جست‌وجوی استاد و پژوهشگر

Jin Woo Songمشاهده پروفایل

دانشیار

• Navigation and Sensor Systems
• Control Theory
• Estimation Theory
• +۷ مورد دیگر

Jin Woo Song is an Associate Professor in the Department of Artificial Intelligence and Robotics at Sejong University's School of Intelligent Mechatronics Engineering. He has held academic positions at Seoul National University and Hoseo University prior to joining Sejong University in 2017. His professional experience also includes serving as CTO/COO at Microinfinity Co., Ltd. from 2004-2014. Currently, he holds multiple leadership roles including Director of Sejong Enterprise Support Foundation, Director of SW-AI Convergence Center, and Provost of Sejong University. Dr. Song received his B.S., M.S., and Ph.D. in Control and Instrumentation Engineering/Electrical Engineering from Seoul National University. His educational background laid the foundation for his expertise in navigation systems and control theory. Dr. Song's research focuses on navigation and sensor systems, control theory, and estimation theory with applications in unmanned systems. His work spans MEMS inertial sensor technologies, Kalman filtering techniques, optimal and robust control theories, and fault detection algorithms. His research has significant applications in unmanned aircraft systems, autonomous vehicles, robotics, and military intelligence systems. His recent publications (2023-2025) demonstrate continued innovation in navigation systems, with emphasis on fault tolerance, sensor fusion, and improved positioning accuracy in challenging environments. His work shows strong trends toward integrating multiple sensor modalities and developing robust algorithms for real-world navigation challenges. Best student paper award, NAECON2000 (IEEE, National Aerospace and Electronics Conference), USA, 2000 Ministry Award, 'IT R&D Engineer of the Year', Ministry of Information and Communication, Republic of Korea, 2005 Best Presentation Award, ICASS 2015, 2015 Best Paper Award, KIEE Conference, 2019 Distinguished Teaching Award, Sejong University, 2021 Distinguished Research Award, Sejong University, 2022 Distinguished Professor, Sejong University, 2024 Dr. Song has served as Editor-in-Chief for ICROS journal and holds editorial positions for multiple prestigious journals including the International Journal of Aeronautical and Space Sciences. He has been actively involved in numerous research grants and industry collaborations, including a recent academic-industrial partnership with Hanwha Systems. As Vice-President of The Institute of Control, Robotics and Systems (ICROS) and various other professional organizations, he plays a significant role in shaping research directions in his field. He leads the Intelligent Navigation and Control Systems Lab at Sejong University, where his team develops cutting-edge navigation sensors and systems, optimal controllers for autonomous systems, and embedded systems for reliable navigation and control. The lab's work has direct applications in unmanned aircraft systems, autonomous vehicles, robotics, and military intelligence systems.

Roarke Horstmeyerمشاهده پروفایل

استادیار

• Computational Optics
• Machine Learning
• Biomedical Imaging
• +۵ مورد دیگر

Roarke Horstmeyer is an Assistant Professor of Biomedical Engineering at Duke University, with secondary appointments in Electrical and Computer Engineering and Physics. He leads the Computational Optics Lab, focusing on advancing optical imaging techniques through machine learning and algorithm design. His research includes developing multi-camera array microscopes (MCAMs) for high-throughput, gigapixel-scale imaging, and applying deep learning to improve biomedical diagnostics. Education: B.S. in Physics and Japanese from Duke University (2006), M.S. from MIT Media Lab (2011), Ph.D. in Electrical Engineering from Caltech (2016). Postdoctoral training included an Einstein Fellowship at Charité Medical School in Berlin and a role as Interim CTO at Kernel Inc. Research Interests: Computational optics, machine learning for hardware design, Fourier ptychography, diffuse correlation spectroscopy, and imaging neural activity in freely moving organisms. His lab collaborates with industry via startups like Ramona Optics and MIRA Inc. Key Achievements: Developed the multi-camera array microscope (MCAM) enabling 3D topographic imaging at cellular resolution. Awarded the APL Photonics Future Luminary Award (2021). Over 150 peer-reviewed publications in top journals like Nature Photonics, Optica, and Neurophotonics. Labs/Teams: Computational Optics Lab at Duke, collaborations with Erlangen School of Advanced Optical Technologies Grants: NSF, NIH, and industry partnerships supporting imaging innovation

• Machine Learning
• Computer Vision
• Structural Health Monitoring
• +۱ مورد دیگر

Senjian An is a Senior Lecturer in the School of Electrical Engineering, Computing and Mathematical Sciences at Curtin University, Faculty of Science and Engineering. His research focuses on machine learning, computer vision, and structural health monitoring, with applications in 3D displacement measurement and anomaly detection. Key interests include physics-guided neural networks, unsupervised learning for time-series data, and vision-based structural analysis. His recent publications emphasize robustness in damage detection, synthetic data generation, and transformer-based models for industrial monitoring. An's work integrates deep learning with engineering challenges, advancing non-contact measurement techniques for civil infrastructure. No students or awards are noted. Collaborative projects involve vibration analysis and maritime surveillance, reflecting a strong applied focus in AI and computer vision.

• Wireless Multimedia Networks
• Video Quality Assessment
• Machine Learning
• +۲ مورد دیگر

Professor Maria Martini is Course Director for MSc Network and Data Communications and MSc Mobile Networks and Media Streaming at Kingston University's Department of Networks and Digital Media. She leads the Wireless Multimedia Networking Research Group and holds a Laurea in Electronic Engineering (University of Perugia) and a PhD in Electronics and Computer Science (University of Bologna). Research interests include wireless multimedia networks, video quality assessment, machine learning, and medical applications. Recent articles focus on light-field visualization, medical imaging quality, and neuromorphic sensor data compression. Awards include recognition as a top 2% global scientist by Stanford University. Stanford University Top 2% World Scientist Extensive editorial experience includes IEEE Signal Processing Magazine and IEEE Transactions on Multimedia. Serves on boards for NetWorld2020 ETP and Video Quality Expert Group (VQEG).

Ying Liuمشاهده پروفایل

دانشیار

• Computer Vision
• Deep Learning
• Image and Video Coding
• +۴ مورد دیگر

Dr. Ying Liu is an Associate Professor in the Department of Computer Science and Engineering at Santa Clara University's School of Engineering. She serves as the Secretary/Treasurer of the APSIPA US Chapter and holds multiple leadership roles including APSIPA Distinguished Lecturer (2025-26) and Vice Chair of the APSIPA US Local Chapter. Her research focuses on deep learning applications for visual data processing and compression. Education: Ph.D., Electrical Engineering, SUNY at Buffalo, 2012 M.S., Electrical Engineering, SUNY at Buffalo, 2008 B.S., Telecommunications Engineering, Beijing University of Posts and Telecommunications, 2006 Dr. Liu's research spans deep learning-based image/video processing , coding for machines , and generative AI . Her work integrates convolutional neural networks, transformers, and generative models to advance video compression and machine vision systems. Current projects include vision-language models and point cloud coding, with emphasis on computational efficiency for real-world deployment. Analysis of her 15 most recent publications reveals a strong focus on neural video compression (40%), image coding for machines (30%), and generative AI applications (20%), with increasing emphasis on transformer architectures and multi-task frameworks since 2022. Her research bridges theoretical innovation with practical industrial applications in manufacturing and autonomous systems. Scientific Awards: Researcher of the Year Award, School of Engineering, Santa Clara University (2024) APSIPA Distinguished Lecturer Appointment (2025-26) Dr. Liu actively mentors PhD students in the Video and Image Processing (VIP) Laboratory, with four current advisees including Pengli Du (first PhD graduate in 2024). Her research is supported by significant grants including an NSF ERI award ($500K, 2022-2025), NVIDIA Academic Hardware Grant, and multiple industry-funded projects with Kwai Inc. totaling over $300K. She also secures internal university funding through Kuehler Undergraduate Research Grants and School of Engineering Research Grants. The VIP Laboratory develops deep learning solutions for the projected 13 billion global cameras by 2030, focusing on applications for mobile video sharing, surveillance, and autonomous vehicles. Current projects utilize CNNs, GANs, RNNs, and transformers for visual coding efficiency.

Angshuman Guinمشاهده پروفایل

پژوهشگر

• Intelligent Transportation Systems (ITS)
• Freeway Operations
• Connected and Autonomous Vehicles
• +۷ مورد دیگر

Dr. Angshuman Guin is a Senior Research Engineer at the School of Civil and Environmental Engineering, Georgia Institute of Technology. He returned to Georgia Tech as faculty in 2007 after industry experience. His research focuses on enabling data-driven decisions in transportation systems through innovations in data collection, quality assurance, and processing. Key areas include Freeway Operations, Connected/Autonomous Vehicles, Intelligent Transportation Systems, and Smart Cities. He co-founded InstaData Systems to translate research into practice. Dr. Guin holds a Ph.D. from Georgia Tech and serves on Transportation Research Board (TRB) committees including Information Systems, Human Factors, and Safety Management. He reviews for journals like IEEE Transactions on ITS and ASCE Journal of Transportation Engineering. His work spans 93+ publications, emphasizing simulation, emissions analysis, intersection safety, and digital twin frameworks. Recent projects include optimizing Atlanta’s MLK Smart Corridor using reinforcement learning, evaluating Restricted Crossing U-Turn emissions, and developing tools for autonomous vehicle merging behaviors. He collaborates with Georgia DOT and FHWA on projects like incident detection systems and corridor performance metrics. Dr. Guin’s research bridges theory and practice, contributing to safer, smarter transportation systems through advanced analytics and emerging technologies.

• Signal Processing
• Passive Radar Systems
• Electromagnetic Sensors
• +۳ مورد دیگر

María del Pilar Jarabo Amores is a Full Professor at the Department of Signal Theory and Communications, University of Alcalá. Her research focuses on passive radar systems, sensor networks, and signal processing for defense and surveillance applications. She leads the AES3 research group (Acoustic and Electromagnetic Smart Sensor networks and Signal processing) and has expertise in radar detection, clutter modeling, and target tracking. Education: PhD in Telecommunications Engineering from the University of Alcalá (2005), supervised by Dr. Francisco López Ferreras. Research Interests: Development of passive radar technologies using DVB-T/S signals, motion compensation algorithms, and AI-driven detection methods. Key application areas include drone surveillance, maritime monitoring, and urban traffic imaging. Her work emphasizes robust detection in cluttered environments and distributed sensor network architectures. Key Contributions: Pioneered motion compensation techniques for passive radar systems, designed smart antennas for improved coverage (e.g., Ku-band microwave video camera), and developed adaptive beamforming methods. Her group's IDEPAR demonstrator showcases passive radar capabilities for terrestrial traffic monitoring. Labs/Teams: Leads the AES3 group, collaborating on EU-funded projects involving SAR imagery analysis and oil spill detection. Active in developing sensor networks for critical infrastructure protection.

Ciaran Eisingمشاهده پروفایل

دانشیار

• Computer Vision
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Ciaran Eising is an Associate Professor in the Department of Electronics & Computer Engineering at the University of Limerick. His research focuses on computer vision, machine learning, and their applications in intelligent transportation systems, particularly autonomous driving and driver assistance systems. He is a member of the Centre for Sustainable Digital (Re)Manufacturing, Data-Driven Computer Engineering Research Centre, and Lero – the SFI Research Centre for Software. Education: PhD from the National University of Ireland Galway (2010), BE (2003). External roles include Senior Expert at Valeo Vision Systems (2009–2020) and Adjunct Lecturer at NUI Galway (2016–present). His expertise spans automotive vision systems, embedded systems, and sensor fusion. Research Interests: Driver Assistance Systems, Autonomous Driving, Object Detection, Motion Segmentation, and Sensor Fusion. Over 94 publications since 2007, with recent work on BEV perception, multimodal fusion, and DDoS mitigation in healthcare IoT. Grants/Advising: Accepting PhD students; collaborations include industry partnerships and cross-disciplinary research. Labs/Teams: Active in Lero and other university research centers, contributing to UN SDGs via sustainable transportation innovations.

• Computer vision
• Robotics
• Machine perception
• +۳ مورد دیگر

Christopher Hollitt is a Senior Lecturer and Programme Director of Electrical Engineering & Mechatronics at the School of Engineering and Computer Science, Victoria University of Wellington. His research focuses on developing autonomous mobile robots capable of interacting with dynamic environments through advanced visual perception systems. Dr. Hollitt holds a BE(Elec), BSc(Hon), and PhD from the University of Adelaide, Australia. His academic journey has led him to specialize in machine perception and robotic control systems. Dr. Hollitt's research interests center on machine perception, particularly machine vision, and the control of robotic and space systems. He aims to develop artificial robot 'minds' capable of perceiving and modeling the world in real time. His specific expertise includes active vision with time constraints, statistical underpinnings of active perception, vision-based estimation of robot pose, and multi-modal active perception systems. His work bridges the gap between theoretical computer vision and practical robotic applications, with emphasis on real-world implementation challenges. His publication record shows a clear progression from fundamental visual attention models to sophisticated context-aware object detection systems. Early work focused on color spaces and basic feature extraction, while recent research explores top-down contextual information integration and uncertainty modeling for improved target object detection. His approach increasingly incorporates evolutionary algorithms and probabilistic methods to create adaptive visual systems that can handle the complexities of real-world environments. Dr. Hollitt actively supervises graduate students, with current doctoral projects examining 'Low cost analysis of milk contaminants' and 'Droplet evaporation of complex fluids.' He previously supervised Jane, Celine's Master's research on spacecraft magnetic disturbance rejection. His grant history includes the 'Generic Shoulder Relief Appliance' project funded by the New Zealand Artificial Limb Service. Within the university, Dr. Hollitt contributes significantly to the academic community through his role as Programme Director and his teaching of advanced engineering courses, helping to shape the next generation of engineers and computer scientists.

Alexandra H. Techetمشاهده پروفایل

استاد

• Experimental Hydrodynamics
• Fluid Mechanics
• Ocean Engineering
• +۷ مورد دیگر

Prof. Alexandra H. Techet is a Professor of Mechanical and Ocean Engineering at MIT's Department of Mechanical Engineering. She leads the Experimental Hydrodynamics Laboratory (EHL), focusing on experimental investigations of hydrodynamics problems relevant to naval engineering and ocean science. Her research integrates advanced imaging techniques like 3D PIV/PTV and biomimetic design to study fluid-structure interactions, free surface flows, and unsteady propulsion mechanisms in marine systems. Prof. Techet holds a B.S.E. from Princeton University and M.S./Ph.D. from MIT's Joint Program with WHOI. Education: B.S.E. in Mechanical & Aerospace Engineering, Princeton University (1995) M.S. in Oceanographic Engineering, MIT/WHOI Joint Program (1998) Ph.D. in Oceanographic Engineering, MIT/WHOI Joint Program (2001) Research Interests: Prof. Techet's work addresses hydrodynamics challenges in naval systems and marine environments through experimental methods. Key areas include: Biologically inspired propulsion (fish swimming, jumping mechanics) Fluid-structure interaction in offshore platforms 3D imaging techniques for multiphase flows Water entry dynamics and spray hydrodynamics Development of autonomous underwater vehicles Her EHL lab employs cutting-edge experimental setups like light field cameras and synthetic aperture PIV for high-resolution flow visualization. Awards & Recognition: 2011, 2009, 2007, 2005 APS Gallery of Fluid Motion Prize 2004 ONR Young Investigators Award 2002-2004 Doherty Professorship for Ocean Utilization Teaching & Outreach: Prof. Techet teaches core courses in hydrodynamics and design principles for ocean engineering systems. She co-directs the Naval Engineering Education Center (NEEC) at MIT and advises the MIT Marine Technology Society chapter. Her pedagogy emphasizes hands-on learning through lab modules linked to ongoing research projects, such as biomimetic underwater vehicle design and offshore energy systems. Lab & Collaborations: The EHL collaborates with Woods Hole Oceanographic Institution to develop oceanographic instrumentation. Recent projects include studying archer fish jumping mechanics, unsteady vortical wakes, and high-speed ship hydrodynamics. Prof. Techet also explores applications of light field imaging for autonomous robotics and real-time flow analysis.

Michele D. Simoniمشاهده پروفایل

استادیار

• Transportation Systems Analysis
• Urban Mobility Planning
• Traffic Flow Simulation
• +۳ مورد دیگر

Michele D. Simoni is an Assistant Professor at the Department of Urban Planning and Environment at KTH Royal Institute of Technology in Stockholm, Sweden. He leads the project Investigating Sidewalks’ Mobility and Improving it with Robots (ISMIR) . His research focuses on advanced transportation systems, including last-mile freight optimization, autonomous vehicle impacts, and urban mobility policies. Education: Ph.D. in Civil Engineering (2019), University of Texas at Austin M.Sc. in Civil Engineering (2013), Delft University of Technology B.Sc. in Civil Engineering (2011), Polytechnic University of Milan Research Interests: Michele’s work integrates cutting-edge technologies like machine learning and sensor-based systems to address challenges in urban logistics, traffic management, and transportation policy. He has pioneered methods for curbside management, dynamic speed limit policies, and optimization of autonomous delivery systems. Grants & Projects: Current PI of ISMIR (2023–2025) and former postdoctoral research at MIT (2019–2020) and UT Austin (2015–2019). Active in collaborative projects on congestion pricing and automated vehicle integration. Labs & Teams: Leads the Transport Systems Analysis group at KTH, focusing on simulation frameworks for urban systems and robotics in logistics.

Karolina Westlingمشاهده پروفایل

مدرس ارشد

• Film Studies
• Media Studies
• Children's Media
• +۴ مورد دیگر

Karolina Westling is a Senior Lecturer at the Department of Cultural Sciences, University of Gothenburg, affiliated with the Aesthetics Unit. Her institutional contact details include email (karolina.westling@kultvet.gu.se), telephone (+46 31-786 53 34), and office location (Renströmsgatan 6, room E210A, Gothenburg). She remains actively engaged in research with publications spanning 2008–2024. Her research centers on film studies , media literacy , and children's rights , with emphasis on early childhood media exposure, gender construction in play and television, and resistance in explicit cinematic works. She explores intersections between moving image aesthetics, pedagogical applications of media, and social justice advocacy—particularly in Swedish and French cinema contexts—while examining how young children (under age 3) navigate television and film within domestic settings. Analysis of her publications reveals evolving focus from foundational studies on infant media consumption (2008–2014) toward contemporary societal critiques (2023–2024), including democratic citizenship through media literacy and intergenerational injustice in modern French film. Recurring themes involve children's agency, ethical media representation, and cultural resistance, consistently bridging academic theory with practical educational frameworks. Scientific Awards: No awards, fellowships, or medals were documented in the provided texts. Advising and Grants: No formal advisees (PhD/Master's students) were listed. No grant funding or project details were referenced in the source material. Labs and Teams: Westling operates within the Aesthetics Unit of the Department of Cultural Sciences, but specific labs, research teams, or collaborative structures were not detailed.

• Signal Processing
• Image Processing and Computer Vision
• Machine Learning Applications
• +۵ مورد دیگر

Professor Zdenka Babić is a full professor at the Department of General Electrical Engineering, Faculty of Electrical Engineering, University of Banja Luka. With a prolific research career spanning over two decades, she has established herself as a leading expert in signal processing, computer vision, and biohybrid systems. Her work bridges electrical engineering with biological applications, particularly in the innovative field of using honeybees for landmine detection. Professor Babić's research interests focus on signal processing applications, image analysis, machine learning, and embedded systems. Her pioneering work in biohybrid systems has gained international recognition, especially her research on using honeybees as biosensors for explosive detection. She has led numerous research projects exploring the intersection of electrical engineering and biological systems, developing sophisticated monitoring platforms for bee activity and environmental parameters. Her recent publications demonstrate a strong focus on practical applications of computer vision and signal processing, with emphasis on UAV video analysis, sensor fusion, and IoT-based monitoring systems. The research shows a clear trajectory toward increasingly sophisticated biohybrid systems that combine traditional engineering approaches with biological sensing mechanisms. Professor Babić has secured significant research funding from various national and international sources, including NATO Science for Peace and Security, European Commission programs, and the Ministry for Science, Technology Development and Higher Education of Republika Srpska. Her projects consistently involve interdisciplinary collaboration across engineering and biological sciences. She has been instrumental in developing electronic systems for remote monitoring of environmental parameters in bee yards, creating novel methods for honeybee counting and activity tracking, and establishing frameworks for biohybrid systems that leverage natural biological processes for security applications. Her work on bee-based landmine detection represents a unique intersection of entomology, electrical engineering, and humanitarian demining efforts.

Shubham Tulsianiمشاهده پروفایل

استادیار

• Computer Vision
• Robotics
• 3D Reconstruction
• +۳ مورد دیگر

Shubham Tulsiani is an Assistant Professor at Carnegie Mellon University's Robotics Institute and part of the Computer Vision group. His research focuses on building perception systems that infer spatial and physical structures from visual data, with applications in 3D vision and robotics. University: Carnegie Mellon University Academic Rank: Assistant Professor Research Group: Computer Vision His work emphasizes reducing reliance on manual supervision by leveraging physical world structure as a 'meta-supervisory' signal. Recent publications at CVPR, ECCV, and NeurIPS explore diffusion models for 3D reconstruction, physics-aware neural networks, and video-based perception systems. Scientific recognition includes: Best Student Paper Award, CVPR 2015 Finalist for Best Paper Award in Robot Manipulation, ICRA 2024 The group actively mentors PhD and MS students, with current advisees including Hanzhe Hu, Himangi Mittal, Qitao Zhao, and Yehonathan Litman. Former students like Yufei Ye and Homanga Bharadhwaj have moved to postdoctoral positions at Stanford and Meta respectively.

Kevin Huangمشاهده پروفایل

دانشیار

• Robotics
• Electrical Engineering
• Human-Robot Interaction
• +۳ مورد دیگر

Kevin Huang is an Associate Professor of Engineering at Smith College, specializing in robotics with a focus on teleoperation, human-robot interaction, and medical robotics. His work bridges engineering principles with applications in surgical robotics and operator interface design. Expertise in teleoperated robotic systems Research interests in haptic feedback and minimally invasive surgery Active in robotics outreach and education His recent research explores operator authentication, 3D viewpoint adjustment, and surgical tool segmentation. Huang also investigates security aspects in teleoperated systems and sensor-aided grasping techniques. Notable projects include visionless exploration of moving objects and transparent object manipulation, demonstrating technical versatility across robotics subdomains. No scientific awards are listed in available data. Education includes a Ph.D. and M.S.E.E. from the University of Washington, and a B.S. from Trinity College. He previously taught at Trinity College and chaired IEEE Robotics and Automation Society activities in Connecticut.