جست‌وجوی استاد و پژوهشگر

Michael Kaessمشاهده پروفایل

دانشیار

• Robotics
• Computer Vision
• SLAM (Simultaneous Localization and Mapping)
• +۶ مورد دیگر

Michael Kaess is an Associate Professor at the Robotics Institute, Carnegie Mellon University (CMU), within the School of Computer Science. He leads the Robot Perception Lab (RPL) and contributes to the Field Robotics Center (FRC) and Computer Vision Group (CV). His research focuses on efficient perception algorithms for mobile robots, particularly in 3D mapping, SLAM, and sensor fusion using vision, LiDAR, inertial, and sonar data. Kaess holds a PhD in Computer Science from Georgia Tech and was a postdoc at MIT's Marine Robotics Lab. Education: Georgia Institute of Technology, PhD in Computer Science (2008) MIT, Postdoctoral Associate (2008–2010) Research Interests: Kaess develops algorithms for robust and efficient inference in robotics, emphasizing factor graphs and linear algebra. His work spans underwater robotics, aerial systems, tactile SLAM, and multi-sensor integration. Key areas include SLAM with planes/lines, imaging sonar reconstruction, and neural field methods for LiDAR-visual fusion. Publications: Over 145 papers, including work on EDPLVO (visual odometry), HoloOcean (underwater simulation), and neural radiance fields with LiDAR. Recent trends focus on robust incremental smoothing, acoustic-optical fusion, and real-time volumetric mapping. Awards: Recognized with the RSS Test of Time Award (2020), Outstanding Associate Editor (2022), and paper awards at ICRA/ICRA. Active in conference organization (IROS/ICRA program committees). Advising & Grants: Supervises 10+ current PhD/MSc students, with past advisees contributing to CoRL/ICRA work. Manages grants in perception, autonomy, and marine robotics. Teaches courses like Robot Localization and Mapping (16-833). Labs/Teams: Directs RPL, collaborates with FRC on field robotics. Develops open-source tools like GTSAM (GNU Toolkit for Smoothing and Mapping).

Chris Donahueمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Music Technology
• +۵ مورد دیگر

Chris Donahue is an Assistant Professor in the Computer Science Department at Carnegie Mellon University . He also serves as a part-time Research Scientist at Google DeepMind on the Magenta team. His work focuses on leveraging generative AI to enhance human creativity, particularly in music. Education: PhD in Computer Science (UC San Diego), Postdoctoral Scholar (Stanford University) His research spans controllable generative modeling of music and audio , with a focus on real-time interactive systems. Projects like Piano Genie , Beat Sage , and Copilot Arena demonstrate his commitment to real-world deployment. His Generative Creativity Lab (G-CLef) explores AI applications beyond music, including programming and natural language. Recent publications highlight advancements in multimodal music evaluation , real-time adaptation , and AI-driven sound morphing . He co-developed Magenta RealTime , an open-weight real-time music generation model, and MusicFX DJ Mode . Scientific Awards: Best Paper Award (top 1) at NAACL Student Research Workshop 2025 Best Paper Award (top 1% of submissions) at CHI 2025 Best Paper Runner-up at ISMIR 2021 He co-advises PhD students like Wayne Chi (NDSEG Fellow) and mentors Irmak Bukey . His lab receives support from the AIxArts incubator fund at CMU .

Sicun Gaoمشاهده پروفایل

دانشیار

• Algorithms and Optimization
• Automated Reasoning
• Cyber-Physical Systems
• +۳ مورد دیگر

Sicun Gao is an Associate Professor in the Computer Science and Engineering department at the University of California, San Diego. His research focuses on practical algorithms for NP-hard search and optimization problems in computational systems, emphasizing combinatorial perspectives in numerical and statistical contexts to achieve reliable autonomy. Research Interests: Automated reasoning, Hamilton-Jacobi reachability, safe reinforcement learning, control barrier functions, and optimization in cyber-physical systems. Teaching: Courses on AI search, optimization, and graduate research seminars. The 15 most recent publications highlight advancements in safe AI control, motion planning, and policy optimization, often integrating neural networks with formal verification. Awards include the IEEE Power & Energy Society Technical Committee Prize Paper Award and the IROS RoboCup Best Paper Award. He advises PhD students working on AI-driven control and robotics, with alumni placed at institutions like Seoul National University, Amazon, and Apple. Grants include NSF Career, Air Force Young Investigator, and DARPA Assured Autonomy funding. His lab develops tools like dReal for automated reasoning in nonlinear theories over the reals.

Andrea Bajcsyمشاهده پروفایل

استادیار

• Robotics
• Artificial Intelligence
• Reinforcement Learning
• +۷ مورد دیگر

Andrea Bajcsy serves as an Assistant Professor in the Robotics Institute and School of Computer Science at Carnegie Mellon University, leading the Interactive and Trustworthy Robotics Lab (Intent Lab). Her work focuses on enabling robots to safely interact with open-world environments through novel algorithms in control theory and machine learning. Her educational background includes a Ph.D. in Electrical Engineering & Computer Science from UC Berkeley under Anca Dragan and Claire Tomlin, followed by a postdoctoral position with Jitendra Malik and industry experience at NVIDIA's Autonomous Vehicle Research Group. Research centers on quantifying robot confidence, computing safe interaction policies for nuanced hazards (tearing, spilling, breaking), and aligning AI with human values. Key methodologies integrate optimal control, reinforcement learning, dynamic game theory, and deep learning, applied to robotic arms, quadrotors, quadrupeds, and autonomous vehicles. Core areas include safety for physical human-robot interaction, robot learning for manipulation, and world modeling. Recent publications (2024-2025) reveal a concentrated effort on uncertainty-aware safety mechanisms, out-of-distribution adaptation, and language-based safety specification. Her work increasingly bridges conformal prediction with interactive learning while leveraging vision-language models for real-time policy steering, as evidenced by multiple CoRL, RSS, ICRA, and ICLR acceptances. Scientific Awards: NSF CAREER Award (2025) Advises four active PhD students (Kensuke Nakamura, Ravi Pandya, Junwon Seo, Yilin Wu) and leads research funded by the NSF CAREER grant. Organizes community initiatives including the Northeast Systems and Control Workshop and ICRA workshops on Safely Leveraging VLMs in Robotics and Public Trust in Autonomy. Directs the Intent Robotics Lab, which develops theoretical frameworks and practical implementations for open-world robot safety. The lab maintains strong industry ties through NVIDIA collaborations and emphasizes real-world deployment across multiple robotic platforms.

Jiaoyang Liمشاهده پروفایل

استادیار

• Multi-Robot Coordination
• Artificial Intelligence
• Planning and Scheduling
• +۵ مورد دیگر

Jiaoyang Li is an Assistant Professor at the Robotics Institute, Carnegie Mellon University , where she leads research in large-scale multi-robot coordination. She earned her Ph.D. in Computer Science from the University of Southern California (2022) under Professor Sven Koenig and holds a B.Eng. in Automation from Tsinghua University (2017) . Ph.D. (2022): University of Southern California B.Eng. (2017): Tsinghua University Research Focus : Jiaoyang Li's work centers on algorithms for multi-robot coordination in dynamic environments. Key areas include: Multi-Agent Path Finding (MAPF) Lifelong Planning for Autonomous Systems Kinodynamic Motion Planning Warehouse and Transportation Automation Human-Robot Collaboration Integration of Planning and Machine Learning Swarm Robotics Publication Trends : Recent work spans 2023-2025 , showing emphasis on: Scalable coordination for 10,000+ robots Bézier curve optimization for dual-arm assembly Diffusion models in multi-robot motion planning Guidance graph optimization for airport/railway traffic Multi-objective search in warehouse automation Temporal plan graphs for switchable passing orders Scientific Honors : ICAPS-24 Best Student Paper Award Three top dissertation awards (ICAPS-23, IFAAAMAS, USC) 2023 League of Robot Runners champion Outstanding student paper award at ICAPS-20 Technology Commercialization Award from USC Student Leadership : Advises 5 Ph.D. students and 1 Master's student at CMU, with alumni now at MIT (Ying Feng) and USC (Yimin Tang). Collaborates with visiting students from National University of Singapore and Tsinghua University. Lab Affiliation : Directs the Artificial Intelligence for Robot Coordination at Scale (ARCS) Lab , focusing on: Warehouse automation with thousands of robots Multi-arm LEGO assembly systems Railway coordination algorithms Cooperative assembly with multiple manipulators

Zeynep Temelمشاهده پروفایل

استادیار

• Bio-Inspired Robotics
• Compliant Mechanisms
• Robotic Manipulation
• +۳ مورد دیگر

Zeynep Temel is an Assistant Professor at Carnegie Mellon University's College of Engineering, jointly appointed in the Biomedical Engineering and Robotics Institute. She leads the Zoom Lab, focusing on bio-inspired compliant mechanisms for robotic systems. Current research emphasizes adaptable robots for complex environments through mechanical intelligence and embedded control . Key application areas include surgical robotics , search-and-rescue , and micromanipulation . Her work spans bio-inspired design, compliant robotics, and human-centered applications. Recent publications highlight advancements in: Swarm robotics for collaborative exploration Soft actuators using bioplastics and gelatin Dexterous manipulation via delta robot frameworks The Zoom Lab trains students in robotic fabrication and biological modeling, with members transitioning to roles in academia and industry.

• Machine Learning
• Artificial Intelligence
• Explainability of AI
• +۳ مورد دیگر

Carlos Guestrin is the Fortinet Founders Professor of Computer Science at Stanford University and serves as Director of the Stanford AI Lab (SAIL) and Senior Fellow at the Institute for Human-Centered AI (HAI). He holds dual roles as Chief Scientist at Visual Layer and Virtue AI. His research focuses on machine learning methods, explainability, fairness, and ethics of AI, alongside systems for scalable AI deployment. Education details are not explicitly provided, but his work spans foundational contributions to machine learning systems (e.g., XGBoost) and explainable AI frameworks like Anchors and LIME. He emphasizes ethical AI through projects like CheckList for model testing and Model Equality Testing for API transparency. His scientific contributions include advancing optimization techniques (AdaScale SGD, TVM compiler) and ethical benchmarks for generative AI. He has been recognized as a Member of the National Academy of Engineering for his transformative impact on AI systems and their societal applications. Guestrin leads interdisciplinary initiatives at SAIL and HAI, fostering collaboration between technical innovation and human-centered design. His work bridges theory and practice, addressing challenges in healthcare (diabetes management systems) and AI security.

• Interactive Embedded Systems
• Haptic Actuation
• Surface Haptics
• +۷ مورد دیگر

Craig Shultz is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Illinois Urbana-Champaign and co-founder of Fluid Reality . His research focuses on interactive embedded systems and haptic actuation , particularly tactile interfaces for VR/AR, IoT, and wearable devices. He employs an interdisciplinary approach blending psychophysics, electrical and mechanical engineering, and human-computer interaction (HCI) to advance haptic rendering. Specializes in surface haptics , non-contact haptics , and electroosmotic pump arrays . Develops technologies for scalable shape displays , mid-air haptic interactions , and haptic-augmented spatial computing . Teaches Interactive Haptic Systems (since 2025). His research has led to 6 best paper awards and nominations at ACM and IEEE venues, including the IEEE Transactions on Haptics Best Application Paper of the Year (2018). He received the Sony Faculty Innovation Award (2025) and the IEEE Technical Committee on Haptics Early Career Award (2025) . His publications emphasize haptic rendering , low-latency touchscreens , and non-contact tactile actuation . He actively collaborates with institutions like Northwestern University and KAIST HCI . Key research areas: tactile interfaces, scientific engineering, VR/AR haptics, and haptic design practices. Technologies developed: Fluid Reality haptic gloves, DynaButtons, LRAir synthetic jets, and TriboTouch micro-patterned surfaces.

Carmel Majidiمشاهده پروفایل

استاد

• Soft Robotics
• Wearable Robotics
• Soft Electronics
• +۱۲ مورد دیگر

Carmel Majidi is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University's College of Engineering. He leads the Soft Machines Lab, where his research focuses on soft robotics, wearable computing, and advanced materials that mimic biological systems. His work enables robots and machines to safely interact with humans through soft, deformable technologies. Education: Ph.D. in EECS, University of California, Berkeley (2007) B.S. in Civil and Environmental Engineering, Cornell University (2001) His research interests span soft robotics, stretchable electronics, liquid metal materials, and bio-inspired engineering. He develops soft electromechanical materials for applications in haptics, medical devices, and human-machine interfaces. His group pioneers fabrication methods for soft composites and microfluidic systems that function as artificial skin, nervous tissue, and muscle. The recent trend in his publications highlights a strong focus on soft actuators, self-healing materials, liquid metal composites, and haptic interfaces for virtual and augmented reality. His work integrates materials science, robotics, and advanced manufacturing to enable scalable, robust, and practical soft systems. Scientific Awards: 2023 Inno Fire Award for Trailblazing Innovators, Pittsburgh Business Times Majidi leads a major research thrust in a new NSF Engineering Research Center (ERC) dedicated to improving robot dexterity, funded up to $52 million. He has been instrumental in developing soft robotic systems inspired by prehistoric organisms, such as the pleurocystitid, and in creating healthcare devices powered by body heat using liquid metal technologies. His research has been featured in Popular Science , Communications of the ACM , and Ars Technica . He is actively involved in advancing scalable manufacturing of soft electronics and enabling robust integration between soft materials and conventional microelectronics. His lab collaborates across disciplines to push the boundaries of physical AI and wearable robotics.

Haohan Wangمشاهده پروفایل

استادیار

• Trustworthy Machine Learning
• Computational Biology
• Healthcare Applications
• +۵ مورد دیگر

Haohan Wang is an Assistant Professor at the University of Illinois Urbana-Champaign's School of Information Sciences, with affiliations to the Carl R. Woese Institute for Genomic Biology and the National Center for Supercomputing Applications. His research focuses on developing trustworthy machine learning methods for computational biology and healthcare applications , emphasizing robustness , causality , and interpretability in vision-based models. Recent research trends in his work include: Large Language Model interactions with biomedical challenges (GenoAgent, GenoTex) Adversarial security in language and vision models (Guard, Jailbreakzoo) Genomic data analysis through robust machine learning frameworks (Precision Lasso, Kernel Mixed Models) Interactive toolkits like Robustar for data annotation and model training Scientific awards include recognition as Baidu's Top 50 AI+X Rising Young Scholars (2022), Best Paper Honorable Mention at WSDM 2023, and Broad Institute's Next Generation status (2019). Current projects explore AI-made scientists for biomedical discovery and Robustar development for GUI-based robust vision learning.

Henny Admoniمشاهده پروفایل

دانشیار

• Human-Robot Interaction
• Assistive Robotics
• Nonverbal Communication
• +۵ مورد دیگر

Henny Admoni is an Associate Professor in the Robotics Institute at Carnegie Mellon University (CMU), with a courtesy appointment in the Human-Computer Interaction Institute. She leads the Human And Robot Partners (HARP) Lab, focusing on assistive and collaborative robotics, particularly how robots can interpret human nonverbal cues like eye gaze to improve interactions. Her research spans healthcare, human-robot teamwork, and socially assistive robotics, supported by NSF, ONR, and industry partners. Admoni holds a PhD in Computer Science from Yale University and a BA/MA from Wesleyan University. Education PhD in Computer Science, Yale University BA/MA in Computer Science, Wesleyan University Research Interests Admoni’s work emphasizes human-centered robotics, including assistive systems for mobility-impaired users, driver situational awareness modeling, and fostering social support networks through AI. She investigates how robots can proactively learn from humans, adapt to team dynamics, and communicate transparently to build trust. Key themes include nonverbal communication, shared autonomy, and ethical design. Grants & Awards NSF CAREER Grant (2020) Okawa Research Grant (2021) A. Nico Habermann Career Development Professorship (CMU) Advising & Teaching Admoni advises graduate students on topics like robot learning, assistive systems, and human-robot teaming. She teaches courses on Human-Robot Interaction at both undergraduate and graduate levels, emphasizing interdisciplinary approaches that blend robotics, AI, and cognitive science. Labs & Projects The HARP Lab develops robots for meal preparation assistance, driving support, and socially assistive interventions. Current projects include the HARMONIC dataset for collaborative tasks and COHUMAIN for socio-cognitive architectures in human-machine teams. Admoni is on sabbatical at KTH University through 2025.

Drew Bridgesمشاهده پروفایل

استادیار

• Bacterial Biofilms
• Microbial Developmental Biology
• Quorum Sensing
• +۳ مورد دیگر

Drew Bridges is an Assistant Professor in the Department of Biological Sciences at Carnegie Mellon University, within the Mellon College of Science. His research focuses on understanding how bacteria make developmental decisions based on extracellular sensory information, with a specific emphasis on the formation and disassembly of bacterial biofilms in Vibrio cholerae . The Bridges Lab employs interdisciplinary approaches, including advanced imaging, genetics, biochemistry, and biophysics, to unravel the molecular mechanisms underlying biofilm dispersal and bacterial lifestyle transitions. Bridges earned a Ph.D. from Dartmouth College and completed a postdoctoral appointment at Princeton University. His work has pioneered novel imaging techniques to study biofilm dynamics and has revealed key insights into signaling pathways, matrix digestion, and motility components that control biofilm dispersal. The lab aims to uncover general principles of microbial behavior and apply these findings to combat infections and inform strategies for manipulating bacterial communities. Research interests extend to exploring how bacteria regulate lifestyle changes across scales—from molecular signaling to community-level behaviors. Future work seeks to expand studies to other microorganisms, identifying species-specific versus universal mechanisms. The lab also prioritizes fostering an inclusive, collaborative environment for trainees, emphasizing scientific rigor and innovation. Recent publications highlight advancements in understanding two-component signaling systems, quorum sensing, and biofilm dispersal mechanisms in Vibrio cholerae . These studies underscore the lab's focus on integrating experimental and theoretical approaches to address complex biological questions. Lab activities include managing a dynamic research group at the historic Mellon Institute building, established in 2022. Collaborative projects and grants are central to advancing their research, though specific grant details are not detailed in the provided texts. The lab website provides further information on ongoing studies and opportunities for trainees.

Kathleen Carleyمشاهده پروفایل

استاد

• Social Network Analysis
• Computational Social Science
• Text Mining
• +۴ مورد دیگر

Kathleen Carley is a Professor at Carnegie Mellon University, holding dual appointments in the Department of Electrical and Computer Engineering (College of Engineering) and the Institute for Software Research (ISR). She directs the Center for Computational Analysis of Social and Organizational Systems (CASOS), an interdisciplinary center specializing in network analysis, computational social science, and organizational theory. Her research focuses on dynamic network analysis, text mining, and modeling complex social systems, particularly in crisis response and cybersecurity contexts. Carley’s work integrates cognitive science, computer science, and organizational behavior to develop tools like ORA (statistical network analysis toolkit) and AutoMap (text-mining system). She leads the development of agent-based models such as BioWar (disease spread simulation) and DyNet (covert network dynamics). These tools address challenges in disaster communication, misinformation diffusion, and conflict escalation analysis. Her contributions include pioneering computational methods for analyzing social media bots, cross-platform information diffusion, and cyber defense strategies. Carley serves as founding co-editor of Computational and Mathematical Organization Theory and has co-edited influential works in computational social science. Her research spans global case studies, including analysis of Russian propaganda during the Ukraine invasion and Chinese influence campaigns on social media.

Zackory Ericksonمشاهده پروفایل

استادیار

• Human-Robot Interaction
• Rehabilitation and Health Care Robotics
• Robot Learning
• +۱۳ مورد دیگر

Zackory Erickson is an Assistant Professor at Carnegie Mellon University's Robotics Institute, leading the Robotic Caregiving and Human Interaction (RCHI) Lab. His work focuses on healthcare robotics, particularly empowering older adults and people with disabilities through assistive technologies. Research Interests: At the intersection of physically assistive robotics , robot learning , physics simulation , and haptic perception , Erickson develops methods for robotic caregivers to intelligently interact with humans. Key areas include physical human-robot interaction , deep learning , rehabilitation robotics , and deformable object manipulation . Notable trends in his recent publications include large language model integration for assistive robotics, electromyography control systems, and sim-to-real frameworks for human mesh recovery. His work emphasizes safe, adaptive human-robot collaboration in healthcare settings. Scientific Awards: Best Paper Nomination at HRI 2025 Best Paper Award at HRI 2024 He advises both PhD and Masters students in projects ranging from robotic feeding systems to wearable interfaces for mobility assistance . Teaching responsibilities include graduate courses on Mechanics of Manipulation and Human-Robot Interaction .

• Artificial Intelligence
• Robotics
• Motion Planning
• +۸ مورد دیگر

Maxim Likhachev is a Professor at the Robotics Institute and National Robotics Engineering Center , both within the School of Computer Science at Carnegie Mellon University (CMU). His research focuses on Artificial Intelligence and Robotics , particularly in real-time graph search algorithms , planning under uncertainty , and high-dimensional mobile manipulation . He co-founded TravelWits.com and RobotWits (acquired by Waymo), and his lab develops the Search-based Planning Library (SBPL), integrated into ROS. Research Themes : Graph search-based planning for deterministic and probabilistic domains Decomposition of hard planning problems into sequential graph searches Incremental algorithms for dynamic environments Experience-driven heuristic optimization Scientific Awards : Gold Edison Award (2013) for industrial mobile manipulator project DARPA Urban Challenge Winner (2007) for autonomous SUV navigation Students : Supervises current PhD students including Itamar Mishani , Muhammad Suhail Saleem , and Rishi Veerapaneni , alongside Masters students like Gabriel Olin . Past advisees include Dhruv Saxena (now at Uber), Michael Phillips (now at Uber), and Shivam Vats (now at Waymo). Lab & Projects : Leads the Search-based Planning Laboratory at CMU, working on systems like K-MAX helicopter , PR2 robots , and industrial mobile manipulators for tasks including autonomous paint stripping and aerial navigation.