جست‌وجوی استاد و پژوهشگر

Wei-Min Shenمشاهده پروفایل

عضو هیئت علمی

• Robotics
• Autonomous Systems
• Machine Learning
• +۴ مورد دیگر

Roles & Affiliations: Dr. Wei-Min Shen is a Research Associate Professor in the Computer Science Department at the University of Southern California (USC) and an Associate Professor of Computer Science Practice at the Viterbi School of Engineering. He serves as Director of the Polymorphic Robotics Laboratory, Associate Director of the USC Center for Robotics and Embedded Systems, and Research Leader at the Information Sciences Institute (ISI). Education: PhD in Computer Science from Carnegie Mellon University (1989), advised by Nobel Laureate Herbert A. Simon and co-advisor Jaime Carbonell. Research Interests: Dr. Shen focuses on autonomous robotics, self-reconfigurable systems (e.g., SuperBot), machine learning, artificial intelligence, and life science applications. His work emphasizes active model abstraction, surprise-based learning, and bio-inspired control mechanisms like the Digital Hormone Model (DHM). He has pioneered projects such as SuperBot, StarCell, and SOLAR, supported by grants from NSF, DARPA, NASA, and others. Awards & Recognition: - Silver-Medal Award in AAAI Robotics Competition (1996) - World RoboCup Championship (1997) - Phi Kappa Phi Faculty Recognition Award (USC, 2003) - 7 U.S. patents for robotics innovations. Teaching & Service: Courses taught include CS561 (AI), DSCI-553 (Data Mining), and CS360 (AI). He has chaired conferences like ICRA, IROS, and served on editorial boards for journals like IEEE Transactions on Mechatronics. His research has been featured in Science , Nature , and media outlets like CNN, BBC, and NHK. Labs & Projects: Leads the Polymorphic Robotics Lab at ISI, developing modular robots (e.g., SuperBot) and autonomous learning frameworks. Projects include Surprise-Based Learning (SBL), CONRO, and DataCrystal.

Seth Copen Goldsteinمشاهده پروفایل

دانشیار

• Programmable Matter
• Claytronics
• Reconfigurable Computing
• +۶ مورد دیگر

Seth Copen Goldstein is an Associate Professor in the Computer Science Department at Carnegie Mellon University's School of Computer Science. His research spans multiple interdisciplinary domains focusing on ensembles - large collections of interacting agents. He has made significant contributions to reconfigurable computing, molecular-scale devices, programmable matter, and more recently, the impact of technology on labor markets and alternative monetary systems. Education: PhD in Computer Science, University of California at Berkeley BS, Princeton University Goldstein's research agenda has evolved from reconfigurable computing to molecular-scale devices and programmable matter, and most recently to social technology and alternative monetary systems. His early work focused on compiling high-level programming languages directly into configurations for computing ensembles of gates. He then investigated molecular-scale circuits and programmable matter - ensembles of computing elements that can be programmed to change physical properties. Since returning from a startup, he has shifted focus to ensembles of people, studying technology's impact on labor markets and innovation, and developing social technologies to reduce poverty and inequality. His publication trends show a consistent focus on modular robotics, distributed systems, and programmable matter. The research spans theoretical foundations, hardware implementation, and programming languages for large-scale ensembles. Recent work emphasizes energy efficiency, distributed algorithms, and novel programming paradigms for heterogeneous systems. The interdisciplinary nature of his work connects computer science, electrical engineering, and social sciences. Research Leadership: Claytronics project - creating ensembles of cooperating submillimeter robots Development of Meld and LDP programming languages for ensemble systems Phoenix project - computing without processors Building on Local Trust (BoLT) initiative Goldstein has advised numerous PhD students who have gone on to positions at major technology companies including Microsoft Research, Sun Microsystems, and NEC Labs. His work has been supported by significant research grants focusing on modular robotics, programmable matter, and distributed computing systems. He has taught core computer science courses including Compiler Design, Introduction to Computer Systems, and Cloud Computing.

Pauline Poundsمشاهده پروفایل

استاد

• Drone design and aerodynamics
• Bipedal robot locomotion
• Embodied intelligence for robots
• +۵ مورد دیگر

Professor Pauline Pounds is a full Professor at the University of Queensland, jointly affiliated with the School of Electrical Engineering and Computer Science (Faculty of EAIT) and the Research Centre in Creative Arts and Human Flourishing (Faculty of HASS). She leads a broad robotics research portfolio centred on low-cost, high-performance drones, bipedal locomotion, embodied intelligence, disposable UAVs, exoskeletons and novel sensor systems. Education: Bachelor of Engineering – Australian National University Doctor of Philosophy – Australian National University Research interests span five thematic areas: (1) Drone design for extended range, efficiency and payload; (2) Low-cost bipedal robot locomotion; (3) Embodied intelligence enabling robots to exploit electromechanical dynamics without heavy computation; (4) Disposable, biodegradable UAVs for one-way missions; and (5) Human-augmenting exoskeletons for search-rescue and warehouse tasks. Her recent publications reveal concentrated effort in deep-reinforcement-learning-based robot control, tactile whisker sensors, lidar-based place recognition, modular aerial robots and real-world RL deployment—trends that emphasise cheap, robust autonomy and novel sensing. Funding & grants include current CSIRO “Robot-Enabled Autonomous Science” (2019-25), Wellcome Leap “Abdominal Laparoscopic Surgical Models with High-Fidelity Haptics” (2023-24), AuScope “EarthDrone” infrastructure (2023-25), and Advance Queensland / Trusted Autonomous Systems CRC “Integrated Sensors and Control” (2020-24), among others. PhD supervision: She has graduated four doctoral candidates to date (one as principal advisor, three as associate) and is currently available for new research students.

• Machine Learning
• Signal Processing
• Remote Sensing
• +۴ مورد دیگر

Wei Xue is an active academic researcher affiliated with Tsinghua University's Department of Computer Science and Technology. Their work spans multiple disciplines, including Machine Learning , Signal Processing , Medical Imaging , and Natural Language Processing . Key research areas include adversarial robustness in DNNs for remote sensing, hierarchical speaker representation learning for speech extraction, and multi-view fuzzy classification for brain network analysis. Recent publications focus on imbalanced data classification, spectrum sensing in cognitive radio, and innovative applications in soft robotics and medical diagnostics. Collaborations include institutions like Tsinghua University, Jiangnan University, and Hong Kong Baptist University, with frequent contributions to journals such as IEEE Transactions on Geoscience and Remote Sensing and Neural Networks .

Lulu Qianمشاهده پروفایل

استاد

• Biological Engineering
• Molecular Programming
• DNA Nanotechnology
• +۶ مورد دیگر

Lulu Qian is a Professor of Bioengineering at the California Institute of Technology (Caltech), leading the Qian Lab. She holds a B.E. from Southeast University (2002) and a Ph.D. from Shanghai Jiao Tong University (2007). Prior to her current role, she served as an Assistant Professor at Caltech (2013–2018). Her research focuses on designing molecular systems with programmable behaviors, including biochemical circuits, DNA neural networks, and molecular robots. These systems aim to mimic biological intelligence and perform tasks like pattern recognition, decision-making, and spatial organization at the molecular level. Her lab’s key projects include developing DNA strand displacement cascades for scalable computation, creating DNA-based neural networks capable of associative memory, and engineering molecular robots that perform collective tasks like cargo sorting. Notable achievements include the world’s smallest DNA-based Tic-Tac-Toe game, fractal assembly of DNA origami arrays, and a DNA robot capable of sorting molecules. Qian’s work bridges molecular engineering, computer science, and synthetic biology to advance nanotechnology and programmable matter. Her lab actively collaborates with Caltech’s graduate programs in Bioengineering, Computer Science, and Chemical Engineering. Current and past students have contributed to projects ranging from programmable DNA circuits to bio-inspired robotics. The lab emphasizes interdisciplinary training, preparing students for careers in academic research and industry innovation.

Daniela Rusمشاهده پروفایل

استاد

• Robotics
• Artificial Intelligence/ML
• Data Science
• +۵ مورد دیگر

Daniela Rus is the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT and Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL). She leads research in robotics, AI/ML, and autonomous systems, emphasizing soft robotics, mobile computing, and data-driven solutions. Her work spans theoretical and applied domains, including self-reconfiguring robots, AI for healthcare, and transportation optimization. Education: Earned her PhD in Computer Science from Cornell University. Recognized as a 2002 MacArthur Fellow, ACM Fellow, IEEE Fellow, and member of the National Academy of Engineering and American Academy of Arts and Sciences. Research focuses on robotics (soft robots, modular systems), AI applications (neural networks, generative models), and societal impacts (autonomous vehicles, data privacy). Projects include the Robot Garden educational platform, M-block modular robots, and AI-driven traffic optimization systems. Her lab, CSAIL, fosters interdisciplinary innovation across computer science, engineering, and biology. Publications highlight breakthroughs in robot design, algorithmic efficiency, and human-robot interaction. Current efforts explore AI for environmental monitoring, surgical robotics, and ethical autonomous systems. CSAIL hosts 100+ research groups, including the Distributed Robotics Lab and Embodied Intelligence Community.

Lining Yaoمشاهده پروفایل

دانشیار

• Programmable and Morphing Materials
• Computational Fabrication
• Design Practices
• +۵ مورد دیگر

Dr. Lining Yao is a Cooper-Siegel Associate Professor of Human-Computer Interaction at Carnegie Mellon University's School of Computer Science, directing the Morphing Matter Lab. She holds courtesy appointments in Mechanical Engineering and Materials Science & Engineering, and is part of the Softbotics initiative. With a PhD from MIT Media Lab (2017), her research focuses on programmable materials, sustainable design, and interdisciplinary fabrication. Yao is a UNIDO eco-design instructor, CMU Inclusive Teaching Fellow, and NSF CAREER Award recipient. Education: PhD in Media Arts & Sciences, MIT Media Lab (2017) Bachelor's/Master's (unspecified in text) Research Interests: Yao's work bridges material science, computation, and design to create adaptive systems. Key themes include morphing materials for sustainability, soft robotics, food engineering, and human-plant interaction. Her lab explores biodegradable actuators, self-folding devices, and energy-harvesting systems. Key Contributions: Notable projects include self-burying seed carriers (Nature 2023), morphing pasta (Science Advances 2021), and the Thermorph 4D printing system (CHI 2018). She co-founded MorphingMatter4Girls, promoting STEM engagement. Awards: NSF CAREER Award 9 Best Paper/Talk Awards Wired UK Fellowship Labs & Future Work: The Morphing Matter Lab develops eco-conscious materials and systems. Upcoming directions include LLM-driven generative design, programmable degradation mechanisms, and interdisciplinary physical AI systems.

Matthew Spenkoمشاهده پروفایل

استاد

• Robotics
• Soft Robotics
• Autonomous Systems
• +۳ مورد دیگر

Matthew Spenko is a Professor of Mechanical and Aerospace Engineering and Interim Department Chair at Illinois Institute of Technology's Armour College of Engineering . He co-leads the CARNATIONS UTC and leads the Welcome to the Jungle team in the XPRIZE Rainforest competition. Ph.D. in Mechanical Engineering from MIT, 2005 M.S. in Mechanical Engineering from MIT, 2001 B.S. in Mechanical Engineering from Northwestern University, 1999 His research focuses on robotics and soft robotics , including gecko-like adhesives for climbing robots, navigation integrity for autonomous vehicles, and granular-based soft robots for ecological applications. He explores robot mobility in challenging environments, transitioning from climbing robots to multimodal systems (flying/terrestrial) for rainforest biodiversity monitoring. Recent publications highlight advancements in navigation safety for autonomous systems, self-assembling robots , and electrostatic adhesives . Key trends include integrating SLAM with integrity monitoring , developing multi-modal transportation robotics , and enhancing safety protocols for urban autonomous vehicles. Dean’s Award for Excellence in Research, Armour College of Engineering, 2022 MMAE Excellence in Research Award, 2018 IIT/Bauer Family Excellence in Undergraduate Teaching Award, 2014 Best Paper, Planetary Rovers Session, Int. Society of Terrain-Vehicle Systems, 2011 Intelligence Community Postdoctoral Fellowship, 2005-2007 Spenko collaborates with institutions like Purdue University on ecological projects and mentors teams in competitions. He integrates educational initiatives through specialized courses on navigation and autonomous systems within CARNATIONS.

Jessica Sparksمشاهده پروفایل

استاد

• Polymer Engineering
• Biomedical Materials
• Dynamic Covalent Chemistry
• +۳ مورد دیگر

Dr. Jessica Sparks is a Professor in the Department of Chemical, Paper, and Biomedical Engineering at Miami University. She specializes in transforming traditional engineering education through innovative online course design, such as converting CPB 102 into a compressed Winter Term course. Her research focuses on dynamic polymer networks, self-healing materials, and biomedical applications. She emphasizes student engagement through interactive online tools and collaborative learning environments. Dr. Sparks has led NIH-funded projects and developed methods for 3D-printed biocompatible materials and responsive polymers. Her educational work includes redesigning curricula to enhance first-year engineering students' sense of belonging and identity through structured activities. This approach has been praised for fostering student success in online settings. Her research spans material science, with contributions to polymer architecture design, smart materials, and tissue engineering applications. Key projects include exploring thermoresponsive polymers and integrating computational modeling to predict material behavior. She has collaborated on interdisciplinary initiatives such as multiscale biomechanical modeling of liver tissue and developing wearable health monitoring devices using liquid metal electrodes.

Mitja Trkovمشاهده پروفایل

استادیار

• Wearable Robotics
• Biomechanics
• Human-Machine Interaction
• +۳ مورد دیگر

Dr. Mitja Trkov is an Assistant Professor in the Department of Mechanical Engineering at Rowan University's Henry M. Rowan College of Engineering. He holds a Ph.D. in Mechanical and Aerospace Engineering from Rutgers University and completed postdoctoral research at the University of Utah. His research focuses on robotics and human-machine interactions in biomedical applications, particularly wearable robotics, biomechanics, and ergonomics. Dr. Trkov's research integrates analytical and experimental approaches including dynamics and control, mathematical modeling, and human subject testing. His work spans several key areas: Wearable robotics for rehabilitation and assistance Human locomotion analysis including slip detection and recovery Soft robotics and physical human-machine interactions Biomechanical modeling of human movement His publications demonstrate consistent focus on human locomotion mechanics, robotic assistance systems, and fall prevention technologies. Recent work shows increasing emphasis on modular soft robotics, educational applications, and multi-modal sensing for human-robot interaction. Dr. Trkov maintains active grants including an NSF-funded project on 'Human-Inspired Robotic Assistance to Prevent Slip-Induced Falls' and an NJHF grant on 'Intelligent Soft Robotic Pad for Pressure Injury Prevention.' He advises multiple graduate students and leads the Robotics and Human Motion Laboratory, focusing on developing experimental platforms for human subject testing and robotic assistive devices.

Shree K. Nayarمشاهده پروفایل

استاد

• Computational Imaging
• Computer Vision
• Computer Graphics
• +۵ مورد دیگر

Shree K. Nayar is the T. C. Chang Professor of Computer Science in the School of Engineering at Columbia University, where he heads the Columbia Vision Laboratory (CAVE). He served as Department Chair from 2009-2012 and was Director of Research at Snap Inc. from 2018-2024. Nayar received his PhD from Carnegie Mellon University and has been at Columbia since 1991, progressing from Assistant to Full Professor. His educational background includes a PhD in Electrical and Computer Engineering from Carnegie Mellon University (1990), an MS from North Carolina State University (1986), and a BS from Birla Institute of Technology in India (1984). He began his career as a Research Engineer at Taylor Instruments in New Delhi before pursuing graduate studies. Nayar's research spans three interconnected areas: novel computational cameras that capture new forms of visual information, physics-based models for vision and graphics, and algorithms for scene understanding. His work in computational imaging has transformed digital photography, with applications in smartphones, robotics, virtual reality, and human-computer interfaces. His research has produced over 300 publications with nearly 60,000 citations and 80 patents. Analysis of his recent publications reveals a strong focus on computational imaging challenges including low-light vision, depth sensing, mobile interaction, and accessibility technologies. His work consistently bridges theoretical foundations with practical applications, as evidenced by commercial implementations of his assorted pixels technology in smartphone cameras. Elected to National Academy of Engineering (2008), American Academy of Arts and Sciences (2011), National Academy of Inventors (2014), and Indian National Academy of Engineering (2022) Okawa Prize (2023), IEEE PAMI Distinguished Researcher Award (2019) Two-time David Marr Prize winner (1990, 1995) - the highest honor in computer vision Multiple best paper awards at major conferences including SIGGRAPH Asia (2024) and ECCV (2024) National Young Investigator Award (1991), Packard Fellowship (1992) Nayar has supervised numerous PhD and Master's students throughout his career at Columbia. His lab has received continuous funding from NSF, industry partners, and foundations. The Columbia Vision Laboratory (CAVE) is known for its interdisciplinary approach, combining optics, hardware design, and algorithms to solve fundamental vision problems. Nayar's Bigshot Camera project demonstrates his commitment to education, providing hands-on learning experiences for students worldwide. The Columbia Vision Laboratory (CAVE) develops cutting-edge computational imaging and computer vision systems. Under Nayar's leadership, the lab has pioneered technologies including self-powered cameras, high dynamic range imaging systems, and novel computational cameras. The lab maintains strong industry connections, particularly through Nayar's role at Snap Research, and emphasizes translating research into real-world applications that benefit society.