#### Publications

**2023**

- Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff.
**Instance-dependent Bounds for Zero-sum Matrix Games.**AISTATS 2023 (arxiv) - Roy Dong, Lillian J. Ratliff, Heling Zhang.
**Approximate Regions of Attraction in Learning with Decision-Dependent Distributions.**AISTATS 2023 (arxiv) - Sarah H.Q. Li, Yue Yu, Nicolas Miguel, Daniel Calderone, Lillian J.
Ratliff, Behcet Acikmese.
**Adaptive Constraint Satisfaction for Markov Decision Process Congestion.**Automatica (to appear), 2023 (arxiv) - Boling Yang, Liyuan Zheng, Lillian J Ratliff, Byron Boots, Joshua Smith.
**Stackelberg Games for Learning Emergent Behaviors During Competitive Co-evolution.**ICRA, 2023 - Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff.
**Minimax Optimization with Smooth Algorithmic Adversaries.**ICLR 2022 (arxiv) - Zhaoqi Li, Lillian Ratliff, Houssam Nassif, Kevin Jamieson, Lalit Jain.
**Instance-optimal PAC Algorithms for Contextual Bandits.**NeurIPS, 2022 (arxiv) - Ryann Sim, Stratis Skoulakis, Georgios Piliouras, and Lillian J. Ratliff.
**Fast Convergence of Optimistic Gradient Ascent in Network Zero-Sum Extensive Form Games.**SAGT, 2022 - Sarah Dean, Mihaela Curmei, Lillian J. Ratliff, Jamie Morgenstern,
Maryam Fazel.
**Multi-learner risk reduction under endogenous participation dynamics.**under review, 2022 (arxiv) - Sarah Li, Lillian J. Ratliff, Peeyush Kumar.
**General Sum Stochastic Games with Networked Information Flows.**ICLR Workshop on 'Gamification and Multiagent Solutions', 2022 - Yue Yu, Daniel Calderone, Sarah Li, Lillian J. Ratliff, Behcet Acikmese
**Variable Demand and Multicommodity Flow in Markovian Network Equilibrium.**Automatica 2022 (arxiv) - Mitas Ray, Lillian J. Ratliff, Dima Drusvyatskiy, Maryam Fazel.
**Decision-Dependent Risk Minimization in Geometrically Decaying Dynamic Environments.**AAAI 2022 (long version with appendix) - Adhyyan Narang, Evan Faulkner, Dmitriy Drusvyatskiy, Maryam Fazel, Lillian
J. Ratliff.
**Multiplayer Performative Prediction: Learning in Decision Dependent Games,**AISTATS 2022 (arxiv) - Chinmay Maheshwari, Chih-Yuan Chiu, Eric Mazumdar, S. Shankar Sastry,
Lillian J. Ratliff.
**Zeroth-Order Methods for Convex-Concave Minmax Problems: Applications to Decision-Dependent Risk Minimization.**2021 (arxiv) AISTATS 2022 - Dmitriy Drusvyatskiy, Maryam Fazel, Lillian
J. Ratliff.
**Improved Rates for Derivative Free Gradient Play in Monotone Games,**IEEE CDC, 2022 (arxiv) - Quoc Liem Vu, Zane Alumbaugh, Ryan Ching, Peter Ding, Arnav Mahajan, Ben
Chasnov, Sam Burden, Lillian J. Ratliff.
**Stackelberg Policy Gradient: Evaluating the Performance of Leaders and Followers.**ICLR Workshop on 'Gamification and Multiagent Solutions', 2022 (link) - Boling Yang, Liyuan Zheng, Lillian J. Ratliff, Byron Boots, Joshua R.
Smith.
**Stackelberg MADDPG: Learning Emergent Behaviors via Information Asymmetry in Competitive Games.**AAAI Workshop on Reinforcement Learning and Games, 2022 (link) - Tanner Fiez, Ryann Sim, Stratis Skoulakis, Georgios Piliouras, Lillian
J. Ratliff.
**Online Learning in Periodic Zero-Sum Games.**NeurIPS 2021 (arxiv) - Tanner Fiez, Lillian J. Ratliff, Eric Mazumdar, Evan Faulkner, Adhyyan
Narang.
**Global Convergence to Local Minmax Equilibrium in Classes of Nonconvex Zero-Sum Games.**NeurIPS 2021 - Tanner Fiez, Chi Jin, Praneeth Netrapalli, Lillian J. Ratliff.
**Minimax Optimization with Smooth Algorithmic Adversaries.**2021 (arxiv) - Roy Dong, Lillian J. Ratliff.
**Approximate Regions of Attraction in Learning with Decision-Dependent Distributions.**2021 (preprint pdf) - Tanner Fiez, Lillian J. Ratliff.
**Local Convergence Analysis of Gradient Descent Ascent with Finite Timescale Separation.**ICLR, 2021 (pdf link) [Alt. Title: Gradient Descent-Ascent Provably Converges to Strict Local Minmax Equilibria with a Finite Timescale Separation (arxiv) ] - Stratis Skoulakis, Tanner Fiez, Ryann Sim, Georgios Piliouras, Lillian
J. Ratliff.
**Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Games.**AAAI Conference on Artificial Intelligence, 2021 (arxiv) - Liyuan Zheng, Tanner Fiez,
Zane Alumbaugh, Benjamin Chasnov, Lillian
J. Ratliff.
**Stackelberg Actor-Critic: A Game-Theoretic Perspective**, to appear at AAAI 2022 (short version appeared at AAAI RLG Workshop, 2021). (extended preprint pdf) - Tanner Fiez, Lillian J. Ratliff.
**Gradient Descent-Ascent Provably Converges to Strict Local Minmax Equilibria with a Finite Timescale Separation.**AAAI RLG Workshop 2021. (extended arxiv version) - Liyuan Zheng, Yuanyuan Shi, Lillian J. Ratliff, Baosen Zhang.
**Safe Reinforcement Learning of control-affine systems with vertex networks.**Learning for Dynamics and Control (L4DC) 2021 (link), (arxiv) - Tanner Fiez, Lillian J. Ratliff.
**Gradient Descent-Ascent Provably Converges to Strict Local Minmax Equilibria with a Finite Timescale Separation.**2020 (arxiv) - Liyuan Zheng, Lillian J. Ratliff.
**Constrained Upper Confidence Reinforcement Learning**Learning for Dynamics and Control (L4DC) 2020 (link), (arxiv) - Sarah Li, Lillian J. Ratliff, Behcet Acikmese.
**Disturbance Decoupling for Gradient-based Multi-Agent Learning with Quadratic Costs.**IEEE Control System Letters (L-CSS) and CDC, 2020. (arxiv) - Tanner Fiez, Benjamin Chasnov, Lillian J. Ratliff.
**Implicit Learning Dynamics in Stackelberg Games: Equilibria Characterization, Convergence Analysis, and Empirical Study.**International Conference on Machine Learning (ICML), 2020. (arxiv, ICML link) -
Tanner Fiez, Nihar Shah, and Lillian J. Ratliff.
**A Super* Algorithm to Determine Orderings of Items to Show Users**. Uncertainty in Artificial Intelligence (UAI), 2020. (arxiv, UAI link) -
Eric Mazumdar, Lillian J. Ratliff, Micheal I. Jordan,
S. Shankar Sastry.
**Policy-Gradient Algorithms Have No Guarantees of Convergence in Linear Quadratic Games**. Autonomous Agents and Multi-Agent Systems (AAMAS), 2020. (arxiv) - Benjamin Chasnov, Daniel Calderone, Behcet Acikmese, Samuel Burden, Lillian J. Ratliff.
**The Local Stability of Equilibria in Two-Player Continuous Games.**CDC, 2020. (arxiv) -
Tanner Fiez
^{}, Lalit Jain^{}, Kevin Jamieson, and Lillian J. Ratliff.**Sequential Experimental Design for Transductive Linear Bandits**. NeuRIPs,*arxiv:1906.08399*, 2019. [ bib ] (arxiv) -
Eric Mazumdar, Lillian J. Ratliff, S. Shankar Sastry.
**On the Convergence of Gradient Based Learning in Continuous Games**. SIAM Journal on Mathematics of Data Science (SIMODS), 2019. (pdf) -
Jingjing Bu, Lillian J. Ratliff, Mehran Mesbahi.
**Global Convergence of Policy Gradient for Sequential Zero-Sum Linear Quadratic Dynamic Games**.*arxiv:1911.04672*, 2019. [ bib ] (arxiv) - Tanner Fiez, Benjamin Chasnov, Lillian J. Ratliff.
**Convergence of Learning in Stackelberg Games.**Smooth Games Optimization and Machine Learning Workshop: Bridging Game Theory and Deep Learning, NeuRIPS, 2019. - Benjamin Chasnov, Tanner Fiez, Lillian J. Ratliff.
**Opponent Anticipation via Conjectural Variations.**Smooth Games Optimization and Machine Learning Workshop: Bridging Game Theory and Deep Learning, NeuRIPS, 2019. - Eric Mazumdar, Lillian J. Ratliff, Shankar Sastry, Michael I. Jordan.
**Policy Gradient in Linear Quadratic Dynamic Games Has No Convergence Guarantees.**Smooth Games Optimization and Machine Learning Workshop: Bridging Game Theory and Deep Learning, NeuRIPS, 2019. -
Tanner Fiez, Nihar Shah, and Lillian J. Ratliff.
**A Super* Algorithm to Determine Orderings of Items to Show Users**.*workshop paper for Real-world Sequential Decision Making workshop at ICML*, 2019. [ bib ] (pdf) -
Tanner Fiez, Benjamin Chasnov, and Lillian J. Ratliff.
**Convergence of Learning Dynamics in Stackelberg Games**.*arxiv:1906.01217*, 2019. [ bib ] (arxiv) -
Benjamin Chasnov, Lillian J. Ratliff, Eric Mazumdar, and Samuel Burden.
**Convergence Guarantees for Gradient-Based Learning in Continuous Games**.*Uncertainty in Artificial Intelligence*, 2019. [ bib ] (link) - Shahriar Talebi, Siavash Alemzadeh, Lillian J. Ratliff, and Mehran Mesbahi.
**Distributed Learning in Network Games: A Dual Averaging Approach**. In*Proceedings of the IEEE Conference on Decision and Control*, 2019. [ bib ] (link) -
Sarah H.Q. Li, Daniel Calderone, Lillian J. Ratliff, and Behcet Acikmese.
**Sensitivity Analysis for MDP Congestion Games**. In*Proceedings of the IEEE Conference on Decision and Control*, 2019. [ bib ] -
Yagiz Savas, Vijay Gupta, Melkior Ornik, , Lillian J. Ratliff, and Ufuk Topcu.
**Incentive Design for Temporal Logic Objectives**. In*Proceedings of the IEEE Conference on Decision and Control*, 2019. [ bib ] -
Eric Mazumdar and Lillian J. Ratliff.
**Local Nash Equilibria are Isolated, Strict Local Nash Equilibria in 'Almost All' Zero-Sum Continuous Games**. In*Proceedings of the IEEE Conference on Decision and Control*, 2019. [ bib ] (arxiv) -
Daniel Calderone and Lillian J. Ratliff.
**Multi-Dimensional Continuous Type Population Potential Games**. In*Proceedings of the IEEE Conference on Decision and Control*, 2019. [ bib ] -
Chase Dowling, Lillian J. Ratliff, and Baosen Zhang.
**Modeling Curbside Parking as a Network of Finite Capacity Queues**. In*IEEE Transactions on Intelligent Transportation Systems (accepted for publication)*, 2019. [ bib ] -
Tyler Westenbroek, Roy Dong, Lillian J. Ratliff, and S. Shankar Sastry.
**Statistical Estimation with Strategic Data Sources in Competitive Settings**. In*IEEE Transactions on Automatic Control*, 2019. [ bib ] (pdf) -
Lillian J. Ratliff and Eric Mazumdar.
**Inverse Risk-Sensitive Reinforcement Learning**. In*IEEE Transactions on Automatic Control*, 2019. [ bib ] (pdf) -
Tanner Fiez and Lillian J. Ratliff.
**Data-Driven Spatio-Temporal Analysis of Curbside Parking Demand**.*accepted for publication in IEEE Transactions on Intelligent Transportation Systems*, 2019 (submitted 2017). [ bib ] -
Lillian J. Ratliff, Roy Dong, Shreyas Sekar, and Tanner Fiez.
**A Perspective on Incentive Design: Challenges and Opportunities**.*Annual Reviews of Controls, Robotics, and Autonomous Systems (to appear)*, 2018. [ bib ] (pdf) -
Esther Ling, Lillian J. Ratliff, and Samuel Coogan.
**Koopman Operator Approach for Instability Detection and Mitigation in Signalized Traffic**. In*IEEE ITSC*, 2018. [ bib ] -
Hui (Sarah) Li, Yue Yu, Daniel Calderone, Lillian J. Ratliff, and Behcet
Acikmese.
**Tolling for Constraint Satisfaction in Markov Decision Process Congestion Games**. 2018. [ bib ] -
Eric Mazumdar and Lillian J. Ratliff.
**On the Convergence of Competitive, Multi-Agent Gradient-Based Learning**.*arXiv:1804.05464*, 2018. [ bib ] -
Benjamin Chasnov, Lillian J. Ratliff, Daniel Calderone, Eric Mazumdar, and
Samuel Burden.
**Finite-Time Convergence of Gradient-Based Learning in Continuous Games**.*AAAI-19 Workshop on Reinforcement Learning in Games*, 2018. [ bib ] -
Tanner Fiez, Shreyas Sekar, Liyuan Zheng, and Lillian J. Ratliff.
**Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences**. In*Uncertainty in Artificial Intelligence*, 2018. [ bib ] (pdf) -
Lillian J. Ratliff and Tanner Fiez.
**Adaptive Incentive Design**.*IEEE TAC*, 2018. [ bib ] -
Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff, and Baosen Zhang.
**Uncertainty in Multi-Commodity Routing Networks: When does it help?**In*Proceedings of the American Control Conference*, 2018. [ bib ] -
Roy Dong, Alvaro A. Cárdenas, Lillian J. Ratliff, Henrik Ohlsson, and
Shankar Sastry.
**Quantifying the Utility-Privacy Tradeoff in the Smart Grid**.*ACM Transactions on Cyber-Physical Systems*, 2018. [ bib ] -
Tanner Fiez, Lillian J. Ratliff, Chase Dowling, and Baosen Zhang.
**Data-Driven Spatio-Temporal Modeling of Parking Demand**. In*Proceedings of the American Control Conference*, 2018. [ bib ] -
Ioannis Konstantakopoulos*, Lillian J. Ratliff*, Ming Jin, S. Shankar Sastry,
and Costas Spanos.
**A Robust Utility Learning Framework via Inverse Optimization**.*IEEE Transactions on Control Systems Technology*, PP(99):1--17, 2017. [ bib | DOI ] -
Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff, and Baosen Zhang.
**Uncertainty in Multi-Commodity Routing Networks: When does it help?***arxiv:1709.08441*, 2017. [ bib ] -
Lillian Ratliff, Shreyas Sekar, Liyuan Zheng, and Tanner Fiez.
**Multi-Armed Bandits for Correlated Markovian Environments with Smoothed Rewards.**2017. (arxiv), [ bib ] -
Kamil Nar, Lillian J. Ratliff, and S. Shankar Sastry.
**Learning Prospect Theory Value Function and Reference Point of a Sequential Decision Maker**. In*Proceedings of the 56th IEEE Conference on Decision and Control*, 2017. [ bib ] -
Eric Mazumdar, Lillian J. Ratliff, Tanner Fiez, and S. Shankar Sastry.
**Gradient--Based Inverse Risk-Sensitive Reinforcement Learning with Applications**. In*Proceedings of the 56th IEEE Conference on Decision and Control*, 2017. [ bib ] -
Chase Dowling, Tanner Fiez, Lillian J. Ratliff, and Baosen Zhang.
**Optimizing Curbside Parking Resources Subject to Congestion Constraints**. In*Proceedings of the 56th IEEE Conference on Decision and Control*, 2017. [ bib ] -
Tyler Westenbroek, Roy Dong, Lillian J. Ratliff, and S. Shankar Sastry.
**Statistical Estimation in Competitive Settings with Strategic Data Sources**. In*Proceedings of the 56th IEEE Conference on Decision and Control*, 2017. [ bib ] -
Chase Dowling, Tanner Fiez, Lillian J. Ratliff, and Baosen Zhang.
**How Much Urban Traffic is Searching for Parking?**In*arXiv:1702.06156*, 2017. [ bib ] -
Ioannis Konstantakopoulos*, Lillian J. Ratliff*, Ming Jin, and Costas Spanos.
**Leveraging Correlations in Utility Learning**. In*Proceedings of the American Control Conference*, 2017. [ bib ] -
L. J. Ratliff, C. Dowling, E. Mazumdar, and B. Zhang.
**To observe or not to observe: Queuing game framework for urban parking**. In*Proceedings of the IEEE 55th Conference on Decision and Control (CDC)*, pages 5286--5291, Dec 2016. [ bib | DOI ] -
D. Calderone, E. Mazumdar, L. J. Ratliff, and S. S. Sastry.
**Understanding the impact of parking on urban mobility via routing games on queue-flow networks**. In*Proceedings of the IEEE 55th Conference on Decision and Control*, pages 7605--7610, Dec 2016. [ bib | DOI ] -
Ioannis C. Konstantakopoulos, Lillian J. Ratliff, Ming Jin, Costas Spanos, and
S. Shankar Sastry.
**Smart building energy efficiency via social game: a robust utility learning framework for closing-the-loop**. In*Proceedings of the 1st International Workshop on Science of Smart City Operations and Platforms Engineering (SCOPE) in partnership with Global City Teams Challenge (GCTC) (SCOPE - GCTC)*, pages 1--6, April 2016. [ bib | DOI ] -
I. C. Konstantakopoulos, L. J. Ratliff, M. Jin, C. J. Spanos, and S. S. Sastry.
**Inverse modeling of non-cooperative agents via mixture of utilities**. In*Proceedings of the IEEE 55th Conference on Decision and Control*, pages 6327--6334, Dec 2016. [ bib | DOI ] -
Lillan J. Ratliff, Samuel A. Burden, and S. Shankar Sastry.
**On the Characterization of Local Nash Equilibria in Continuous Games**.*IEEE Transactions on Automatic Control*, 61(8):2301--2307, Aug. 2016. [ bib | DOI ] -
**Incentivizing Efficiency in Societal-Scale Cyber-Physical Systems**. Lillian J. Ratliff. PhD thesis, University of California, Berkeley, 2015. [ bib ] -
D. Scobee, L. Ratliff, R. Dong, H. Ohlsson, M. Verhaegen, and S. S. Sastry.
**Nuclear norm minimization for blind subspace identification (N2BSID)**. In*Proceedings of the 54th IEEE Conference on Decision and Control*, pages 2127--2132, Dec 2015. [ bib | DOI ] -
Ming Jin, Lillian J. Ratliff, Ioannis Konstantakopoulos, Costas Spanos, and
Shankar Sastry.
**REST: A Reliable Estimation of Stopping Time Algorithm for Social Game Experiments**. In*Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems*, ICCPS '15, pages 90--99, New York, NY, USA, 2015. ACM. [ bib | DOI | http ] -
D. J. Calderone, L. J. Ratliff, and S. S. Sastry.
**Lane pricing via decision-theoretic lane changing model of driver behavior**. In*Proceedings of the 54th IEEE Conference on Decision and Control*, pages 3457--3462, Dec 2015. [ bib | DOI ] -
Lillian J. Ratliff, Roy Dong, Henrik Ohlsson, and S. Shankar Sastry.
**Energy Efficiency via Incentive Design and Utility Learning**. In*Proceedings of the 3rd International Conference on High Confidence Networked Systems*, HiCoNS '14, pages 57--58, New York, NY, USA, 2014. ACM. [ bib | DOI ] -
Roy Dong, Lillian Ratliff, Henrik Ohlsson, and S. Shankar Sastry.
**Fundamental Limits of Nonintrusive Load Monitoring**. In*Proceedings of the 3rd International Conference on High Confidence Networked Systems*, HiCoNS '14, pages 11--18, New York, NY, USA, 2014. ACM. [ bib | DOI ] -
Henrik Ohlsson, Lillian Ratliff, Roy Dong, and S. Shankar Sastry.
**Blind Identification via Lifting**. In*Proceedings of the 19th World Congress of the International Federation of Automatic Control*, volume 47, pages 10367--10372, 2014. [ bib | DOI ] -
Daniel Calderone, Lillian J. Ratliff, and S. Shankar Sastry.
**Pricing for Coordination in Open--Loop Differential Games**.*IFAC Proceedings Volumes*, 47(3):9001 -- 9006, 2014. [ bib | DOI ] -
L. J. Ratliff, R. Dong, H. Ohlsson, A. A. Cárdenas, and S. S. Sastry.
**Privacy and customer segmentation in the smart grid**. In*Proceedings of the 53rd IEEE Conference on Decision and Control*, pages 2136--2141, Dec 2014. [ bib | DOI ] -
L. J. Ratliff, S. A. Burden, and S. S. Sastry.
**Genericity and structural stability of non-degenerate differential Nash equilibria**. In*Proceedings of the American Control Conference*, pages 3990--3995, June 2014. [ bib | DOI ] -
L. J. Ratliff, M. Jin, I. C. Konstantakopoulos, C. Spanos, and S. S. Sastry.
**Social game for building energy efficiency: Incentive design**. In*Proceedings of the 52nd Annual Allerton Conference on Communication, Control, and Computing*, pages 1011--1018, Sept 2014. [ bib | DOI ] -
Lillian J Ratliff, Roy Dong, Henrik Ohlsson, and S Shankar Sastry.
**Incentive Design and Utility Learning via Energy Disaggregation**. In*Proceedings of the 19th World Congress of the International Federation of Automatic Control*, volume 47, pages 3158--3163, 2014. [ bib | DOI ] -
Lillian Ratliff, Carlos Barreto, Roy Dong, Henrik Ohlsson, Alvaro A. Cardenas,
and S. Shankar Sastry.
**Effects of Risk on Privacy Contracts for Demand-Side Management**.*arxiv:1409.7926v3*, 2014. [ bib ] -
P. Kachroo, L. Ratliff, and S. Sastry.
**Analysis of the Godunov-Based Hybrid Model for Ramp Metering and Robust Feedback Control Design**.*IEEE Transactions on Intelligent Transportation Systems*, 15(5):2132--2142, Oct 2014. [ bib | DOI ] -
Aaron Bestick, Lillian J. Ratliff, Posu Yan, Ruzena Bajcsy, and S. Shankar
Sastry.
**An Inverse Correlated Equilibrium Framework for Utility Learning in Multiplayer, Noncooperative Settings**. In*Proceedings of the 2nd ACM International Conference on High Confidence Networked Systems*, HiCoNS '13, pages 9--16, New York, NY, USA, 2013. ACM. [ bib | DOI ] -
Henrik Ohlsson, Lillian Ratliff, Roy Dong, and S. Shankar Sastry.
**Blind Identification of ARX Models with Piecewise Constant Inputs**.*arxiv:1303.6719*, 2013. [ bib ] -
R. Dong, L. J. Ratliff, H. Ohlsson, and S. S. Sastry.
**Energy disaggregation via adaptive filtering**. In*Proceedings of the 51st Annual Allerton Conference on Communication, Control, and Computing*, pages 173--180, Oct 2013. [ bib | DOI ] -
L. J. Ratliff, S. A. Burden, and S. S. Sastry.
**Characterization and computation of local Nash equilibria in continuous games**. In*Proceedings of the 51st Annual Allerton Conference on Communication, Control, and Computing*, pages 917--924, Oct 2013. [ bib | DOI ] -
D. J. Calderone, L. J. Ratliff, and S. S. Sastry.
**Pricing design for robustness in linear quadratic games**. In*Proceedings of the 52nd IEEE Conference on Decision and Control*, pages 4349--4354, Dec 2013. [ bib | DOI ] -
L. J. Ratliff, R. Dong, H. Ohlsson, A. A. Cárdenas, and S. S. Sastry.
**Privacy and customer segmentation in the smart grid**. In*Proceedings of the 53rd IEEE Conference on Decision and Control*, pages 2136--2141, Dec 2014. [ bib | DOI ] -
S. Coogan, L. J. Ratliff, D. Calderone, C. Tomlin, and S. S. Sastry.
**Energy management via pricing in LQ dynamic games**. In*Proceedings of the American Control Conference*, pages 443--448, June 2013. [ bib | DOI ] -
R. Dong, L. Ratliff, H. Ohlsson, and S. S. Sastry.
**A dynamical systems approach to energy disaggregation**. In*Proceedings of the 52nd IEEE Conference on Decision and Control*, pages 6335--6340, Dec 2013. [ bib | DOI ] -
L. J. Ratliff, S. Coogan, D. Calderone, and S. S. Sastry.
**Pricing in linear-quadratic dynamic games**. In*Proceedings of the 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton)*, pages 1798--1805, Oct 2012. [ bib | DOI ] -
Lillian J. Ratliff and Pushkin Kachroo.
**Validating numerically consistent macroscopic traffic models using microscopic data**.*Transportation Research Board Annual Meeting*, 2010. [ bib ] - 2020 ONR Young Investigator Award
- 2019 National Academy of Engineering, Invited Speaker for the China-America Frontiers of Engineering Symposium
- 2019 National Science Foundation CAREER Award
- 2017 National Science Foundation CISE Research Initiation Initiative Award
- 2009 National Science Foundation Graduate Research Fellowship

**2022**

**2021**

**2020**

**2019**

**2018**

**2017**

**2016**

**2015**

**2014**

**2013**

**2012**

**2010**

**Funding**

This work is funded by the National Science
Foundation (current: CNS-1736582, CNS-1836819, CNS-1931718, CNS-1907907,
CNS-1844729, CNS-1952011; previous: CNS-1634136,
CNS-1646912, CNS-1656873) and the Office of Naval Research (current: ONR YIP)

**Awards & Recognition**