| A | B | C | D | E | F | K | L | M | N | O | P | Q | R | S | |
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1 | Posters must fit on 30" x 40" boards. We will provide clips to attach posters to boards | ||||||||||||||
2 | Poster ID | Poster Title | First Name | Last Name | Poster Session | Poster board # | |||||||||
3 | 1 | Adaptive Contact-Implicit Model Predictive Control with Online Residual Learning | Wei-Cheng | Huang | Morning | 1 | |||||||||
4 | 2 | Learning-Based Pareto Optimal Control of Large-Scale Systems with Unknown Slow Dynamics | Saeed | Tajik Hesarkuchak | Morning | 2 | |||||||||
5 | 3 | CoVO-MPC: Theoretical Analysis of Sampling-based MPC and Optimal Covariance Design | Zeji | Yi | Morning | 3 | |||||||||
6 | 4 | Controlling Distributed Optimization using Structured Reinforcement Learning | Adit | Jain | Morning | 4 | |||||||||
7 | 5 | Market Power and Withholding Behavior of Energy Storage Units | Yiqian | Wu | Morning | 5 | |||||||||
8 | 6 | Decentralized Welfare Optimization for Energy Communities | Ahmed | Alahmed | Morning | 6 | |||||||||
9 | 7 | A Least-square Method for Non-asymptotic Identification in Linear Switching Control | Haoyuan | Sun | Morning | 7 | |||||||||
10 | 8 | Data-Driven Control with Inherent Lyapunov Stability | Youngjae | Min | Morning | 8 | |||||||||
11 | 9 | Replicable Function Approximation in Reinforcement Learning | Sikata | Sengupta | Morning | 9 | |||||||||
12 | 10 | Near Optimal Solutions of Constrained Learning Problems | Juan | Elenter | Morning | 10 | |||||||||
13 | 11 | Enhancing Task Performance of Learned Simplified Models via Reinforcement Learning | Hien | Bui | Morning | 11 | |||||||||
14 | 12 | Active Learning for Control-Oriented Identification of Nonlinear Systems | Bruce | Lee | Morning | 12 | |||||||||
15 | 13 | Geometric Tracking Control on Homogeneous Riemannian Manifolds | Jake | Welde | Morning | 13 | |||||||||
16 | 14 | Safe Deep Policy Adaptation | Wenli | Xiao | Morning | 14 | |||||||||
17 | 15 | Conservative safety critics via a binary bellman inequality | Agustin | Castellano | Morning | 15 | |||||||||
18 | 16 | Beyond Uncertainty: Risk-Aware Active View Acquisition for Safe Robot Navigation and 3D Scene Understanding with FisherRF | Guangyi | Liu | Morning | 16 | |||||||||
19 | 17 | Provable guarantees for generative behavior cloning: Bridging low-level stability and high-level behavior | Daniel | Pfrommer | Morning | 17 | |||||||||
20 | 18 | Approximate Optimal Controller Synthesis for Cart-Poles and Quadrotors via Sums-of-Squares | Lujie | Yang | Morning | 18 | |||||||||
21 | 19 | Learning-enabled safe control for hybrid systems | Shuo | Yang | Morning | 19 | |||||||||
22 | 20 | Reactive temporal logic based planning and control for interactive robotic tasks | Farhad Nawaz | Savvas Sadiq Ali | Morning | 20 | |||||||||
23 | 21 | Robust Autonomous Exploration: A Game-theoretic Perspective | Siming | He | Morning | 21 | |||||||||
24 | 22 | Agile But Safe: Learning Collision-Free High-Speed Legged Locomotion | Chong | Zhang | Morning | 22 | |||||||||
25 | 23 | Federated learning into Control | Han | Wang | Morning | 23 | |||||||||
26 | 24 | Data-Driven Modeling and Verification of Perception-Based Autonomous Systems | Thomas | Waite | Morning | 24 | |||||||||
27 | 25 | PrObE: Proprioceptive Obstacle Detection and Estimation in Cluttered Environments | Dhruv | Metha Ramesh | Morning | 25 | |||||||||
28 | 26 | Observation selection for nonlinear measurement models | Reza | Vafaee | Morning | 26 | |||||||||
29 | 27 | Learning Linear Dynamics from Bilinear Observations | Yahya | Sattar | Morning | 27 | |||||||||
30 | 28 | Efficient Reductions for Learning from Implicit Human Feedback | Gokul | Swamy | Afternoon | 1 | |||||||||
31 | 29 | Bayesian Priors for Efficient Linear Representation Learning | Leonardo Felipe | Toso | Afternoon | 2 | |||||||||
32 | 30 | Collaborative Bayesian Optimization with Privacy Preservation | Donglin | Zhan | Afternoon | 3 | |||||||||
33 | 31 | Finite-Time Guarantees for Suboptimal Online Control | Aren | Karapetyan | Afternoon | 4 | |||||||||
34 | 32 | Minimizing the Thompson Sampling Regret-to-Sigma Ratio (TS-RSR): a provably efficient algorithm for batch Bayesian Optimization | Zhaolin | Ren | Afternoon | 5 | |||||||||
35 | 33 | Blending Data-Driven Priors in Dynamic Games | Justin | Lidard | Afternoon | 6 | |||||||||
36 | 34 | Epidemic Population Games for Policy Design | Jair | Certorio | Afternoon | 7 | |||||||||
37 | 35 | Representation Learning for Control | Thomas | Zhang | Afternoon | 8 | |||||||||
38 | 36 | Data-driven Optimal Filtering for Linear Systems with Unknown Noise Covariances | Shahriar | Talebi | Afternoon | 9 | |||||||||
39 | 37 | Incentive Design for Sociotechnical Systems | Umar | Niazi | Afternoon | 10 | |||||||||
40 | 38 | Model-free Learning of Regions of Attractions via Recurrent Sets | Yue | Shen | Afternoon | 11 | |||||||||
41 | 39 | Network modeling of consumers’ selection of providers based on online reviews | Tian | Gan | Afternoon | 12 | |||||||||
42 | 40 | Constrained Passive Interactive Control: Leveraging Passivity and Safety for Robot Manipulators | Zhiquan | Zhang | Afternoon | 13 | |||||||||
43 | 41 | Towards a lightweight fully actuated aerial vehicle: Thrust Vectoring and Control Allocation Under Redundancy | Saibernard | Yogendran | Afternoon | 14 | |||||||||
44 | 42 | Integrated Hardware and Software Codesign for Controlling Underactuated Aerial Robots | Jack | Campanella | Afternoon | 15 | |||||||||
45 | 43 | Gameplay Filters: Safe Robot Walking through Adversarial Imagination | Kai-Chieh | Hsu | Afternoon | 16 | |||||||||
46 | 44 | Who Plays First? Optimizing the Order of Play in Stackelberg Games with Many Robots | Haimin | Hu | Afternoon | 17 | |||||||||
47 | 45 | MORALS: Analysis of High-Dimensional Robot Controllers via Topological Tools in a Latent Space. | Aravind | Sivaramakrishnan | Afternoon | 18 | |||||||||
48 | 46 | Friction-Cone-Constrained Quadratic Programming for Whole Body Control of Legged Robots | Brian | Acosta | Afternoon | 19 | |||||||||
49 | 47 | Learning Contact Dynamics Models via Vision and Physics | Bibit | Bianchini | Afternoon | 20 | |||||||||
50 | 48 | Running Controller for the Bipedal Robot Cassie | William | Yang | Afternoon | 21 | |||||||||
51 | 49 | Invariance, Performance, Feasibility and Extensions of Safety-Critical Reactive Control Techniques | Yifan | Xue | Afternoon | 22 | |||||||||
52 | 50 | Learning Dexterous In-Hand Translation with Compliant Tactile Skin | Jessica | Yin | Afternoon | 23 | |||||||||
53 | 51 | Practical Challenges in the Application of Conformal Prediction | Nandan | Tumu | Afternoon | 24 | |||||||||
54 | 52 | Back-stepping Experience Replay with Application to Model-free Reinforcement Learning for a Soft Snake Robot | Dong | Chen | Afternoon | 25 | |||||||||
55 | 53 | Sampling based MPC for contact rich manipulation | Sharanya Puthige | Venkatesh | Afternoon | 26 | |||||||||
56 | 54 | Nonlinear Iterative Learning Control using Model Predictive Path Integrals with Safe Set Projection | Zirui | Zang | Afternoon | 27 | |||||||||
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