorial Board Member for Discover Artificial Intelligence (Springer Nature), he contributes to academic governance. Peer review experience includes 60+ journal manuscripts for venues like IEEE Transactions on Image Processing and Elsevier Neural Networks . Facilities utilized include DARTeC and AIRC .

Scott Koziolمشاهده پروفایل

دانشیار

• Robotics
• Neuromorphic Engineering
• Embedded Systems
• +۹ مورد دیگر

Dr. Scott Koziol is an Associate Professor and Associate Chair in the Department of Electrical & Computer Engineering at Baylor University, College of Engineering. He is actively leading research and teaching in robotics, embedded systems, and neuromorphic engineering. PhD in Robotics, Georgia Institute of Technology (2013) MS in Mechanical Engineering, Georgia Institute of Technology (2011) MS in Electrical Engineering, Iowa State University (2000) BS in Electrical Engineering, Cedarville University (1998) His research focuses on robotics, neuromorphic engineering, embedded systems, and analog/digital signal processing . He develops bio-inspired algorithms for autonomous navigation and implements them using reconfigurable analog VLSI and Field Programmable Analog Arrays (FPAA). His work integrates machine learning with stochastic computing and explores event-based vision, quantum random number generation, and assistive technologies such as The Reminding Walker device. His recent publications span topics including autonomous path planning, millimeter-wave radar for biomechanics, stochastic neural networks, and quantum workforce development. These works appear in journals like IEEE Access , Entropy , and Quantum Science and Technology , reflecting a multidisciplinary approach that bridges robotics, computing, and biomedical applications. Best Live Demo Award, ISCAS 2010 Outstanding Poster Presentation Award, URSA Scholars Week 2016 Dr. Koziol advises numerous graduate and undergraduate students, including thesis authors in robotics and neuromorphic computing. His research is supported by sponsors such as DARPA, ONR, DOE, and Baylor’s internal programs. He leads the Neuromorphic & Robotic Systems Lab located at the Baylor Research and Innovation Collaborative (BRIC), where his team conducts cutting-edge work in hardware-based neural computation and autonomous systems.

• Machine Learning
• Compressed Sensing
• Privacy-Preserving Techniques
• +۴ مورد دیگر

Jia Liang is a researcher at Henan Polytechnic University's School of Electrical Engineering and Automation, with a focus on Machine Learning , Compressed Sensing , and Privacy-Preserving Techniques . His work bridges Computer Science and Signal Processing , particularly in Radar Imaging and Medical Image Analysis . Key Collaborations: Di Xiao, Ying Luo, Qun Zhang, Hui Huang Technical Expertise: Federated Learning, SAR Imaging, Compressive Sensing, Adversarial Learning His research emphasizes secure data processing in IoT and cloud environments, with recent innovations in cross-disciplinary applications like biosignal analysis for cysticercosis diagnosis . Publications span top venues including IEEE Transactions on Aerospace Systems and Remote Sensing . Notable trends include privacy-preserving machine learning for federated systems and 3D radar imaging of rotating targets, alongside medical imaging solutions for chest radiographs and optical coherence tomography .

• Computer Vision
• Pattern Recognition
• Biometrics
• +۳ مورد دیگر

Zhen Lei is a researcher at the National Laboratory of Pattern Recognition , Chinese Academy of Sciences, Beijing, China. His work focuses on Computer Vision , Biometrics , and Pattern Recognition . Research trends from his publications include Face Recognition , Anti-Spoofing , Person Re-Identification , 3D Face Reconstruction , and Vision Transformers . He has contributed to Information Fusion , Neural Networks , and Image Processing journals. Recent awards or affiliations with honorifics were not explicitly mentioned. Collaborative efforts are evident through co-authorship with experts in Face Detection , Domain Adaptation , and Medical Imaging .

• Machine Learning
• Maritime Engineering
• Robotics
• +۴ مورد دیگر

Shengkai Zhang is an active researcher with 26 publications and 444 citations spanning engineering, computer science, and environmental disciplines. His work demonstrates strong interdisciplinary collaboration through co-authorship with researchers like Kezhong Liu and Mozi Chen across multiple high-impact venues including IEEE conferences, arXiv, and specialized journals. His research interests center on Machine Learning applications in maritime systems , with significant contributions to Large Language Model integration for ship navigation, wireless sensing for bridge officer monitoring, and sensor fusion techniques. Additional expertise spans robotics perception (visual-inertial systems, mmWave radar enhancement), environmental modeling (urban energy systems, climate studies), and biomedical applications of traditional medicine. Recent work shows increasing focus on AI foundation models and their security implications. Zhang's publication trajectory reveals consistent output with accelerating impact since 2023, featuring 15+ papers in 2024 alone. His research clusters around three core themes: Maritime AI Systems (LLM navigation, track association, watchkeeping monitoring) Advanced Sensing Technologies (mmWave radar, Wi-Fi sensing, GNSS fusion) Environmental & Biomedical Applications (urban energy modeling, gut microbiome studies) These areas demonstrate both technical depth in signal processing/computer vision and practical focus on real-world engineering challenges.