Faculty Candidate
Faculty Candidate Talk: Closing the Loop with Vision Feedback and Compliance in Robotic Manipulation
Areas of Interest: Grasping and Manipulation Abstract Robotic manipulation is a key functional requirement that is largely missing from the current state of the art regarding robots in unstructured environments. While models of manipulation phenomenon give us invaluable insights on various principles, many parameters (e.g. surface geometry, friction coefficients, contact locations) are difficult to [...]
Faculty Candidate Talk: Designing Robot Behavior in Human-Robot Interactions
Areas of Interest: Industrial Collaborative Robot, Autonomous Driving, Non-Convex Optimization, Distributed Conflict Resolution Abstract Human-robot interactions (HRI) have been recognized to be a key element of future robots in many application domains such as manufacturing, transportation, service and entertainment, which entail huge social and economic impacts. Technically, it is challenging to design the behavior [...]
Faculty Candidate Talk: Making sense of the physical world with high-resolution tactile sensing
Areas of Interest: Robotic Tactile Sensing, Robotic Perception Abstract: With the rapid progress in robotics, people expect robots to be able to accomplish a wide variety of tasks in the real world, such as working in factories, performing household chores, and caring for elderly. However, it is still very difficult for robots to act [...]
Faculty Candidate Talk: Extreme Motions in Natural and Synthetic Systems
Areas of Interest: Extreme motions of small-scale natural and synthetic systems Abstract: Small organisms can achieve extraordinary accelerations, speeds, and forces repeatedly throughout their lifespan with minimal costs. For example, bacteria can effectively swim in low Reynolds number environments, rotating their flagella at 100 Hz; mantis shrimp break clam shells with a single strike, [...]
Faculty Candidate Talk: Design and Evaluation of Everyday Interactive Robots
Areas of Interest: Human-Computer Interaction and Robotics Host: Aaron Steinfeld Admin Contact: Peggy Martin pm1e@andrew.cmu.edu As robots appear in more everyday environments, they will have new opportunities to enhance the lives of the people around them. Despite this potential gain, modern robots lack many of the necessary skills to effectively interact with people. In particular, almost all [...]
Faculty Candidate: David Braun
Areas of interest: Robotics, Optimal Control, System Dynamics, Impedance Control, Variable Impedance Actuators Host: Hartmut Geyer Admin Contact: Keyla Cook keylac@andrew.cmu.edu
Faculty Candidate: Ling-Qi Yan
Areas of Interest: Physically-based rendering, appearance modeling, molumetric scattering, light transport algorithms, sampling & reconstruction theory Host: Srinivasa Narasimhan Admin Contact: Nora Kazour nkazour@andrew.cmu.edu
Faculty Candidate: Computational Sensorimotor Learning
Areas of Interest: Artificial Intelligence Host: Abhinav Gupta Admin Contact: Chris Downey cdowney@andrew.cmu.edu Abstract: An open question in artificial intelligence is how to endow agents with common sense knowledge that humans naturally seem to possess. A prominent theory in child development posits that human infants gradually acquire such knowledge by the process of experimentation. [...]
Faculty Candidate: Designing interactive algorithms for human-robot collaboration
Areas of Interest: Robot control, human-robot interaction, artificial intelligence Abstract: We are on the cusp of a fundamental revolution in how robotics at large will be consumed by and assimilated into our everyday life. In the next decade, state of the art robot platforms will become easier to deploy, more accessible to purchase, and [...]
Faculty Candidate Talk: Adaptive Adversarial Learning for a Diverse Visual World
Areas of Interest: Computer vision and machine learning Abstract Automated visual recognition is in increasingly high demand. However, despite tremendous performance improvement in recent years, state-of-the-art deep visual models learned using large-scale benchmark datasets still fail to generalize to the diverse visual world. In this talk I will discuss a general purpose semi-supervised learning algorithm, [...]