Poster sessions

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The poster sessions will be hosted in the Houston Hall.

Session 1 (June 15, Thursday, 13:00-14:00)
Session 2 (June 15, Thursday, 16:30-17:30)
Session 3 (June 16, Friday, 13:00-14:00)
Session 4 (June 16, Friday, 16:15-17:15)

Click the headers to sort the table.

Paper #	Session #	Poster #	Authors	Title
2	3	2	Kwangjun Ahn, Zakaria Mhammedi, Horia Mania, Zhang-Wei Hong, Ali Jadbabaie	Model Predictive Control via On-Policy Imitation Learning
3	4	25	Michelle Guo, Yifeng Jiang, Andrew Everett Spielberg, Jiajun Wu, Karen Liu	Benchmarking Rigid Body Contact Models
7	1	9	Sourya Dey, Eric William Davis	DLKoopman: A deep learning software package for Koopman theory
8	1	14	Alireza Farahmandi, Brian Reitz, Mark Debord, Douglas Philbrick, Katia Estabridis, Gary Hewer	Hyperparameter Tuning of an Off-Policy Reinforcement Learning Algorithm for H∞ Tracking Control
10	3	26	Baris Kayalibay, Atanas Mirchev, Ahmed Agha, Patrick van der Smagt, Justin Bayer	Filter-Aware Model-Predictive Control
13	4	3	Bence Zsombor Hadlaczky, Noémi Friedman, Béla Takarics, Balint Vanek	Wing shape estimation with Extended Kalman filtering and KalmanNet neural network of a flexible wing aircraft
15	1	10	Killian Reed Wood, Emiliano Dall’Anese	Online Saddle Point Tracking with Decision-Dependent Data
16	1	5	Yue Meng, Chuchu Fan	Hybrid Systems Neural Control with Region-of-Attraction Planner
18	1	13	Aritra Mitra, Hamed Hassani, George J. Pappas	Linear Stochastic Bandits over a Bit-Constrained Channel
21	2	6	Guanchun Tong, Michael Muehlebach	A Dynamical Systems Perspective on Discrete Optimization
22	4	7	Ian Char, Joseph Abbate, Laszlo Bardoczi, Mark Boyer, Youngseog Chung, Rory Conlin, Keith Erickson, Viraj Mehta, Nathan Richner, Egemen Kolemen, Jeff Schneider	Offline Model-Based Reinforcement Learning for Tokamak Control
25	2	16	Gautam Goel, Naman Agarwal, Karan Singh, Elad Hazan	Best of Both Worlds in Online Control: Competitive Ratio and Policy Regret
27	3	3	Hengquan Guo, Zhu Qi, Xin Liu	Rectified Pessimistic-Optimistic Learning for Stochastic Continuum-armed Bandit with Constraints
28	1	16	Patricia Pauli, Dennis Gramlich, Frank Allgöwer	Lipschitz constant estimation for 1D convolutional neural networks
29	4	1	Han Wang, Leonardo Felipe Toso, James Anderson	FedSysID: A Federated Approach to Sample-Efficient System Identification
30	2	9	Doumitrou Daniil Nimara, Mohammadreza Malek-Mohammadi, Petter Ogren, Jieqiang Wei, Vincent Huang	Model-Based Reinforcement Learning for Cavity Filter Tuning
32	2	10	Tobias Enders, James Harrison, Marco Pavone, Maximilian Schiffer	Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems
33	3	5	Tahiya Salam, Alice Kate Li, M. Ani Hsieh	Online Estimation of the Koopman Operator Using Fourier Features
36	2	13	Nick-Marios Kokolakis, Kyriakos G Vamvoudakis, Wassim Haddad	Reachability Analysis-based Safety-Critical Control using Online Fixed-Time Reinforcement Learning
38	4	16	Zifan Wang, Yulong Gao, Siyi Wang, Michael Zavlanos, Alessandro Abate, Karl Henrik Johansson	Policy Evaluation in Distributional LQR
39	4	13	Sophia Huiwen Sun, Robin Walters, Jinxi Li, Rose Yu	Probabilistic Symmetry for Multi-Agent Dynamics
40	4	5	Majid Khadiv, Avadesh Meduri, Huaijiang Zhu, Ludovic Righetti, Bernhard Schölkopf	Learning Locomotion Skills from MPC in Sensor Space
41	2	3	Daniel Tabas, Ahmed S Zamzam, Baosen Zhang	Interpreting Primal-Dual Algorithms for Constrained Multiagent Reinforcement Learning
43	4	21	Rahel Rickenbach, Elena Arcari, Melanie Zeilinger	Time Dependent Inverse Optimal Control using Trigonometric Basis Functions
44	3	22	Antoine Leeman, Johannes Köhler, Samir Bennani, Melanie Zeilinger	Predictive safety filter using system level synthesis
45	2	14	Hancheng Min, Enrique Mallada	Learning Coherent Clusters in Weakly-Connected Network Systems
48	2	4	Elie Aljalbout, Maximilian Karl, Patrick van der Smagt	CLAS: Coordinating Multi-Robot Manipulation with Central Latent Action Spaces
51	1	11	Yingying Li, James A Preiss, Na Li, Yiheng Lin, Adam Wierman, Jeff S Shamma	Online switching control with stability and regret guarantees
53	1	7	Kong Yao Chee, M. Ani Hsieh, Nikolai Matni	Learning-enhanced Nonlinear Model Predictive Control using Knowledge-based Neural Ordinary Differential Equations and Deep Ensembles
54	2	5	Arnob Ghosh	Provably Efficient Model-free RL in Leader-Follower MDP with Linear Function Approximation
55	3	19	Tsun-Hsuan Wang, Wei Xiao, Makram Chahine, Alexander Amini, Ramin Hasani, Daniela Rus	Learning Stability Attention in Vision-based End-to-end Driving Policies
56	4	18	Alessio Russo, Alexandre Proutiere	Analysis and Detectability of Offline Data Poisoning Attacks on Linear Dynamical Systems
58	3	14	Lukas Kesper, Sebastian Trimpe, Dominik Baumann	Toward Multi-Agent Reinforcement Learning for Distributed Event-Triggered Control
59	2	23	Sydney Dolan, Siddharth Nayak, Hamsa Balakrishnan	Satellite Navigation and Coordination with Limited Information Sharing
61	1	18	Alex Devonport, Peter Seiler, Murat Arcak	Frequency Domain Gaussian Process Models for H∞ Uncertainties
62	3	10	Xinyi Chen, Edgar Minasyan, Jason D. Lee, Elad Hazan	Regret Guarantees for Online Deep Control
66	1	25	Deepan Muthirayan, Chinmay Maheshwari, Pramod Khargonekar, Shankar Sastry	Competing Bandits in Time Varying Matching Markets
67	3	18	Zhaolin Ren, Yang Zheng, Maryam Fazel, Na Li	On Controller Reduction in Linear Quadratic Gaussian Control with Performance Bounds
68	2	29	Rishi Rani, Massimo Franceschetti	Detection of Man-in-the-Middle Attacks in Model-Free Reinforcement Learning
69	3	17	Guanru Pan, Ruchuan Ou, Timm Faulwasser	Data-driven Stochastic Output-Feedback Predictive Control: Recursive Feasibility through Interpolated Initial Conditions
70	4	15	Joshua Pilipovsky, Vignesh Sivaramakrishnan, Meeko Oishi, Panagiotis Tsiotras	Probabilistic Verification of ReLU Neural Networks via Characteristic Functions
72	1	2	Panagiotis Vlantis, Leila Bridgeman, Michael Zavlanos	Failing with Grace: Learning Neural Network Controllers that are Boundedly Unsafe
73	2	1	Francesco De Lellis, Marco Coraggio, Giovanni Russo, Mirco Musolesi, Mario di Bernardo	CT-DQN: Control-Tutored Deep Reinforcement Learning
75	4	26	Reza Khodayi-mehr, Pingcheng Jian, Michael Zavlanos	Physics-Guided Active Learning of Environmental Flow Fields
76	3	13	Xiyu Deng, Christian Kurniawan, Adhiraj Chakraborty, Assane Gueye, Niangjun Chen, Yorie Nakahira	A Learning and Control Perspective for Microfinance
77	4	11	SooJean Han, Soon-Jo Chung, Johanna Gustafson	Congestion Control of Vehicle Traffic Networks by Learning Structural and Temporal Patterns
77	1	1	SooJean Han, Soon-Jo Chung, Johanna Gustafson	Congestion Control of Vehicle Traffic Networks by Learning Structural and Temporal Patterns
78	4	27	Adrien Banse, Licio Romao, Alessandro Abate, Raphael Jungers	Data-driven memory-dependent abstractions of dynamical systems
79	2	28	Jan Achterhold, Philip Tobuschat, Hao Ma, Dieter Büchler, Michael Muehlebach, Joerg Stueckler	Black-Box vs. Grey-Box: A Case Study on Learning Ping Pong Ball Trajectory Prediction with Spin and Impacts
80	3	4	Kehan Long, Yinzhuang Yi, Jorge Cortes, Nikolay Atanasov	Distributionally Robust Lyapunov Function Search Under Uncertainty
82	3	27	Saminda Wishwajith Abeyruwan, Alex Bewley, Nicholas Matthew Boffi, Krzysztof Marcin Choromanski, David B D’Ambrosio, Deepali Jain,Pannag R Sanketi, Anish Shankar, Vikas Sindhwani, Sumeet Singh, Jean-Jacques Slotine, Stephen Tu	Agile Catching with Whole-Body MPC and Blackbox Policy Learning
83	3	1	Tanya Veeravalli, Maxim Raginsky	Nonlinear Controllability and Function Representation by Neural Stochastic Differential Equations
86	3	20	Harrison Delecki, Anthony Corso, Mykel Kochenderfer	Model-based Validation as Probabilistic Inference
87	4	17	Xu Zhang, Marcos Vasconcelos	Top-k data selection via distributed sample quantile inference
90	4	20	An Thai Le, Kay Hansel, Jan Peters, Georgia Chalvatzaki	Hierarchical Policy Blending As Optimal Transport
91	4	22	Weiye Zhao, Tairan He, Changliu Liu	Probabilistic Safeguard for Reinforcement Learning Using Safety Index Guided Gaussian Process Models
94	4	12	Yuxiang Yang, Xiangyun Meng, Wenhao Yu, Tingnan Zhang, Jie Tan, Byron Boots	Continuous Versatile Jumping Using Learned Action Residuals
95	2	18	Armand Comas, Christian Fernandez Lopez, Sandesh Ghimire, Haolin Li, Mario Sznaier, Octavia Camps	Learning Object-Centric Dynamic Modes from Video and Emerging Properties
96	4	19	Valentin Duruisseaux, Thai P. Duong, Melvin Leok, Nikolay Atanasov	Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems
97	4	4	Luigi Campanaro, Daniele De Martini, Siddhant Gangapurwala, Wolfgang Merkt, Ioannis Havoutis	Roll-Drop: accounting for observation noise with a single parameter
98	3	12	Wenliang Liu, Kevin Leahy, Zachary Serlin, Calin Belta	CatlNet: Learning Communication and Coordination Policies from CaTL+ Specifications
100	3	24	Yuyang Zhang, Runyu Zhang, Gen Li, Yuantao Gu, Na Li	Multi-Agent Reinforcement Learning with Reward Delays
101	1	20	Cyrus Neary, Ufuk Topcu	Compositional Learning of Dynamical System Models Using Port-Hamiltonian Neural Networks
102	4	24	Prithvi Akella, Skylar X. Wei, Joel W. Burdick, Aaron Ames	Learning Disturbances Online for Risk-Aware Control: Risk-Aware Flight with Less Than One Minute of Data
104	1	3	Muhammad Abdullah Naeem, Miroslav Pajic	Transportation-Inequalities, Lyapunov Stability and Sampling for Dynamical Systems on Continuous State Space
106	1	28	Swaminathan Gurumurthy, J Zico Kolter, Zachary Manchester	Value-Gradient Updates Using Approximate Simulator Gradients to Speed Up Model-free Reinforcement Learning
107	3	28	Swaminathan Gurumurthy, Zachary Manchester, J Zico Kolter	Practical Critic Gradient based Actor Critic for On-Policy Reinforcement Learning
109	4	8	Yaqi Duan, Martin J. Wainwright, Martin Wainwright	Policy evaluation from a single path: Multi-step methods, mixing and mis-specification
110	1	19	Srinath Tankasala, Mitch Pryor	Accelerating Trajectory Generation for Quadrotors Using Transformers
112	2	27	Thomas TCK Zhang, Katie Kang, Bruce D Lee, Claire Tomlin, Sergey Levine, Stephen Tu, Nikolai Matni	Multi-Task Imitation Learning for Linear Dynamical Systems
113	3	6	Zihao Zhou, Rose Yu	Automatic Integration for Fast and Interpretable Neural Point Processes
114	2	7	Paula Gradu, Elad Hazan, Edgar Minasyan	Adaptive Regret for Control of Time-Varying Dynamics
115	1	12	Mingyu Cai, Calin Belta, Cristian Ioan Vasile, Erfan Aasi	Time-Incremental Learning of Temporal Logic Classifiers Using Decision Trees
116	3	7	Leilei Cui, Tamer Başar, Zhong-Ping Jiang	A Reinforcement Learning Look at Risk-Sensitive Linear Quadratic Gaussian Control
117	3	25	Thomas Beckers, Qirui Wu, George J. Pappas	Physics-enhanced Gaussian Process Variational Autoencoder
118	2	12	Guillaume O Berger, Sriram Sankaranarayanan	Template-Based Piecewise Affine Regression
119	1	26	Spencer Hutchinson, Berkay Turan, Mahnoosh Alizadeh	The Impact of the Geometric Properties of the Constraint Set in Safe Optimization with Bandit Feedback
120	2	25	Tianqi Cui, Thomas Bertalan, George J. Pappas, Manfred Morari, Yannis Kevrekidis, Mahyar Fazlyab	Certified Invertibility in Neural Networks via Mixed-Integer Programming
121	1	30	Sampada Deglurkar, Michael H Lim, Johnathan Tucker, Zachary N Sunberg, Aleksandra Faust, Claire Tomlin	Compositional Learning-based Planning for Vision POMDPs
124	1	8	Paul Griffioen, Alex Devonport, Murat Arcak	Probabilistic Invariance for Gaussian Process State Space Models
125	1	24	Xiaobing Dai, Armin Lederer, Zewen Yang, Sandra Hirche	Gaussian Process-Based Event-Triggered Online Learning with Computational Delays for Control of Unknown Systems
126	1	22	Kaiyuan Tan, Jun Wang, Yiannis Kantaros	Targeted Adversarial Attacks against Neural Network Trajectory Predictors
128	2	22	Lauren E Conger, Sydney Vernon, Eric Mazumdar	Designing System Level Synthesis Controllers for Nonlinear Systems with Stability Guarantees
131	2	17	Taha Entesari, Mahyar Fazlyab	Automated Reachability Analysis of Neural Network-Controlled Systems via Adaptive Polytopes
132	4	6	Yashaswini Murthy, Mehrdad Moharrami, R. Srikant	Modified Policy Iteration for Exponential Cost Risk Sensitive MDPs
133	2	19	Muhammad Abdullah Naeem	Concentration Phenomenon for Random Dynamical Systems: An Operator Theoretic Approach
134	1	27	Wenqi Cui, Linbin Huang, Weiwei Yang, Baosen Zhang	Efficient Reinforcement Learning Through Trajectory Generation
136	1	4	Zhuoyuan Wang, Yorie Nakahira	A Generalizable Physics-informed Learning Framework for Risk Probability Estimation
137	3	15	Luke Bhan, Yuanyuan Shi, Miroslav Krstic	Operator Learning for Nonlinear Adaptive Control
139	3	9	Yan Jiang, Wenqi Cui, Baosen Zhang, Jorge Cortes	Equilibria of Fully Decentralized Learning in Networked Systems
140	2	21	Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo Jovanovic	Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning
142	2	8	Anushri Dixit, Lars Lindemann, Skylar Wei, Matthew Cleaveland, George J. Pappas, Joel W. Burdick	Adaptive Conformal Prediction for Motion Planning among Dynamic Agents
144	4	2	Fernando Castañeda, Haruki Nishimura, Rowan Thomas McAllister, Koushil Sreenath, Adrien Gaidon	In-Distribution Barrier Functions: Self-Supervised Policy Filters that Avoid Out-of-Distribution States
145	2	20	Songyuan Zhang, Yumeng Xiu, Guannan Qu, Chuchu Fan	Compositional Neural Certificates for Networked Dynamical Systems
146	3	16	Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman	Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching
147	2	26	Yitian Chen, Timothy Molloy, Tyler Summers, Iman Shames	Regret Analysis of Online LQR Control via Trajectory Prediction and Tracking
148	1	17	Tejas Pagare, Konstantin Avrachenkov, Vivek Borkar	Full Gradient Deep Reinforcement Learning for Average-Reward Criterion
149	1	23	Rajiv Sambharya, Georgina Hall, Brandon Amos, Bartolomeo Stellato	End-to-End Learning to Warm-Start for Real-Time Quadratic Optimization
150	1	15	Keyan Miao, Konstantinos Gatsis	Learning Robust State Observers using Neural ODEs
151	4	28	Serban Sabau, Yifei Zhang, Sourav Kumar Ukil, Andrei Sperila	Sample Complexity for Evaluating the Robust Linear Observer’s Performance under Coprime Factors Uncertainty
153	3	23	Sarper Aydin, Ceyhun Eksin	Policy Gradient Play with Networked Agents in Markov Potential Games
154	2	11	Sheng Cheng, Lin Song, Minkyung Kim, Shenlong Wang, Naira Hovakimyan	DiffTune+: Hyperparameter-Free Auto-Tuning using Auto-Differentiation
156	3	8	Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn	Contrastive Example-Based Control
157	2	15	Orhan Eren Akgun, Arif Kerem Dayi, Stephanie Gil, Angelia Nedich	Learning Trust Over Directed Graphs in Multiagent Systems
158	1	21	Yaofeng Desmond Zhong, Jiequn Han, Biswadip Dey, Georgia Olympia Brikis	Improving Gradient Computation for Differentiable Physics Simulation with Contacts
160	4	23	Xunbi Ji, Gabor Orosz	Learning the dynamics of autonomous nonlinear delay systems
161	4	9	Yikun Cheng, Pan Zhao, Naira Hovakimyan	Safe Model-Free Reinforcement Learning using Disturbance-Observer-Based Control Barrier Functions
163	1	29	Kai-Chieh Hsu, Duy Phuong Nguyen, Jaime Fernández Fisac	ISAACS: Iterative Soft Adversarial Actor-Critic for Safety
165	3	21	Kaustubh Sridhar, Souradeep Dutta, James Weimer, Insup Lee	Guaranteed Conformance of Neurosymbolic Models to Natural Constraints
166	4	10	Pengzhi Yang, Shumon Koga, Arash Asgharivaskasi, Nikolay Atanasov	Policy Learning for Active Target Tracking over Continuous SE(3) Trajectories
167	2	24	Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra	Can Direct Latent Model Learning Solve Linear Quadratic Gaussian Control?
168	2	2	Bilgehan Sel, Ahmad Tawaha, Yuhao Ding, Ruoxi Jia, Bo Ji, Javad Lavaei, Ming Jin	Learning-to-Learn to Guide Random Search: Derivative-Free Meta Blackbox Optimization on Manifold
171	1	6	Adithya Ramesh, Balaraman Ravindran	Physics-Informed Model-Based Reinforcement Learning
172	4	14	Saber Jafarpour, Akash Harapanahalli, Samuel Coogan	Interval Reachability of Nonlinear Dynamical Systems with Neural Network Controllers
173	3	11	Karthik Elamvazhuthi, Xuechen Zhang, Samet Oymak, Fabio Pasqualetti	Learning on Manifolds: Universal Approximations Properties using Geometric Controllability Conditions for Neural ODEs