Journals

[J15] Srivatsan Krishnan, Max Lam, Sharad Chitlangia, Zishen Wan, Gabriel Barth-Maron, Aleksandra Faust, Vijay Janapa Reddi, “QuaRL: Quantization for Fast and Environmentally Sustainable Reinforcement Learning,” Transactions of Machine Learning Research (TMLR), 2022.Press: Blog, MarketTechPost.

[J14] Jack Parker-Holder, Raghu Rajan, Xingyou Song, André Biedenkapp, Yingjie Miao, Theresa Eimer, Baohe Zhang, Vu Nguyen, Roberto Calandra, Aleksandra Faust,* Frank Hutter*, Marius Lindauer*, "Automated Reinforcement Learning (AutoRL): A Survey and Open Problems," Journal of Artificial Intelligence Research (JAIR) 2022.

[J13] Behzad Boroujerdian, Hasan Genc, Srivatsan Krishnan, Bardienus Pieter Duisterhof, Brian Plancher, Kayvan Mansoorshahi, Marcelino Almeida,  Aleksandra Faust, Vijay Janapa Reddi, "The Role of Compute in Autonomous Micro Aerial Vehicles: Optimizing for Flight Time and Energy Efficiency," ACM Transactions on Computer Systems (TOCS), 2022

[J12] Srivatsan Krishnan, Behzad Borojerdian, William Fu, Aleksandra Faust, Vijay Janapa Reddi, Air Learning: An AI Research Platform for Algorithm-Hardware Benchmarking of Autonomous Aerial Robots,” Mach Learn., 110, 2501–2540, 2021. Press: Techxplore

[J11] Somil Bansal, Varun Tolani, Aleksandra Faust, Claire Tomlin, Visual Navigation Among Humans with Optimal Control as a Supervisor, IEEE Robotics and Automation Letters (RA-L), 2021. Press: VentureBeat, Techxplore

[J10] Hao-Tien Lewis Chiang, John E. G. Baxter, Satomi Sugaya, Mohammad R. Yousefi, Aleksandra Faust, Lydia Tapia, “Fast Deep Swept Volume Estimator”, Invited to The Workshop on the Algorithmic Foundations of Robotics (WAFR) Special Issue of The International Journal of Robotics Research (IJRR), Vol 40, Issue 10-11, 2021.

[J9] Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj, Paul Whatmough, Aleksandra Faust, Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi, The Sky Is Not the Limit: A Visual Performance Model for Cyber-Physical Co-Design in Autonomous Machines,” IEEE Computer Architecture Letters (CAL), vol. 19, no. 1, pp. 38-42, 1 Jan.-June 2020. (Best of IEEE Computer Architecture Letters)

[J8] Anthony Francis, Aleksandra Faust, Hao-Tien Lewis Chiang, Jasmine Hsu, J. Chase Kew, Marek Fiser, Tsang-Wei Edward Lee, “Long-Range Indoor Navigation with PRM-RL,” IEEE Transactions on Robotics (T-RO), 2020. Video. 4400+ downloads.

[J7] Hao-Tien Lewis Chiang, Jasmine Hsu, Marek Fiser, Lydia Tapia, Aleksandra Faust, “RL-RRT: End-to-End Kinodynamic Robot Motion Planning,” IEEE Robotics and Automation Letters (RA-L), 2019. 5000+ downloads.

[J6] Hao-Tien Chiang*, Aleksandra Faust,* Marek Fiser, Antony Francis, “Learning Navigation Behaviors End to End with AutoRL,” IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 2007-2014, April 2019. 9900+ full text downloads Press: Blog, VentureBeat, Packtpub, Medium, IEEE Spectrum, Jeff Dean's keynote

[J5] Timothy J. Draelos, Matthew G. Peterson, Hunter A. Knox, Benjamin J. Lawry, Kristin E. Phillips‐Alonge, Abra E. Ziegler, Eric P. Chael, Christopher J Young, Aleksandra Faust, “Dynamic Tuning of Seismic Signal Detector Trigger Levels for Local Networks,” Bulletin of the Seismological Society of America vol. 108 no. 2, pp. 1346-1354, 2018.

[J4] Conrad D. James, James B. Aimone, Nadine E. Miner, Craig M. Vineyard, Fredrick H. Rothganger, Kristofor D. Carlson, Samuel A. Mulde, Timothy J. Draelos, Aleksandra Faust, Matthew J. Marinell, John H. Naegle, Steven J. Plimpton, "A Historical Survey of Algorithms and Hardware Architectures for Neural-inspired and Neuromorphic Computing Applications," Biologically Inspired Cognitive Architectures, vol. 19, pp 49-64, January 2017.

[J3] Aleksandra Faust, Ivana Palunko, Patricio Cruz, Rafael Fierro, Lydia Tapia, “Automated Aerial Suspended Cargo Delivery through Reinforcement Learning,” Artificial Intelligence, vol. 247, pp. 381-398,  2017.

[J2] Aleksandra Faust, Peter Ruymgaart, Molly Salman, Rafael Fierro, Lydia Tapia, "Continuous Action Reinforcement Learning for Control-Affine Systems with Unknown Dynamics," Acta Automatica Sinica Special Issue on Extensions of Reinforcement Learning and Adaptive Control, IEEE/CAA Journal of, vol. 1, No.3, pp. 323-336, 2014.

[J1] Nick Malone, Aleksandra Faust, Brandon Rohrer, Ron Lumia, John Wood, Lydia Tapia, “Efficient Motion-based Task Learning for a Serial Link Manipulator,” Transactions on Control and Mechanical Systems Journal, vol. 3, no. 1, 2014.

Conferences

[C41] Meredith Ringel Morris, Jascha Sohl-dickstein, Noah Fiedel, Tris Warkentin, Allan Dafoe, Aleksandra Faust, Clement Farabet, Shane Legg, “Levels of AGI: Operationalizing Progress on the Path to AGI,” Positional paper, International Conference on Machine Learning (ICML) 2024. Press: Forbes, MIT Technology Review, VentureBeat

[C40] Jesse Farebrother, Jordi Orbay, Quan Vuong, Adrien Ali Taiga, Yevgen Chebotar, Ted Xiao, Alex Irpan, Aleksandra Faust, Pablo Samuel Castro, Sergey Levine, Aviral Kumar, Rishabh Agarwal, “Stop Regressing: The Unreasonable Effectiveness of Classification in Deep Reinforcement Learning,” International Conference on Machine Learning (ICML) 2024. 

[C39] Izzeddin Gur, Hiroki Furuta, Austin Huang, Mustafa Safdari, Yutaka Matsuo, Douglas Eck, Aleksandra Faust, “A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis,” International Conference of Learning Representations (ICLR), May 2024. (Oral – 1.17% acceptance rate) Press: MarkTechPost, Synced, Toward AI

[C38] Hiroki Furuta, Kuang-Huei Lee, Ofir Nachum, Yutaka Matsuo, Aleksandra Faust, Shixiang Shane Gu, Izzeddin Gur, “Multimodal Web Navigation with Instruction-Finetuned Foundation Models,” International Conference of Learning Representations (ICLR), May 2024.

[C37] Izzeddin Gur, Ofir Nachum, Yingjie Miao, Mustafa Safdari, Austin Huang, Sharan Narang, Aakanksha Chowdhery, Noah Fiedel, Aleksandra Faust, Understanding HTML with Large Language Models,” Findings of Conference on Empirical Methods in Natural Language Processing (EMNLP) 2023

[C36] Cole Gulino, Justin Fu, Wenjie Luo, George Tucker, Eli Bronstein, Yiren Lu, Jean Harb, Xinlei Pan, Yan Wang, Xiangyu Chen, John D Co-Reyes, Rishabh Agarwal, Rebecca Roelofs, Yao Lu, Nico Montali, Paul Mougin, Zoey Zeyu Yang, Brandyn White, Aleksandra Faust, Rowan Thomas McAllister, Dragomir Anguelov, Benjamin Sapp Hide, “WayMax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research,” Conference on Neural Information Processing Systems (NeurIPS) 2023. Press: TechCrunch, TechTimes

[C35] Yujin Tang, Wenhao Yu, Jie Tan, Heiga Zen, Aleksandra Faust, Tatsuya Harada, “SayTap: Language to Quadrupedal Locomotion,” Conference on Robot Learning (CoRL), 2023. Press: Blog, Gizmodo, InterestingEngineering 

[C34] Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Becca Roelofs, Ben Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, Drago Anguelov, Sergey Levine, “Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023. Blog

[C33] Yazied Hasan, Ariana Villegas Suarez, Evan C. Carter, Aleksandra Faust, Lydia Tapia “Enhancing Value Estimation Policies by Post-Hoc Symmetry Exploitation in Motion Planning Tasks,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023.

[C32] Anish Muthali, Haotian Shen, Sampada Deglurkar, Michael H. Lim, Rebecca Roelofs, Aleksandra Faust, Claire J. Tomlin, “Multi-Agent Reachability Calibration with Conformal Prediction,” IEEE Conference on Decision and Control (CDC), 2023.

[C31] Abdus Salam Azad, Izzeddin Gur, Jasper Emhoff, Nathaniel Alexis, Aleksandra Faust, Pieter Abbeel, Ion Stoica, CLUTR: Curriculum Learning via Unsupervised Task Representation Learning,” International Conference on Machine Learning (ICML), 2023.

[C30] Srivatsan Krishnan, Amir Yazdanbaksh, Shvetank Prakash, Jason Jabbour, Ikechukwu Uchendu, Susobhan Ghosh, Behzad Boroujerdian, Daniel Richins, Devashree Tripathy, Aleksandra Faust, Vijay Janapa Reddi, "ArchGym: An Open-Source Gymnasium for Machine Learning Assisted Architecture Design," International Symposium on Computer Architecture (ISCA) 2023. Press: Blog

[C29] Sampada Deglurkar, Michael H. Lim, Johnathan Tucker, Zachary N. Sunberg, Aleksandra Faust, Claire J. Tomlin, "Compositional Learning-based Planning for Vision POMDPs," Learning for Dynamics & Control Conference (L4DC) 2023

[C28] Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj, Paul Whatmough, Aleksandra Faust, Sabrina M. Neuman Gu-Yeon Wei, David Brooks, Vijay Janapa Reddi, Automatic Domain-Specific SoC Design for Autonomous Unmanned Aerial Vehicles,” IEEE/ACM International Symposium on Microarchitecture (MICRO) 2022, IEEE Micro Top Picks 2023 Honorable Mention.

[C27] Yingjie Miao, Xingyou Song, John D Co-Reyes, Daiyi Peng, Summer Yue, Eugene Brevdo, Aleksandra Faust, "Differentiable Architecture Search for Reinforcement Learning," The International Conference on Automated Machine Learning (AutoML), 2022. (19% acceptance rate).

[C26] Sungryull Sohn, Hyunjae Woo, Jongwook Choi, lyubing Qiang, Izzeddin Gur, Aleksandra Faust, Honglak Lee, "Fast Inference and Transfer of Compositional Task Structures for Few-shot Task Generalization," Oral @ Uncertainty in Artificial Intelligence (UAI) 2022. (5% acceptance rate)

[C25] Sabrina M. Neuman, Brian Plancher, Bart Duisterhof, Srivatsan Krishnan, Colby Banbury, Mark Mazumder, Shvetank Prakash, Jason Jabbour, Aleksandra Faust, Guido de Croon, Vijay Janapa Reddi, "Tiny Robot Learning: Challenges and Directions for Machine Learning in Resource-Constrained Robots," IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS) special session on Low Power Autonomous Systems 2022.

[C24] Srivatsan Krishnan , Zishen Wan, Kshitij Bhardwaj, Ninad Jadhav,. Aleksandra Faust, Vijay Janapa Reddi, "Roofline Model for UAVs: A Visual Performance Model for Guiding Compute System Design in Autonomous Drones," IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2022

[C23] Su Wang, Ceslee Montgomery, Jordi Orbay, Vighnesh Birodkar, Aleksandra Faust, Izzeddin Gur, Natasha Jaques, Austin Waters, Jason Baldridge, Peter Anderson, "Less is More: Generating Grounded Navigation Instructions from Landmarks," IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) 2022

[C22] Michael Lim, Andy Zeng, Brian Ichter, Maryam Bandari, Erwin Coumans, Claire Tomlin, Stefan Schaal, Aleksandra Faust, "Multi-Task Learning with Sequence-Conditioned Transporter Networks," International Conference on Robotics and Automation (ICRA), 2022.

[C21] Marco Carmona, Dejan Milutinovic, Aleksandra Faust, "Metrics-only Training Neural Network for Switching among an Array of Feedback Controllers for Bicycle Model Navigation," American Controls Conference (ACC), 2022.

[C20] Izzeddin Gur, Natasha Jaques, Yingjie Miao, Jongwook Choi, Manoj Tiwari, Honglak Lee, Aleksandra Faust, Environment Generation for Zero-Shot Compositional Reinforcement Learning,” Conference on Neural Information Processing Systems (NeurIPS) 2021.

[C19] Bardienus P. Duisterhof, Srivatsan Krishnan, Jonathan J. Cruz, Colby R. Banbury, William Fu, Aleksandra Faust, Guido C. H. E. de Croon, Vijay Janapa Reddi, "Tiny Robot Learning (tinyRL) for Source Seeking on a Nano Quadcopter," IEEE International Conference on Robotics and Automation (ICRA), Xi'an, China, 2021, pp. 7242-7248.

[C19] Felipe Felix Arias,, Brian Ichter, Aleksandra Faust, Nancy M. Amato, “Avoidance Critical Probabilistic Roadmaps for Motion Planning in Dynamic Environments," IEEE International Conference on Robotics and Automation (ICRA), Xi'an, China, 2021, pp. 10264-10270.

[C18] John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Sergey Levine, Quoc Le, Honglak Lee, Aleksandra Faust, “Evolving Reinforcement Learning Algorithms,” Oral @ International Conference of Learning Representations (ICLR) 2021 (<2% acceptance rate) Press: Google AI Year in Review, Analytics India Magazine

[C17] Rose E. Wang, J. Chase Kew, Dennis Lee, Brian Ichter, Tsang-Wei Edward, Lee, Tingnan Zhang, Jie Tan, Aleksandra Faust, “Model-based Reinforcement Learning for Multiagent Goal Alignment,“ Conference on Robot Learning (CoRL) 2020. Website, Video. (34% acceptance rate). Press: Google AI Year in Review

[C16] Yinlam Chow, Ofir Nachum, Aleksandra Faust, Mohammad Ghavamzadeh, Edgar Duenez-Guzman, Safe Policy Learning for Continuous Control,Conference on Robot Learning (CoRL) 2020. (34% acceptance rate). Press: Google AI Year in Review,

[C15] J. Chase Kew, Brian Ichter, Maryam Bandari, Tsang-Wei Edward Lee, Aleksandra Faust, Neural Collision Clearance Estimator for Batched Motion Planning,” The Workshop on the Algorithmic Foundations of Robotics (WAFR) 2020. Video

[C14] Xinlei Pan, Tingnan Zhang, Brian Ichter, Aleksandra Faust, Jie Tan, Sehoon Ha, “Zero-shot Imitation Learning from Demonstrations for Legged Robot Visual Navigation,” International Conference on Robotics and Automation (ICRA), Paris, France, 2020, pp. 679-685. Website

[C13] Brian Ichter, Edward Schmerling, Tsang-Wei Edward Lee, Aleksandra Faust, Learned Critical Probabilistic Roadmaps for Robotic Motion Planning,” EEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020, pp. 9535-9541. Video

[C12] Arpit Garg, Hao-Tien Lewis Chiang, Satomi Sugaya, Aleksandra Faust, Lydia Tapia, “Comparison of Deep Reinforcement Learning Policies to Formal Methods for Moving Obstacle Avoidance,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2019.

[C11] Izzedin Gur, Ulrich Rueckert, Aleksandra Faust, Dilek Hakkani-Tur, “Learning to Navigate the Web,” International Conference of Learning Representations (ICLR), May 2019. (in top 10% of accepted papers, 31% acceptance rate). Press: ZDNet, Tech Register, Medium

[C10] Hao-Tien Chiang, Aleksandra Faust, Lydia Tapia, Fast Swept Volume Estimation with Deep Learning,The 13th International Workshop on the Algorithmic Foundations of Robotics (WAFR), 2018.

[C9] Behzad Boroujerdian, Hasan Genc, Srivatsan Krishnan, Wenzhi Cui, Aleksandra Faust, Vijay Janapa Reddi, “MAVBench: Micro Aerial Vehicle Benchmarking,” 51st IEEE/ACM International Symposium on Microarchitecture (MICRO) pp. 894-907, 2018. (21% acceptance rate).

[C8] Aleksandra Faust, James B. Aimone, Conrad D. James, Lydia Tapia, “Resilient Computing with Reinforcement Learning on a Dynamical System: Case Study in Sorting,57th IEEE Conference on Decision and Control (CDC), pp. 5999-6006, 2018. Press: ZDNet, Medium 

[C7] Aleksandra Faust, Oscar Ramirez, Marek Fiser, Ken Oslund, Anthony Francis, James Davidson, Lydia Tapia, “PRM-RL: Long-range Robotic Navigation Tasks by Combining Reinforcement Learning and Sampling-based Planning,IEEE International Conference on Robotics and Automation (ICRA), pp. 5113-5120, Brisbane, Australia, 2018. Best paper in Service robotics. Press: Google AI Blog, VentureBeat, Packtpub, Medium

[C6] Aleksandra Faust, Hao-Tien Chiang, Nathanael Rackley, Lydia Tapia, “Avoiding Moving Obstacles with Stochastic Hybrid Dynamics Using PEARL: PrEference Appraisal Reinforcement Learning,” IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016, pp. 484-490.

[C5] Aleksandra Faust, Nick Malone, Lydia Tapia, “Preference-balancing Motion Planning under Stochastic Disturbances,IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, 2015, pp. 3555-3562.

[C4] Rafael Figueroa, Aleksandra Faust, Patricio Cruz, Lydia Tapia, Rafael Fierro, "Reinforcement Learning for Balancing a Flying Inverted Pendulum," The 11th World Congress on Intelligent Control and Automation (WCICA), Shenyang, China, 2014.

[C3] Aleksandra Faust, Ivana Palunko, Patricio Cruz, Rafael Fierro, Lydia Tapia, “Learning Swing-free Trajectories for UAVs with a Suspended Load,IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, May 2013, pp. 4887–4894.

[C2] Ivana Palunko, Aleksandra Faust, Patricio Cruz, Lydia Tapia, Rafael Fierro, "A Reinforcement Learning Approach to Suspended Load Manipulation with Aerial Robots," IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 2013, pp 4881–4886.

[C1] Peter B. Merkle, Antonio Gonzales, Aleksandra Faust, Kurt W. Larson, Jack C. Bartberger, Karl E. Horak, Manuel M. Trujillo, Nathan Reynolds Schanfein, Keith M. Tolk, Nairong Nancy Wang, “Reflective Particle Tag for Arms Control and Safeguards Authentication,” Institute of Nuclear Materials Management Annual Conference, Tucson, AZ, July 2009.

Refereed workshops 

[W27] Jordi Orbay, Yingjie Miao, Rishabh Agarwal, Aviral Kumar, George Tucker, Aleksandra Faust, “Scaling Offline Q-Learning with Vision Transformers,”Foundation Models for Decision Making Workshop at NeurIPS 2023.

[W26] Izzeddin Gur, Ofir Nachum, Yingjie Miao, Mustafa Safdari, Austin Huang, Sharan Narang, Aakanksha Chowdhery, Noah Fiedel, Aleksandra Faust, Understanding HTML with Large Language Models,” Mathematical and Empirical Understanding of Foundation Models (ME-FoMo),  International Conference of Learning Representations (ICLR) 2023.

[W25] Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Becca Roelofs, Ben Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, Drago Anguelov, Sergey Levine, Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios.Machine Learning for Autonomous Driving (ML4AD), Conference on Neural Information Processing Systems (NeurIPS) 2022.

[W24] Srivatsan Krishnan, Natasha Jaques, Shayegan Omidshafiei, Dan Zhang, Izzeddin Gur, Vijay Janapa Reddi, Aleksandra Faust, “Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration,” Machine Learning Systems, Conference on Neural Information Processing Systems (NeurIPS) 2022. Oral.

[W23] Juan Jose Garau-Luis, Yingjie Miao, John D. Co-Reyes, Aaron Parisi, Jie Tan, Esteban Real, Aleksandra Faust, "Multi-Objective Evolution for Generalizable Policy Gradient Algorithms," Generalizable Policy Learning in the Physical World Workshop, International Conference of Learning Representations (ICLR) 2022.

[W22] Izzeddin Gur, Ofir Nachum, Aleksandra Faust, "Targeted Environment Design from Offline Data," Deep RL, Conference on Neural Information Processing Systems (NeurIPS), 2021

[W21] Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Izzeddin Gur, Aleksandra Faust, Honglak Lee, “Fast Inference and Transfer of Compositional Task Structure for Few-shot Task Generalization,” Deep RL @ Conference on Neural Information Processing Systems (NeurIPS), 2021.

[W20] Alberto Camacho, Izzeddin Gur, Marcin Lukasz Moczulski, Ofir Nachum, Aleksandra Faust, SparseDice: Imitation Learning for Temporally Sparse Data via Regularization”, Workshop on Unsupervised RL @ International Conference on Machine Learning (ICML), 2021

[W19] Dennis Lee, Natasha Jaques, J. Chase Kew, Douglas Eck, Dale Schuurmans, Aleksandra Faust, Joint Attention for Multi-Agent Coordination and Social Learning,” Social Intelligence in Humans and Robots, IEEE International Conference on Robotics and Automation (ICRA), 2021

[W18] Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Izzeddin Gur, Aleksandra Faust, Honglak Lee, “Fast Inference and Transfer of Compositional Task Structure for Few-shot Task Generalization, Never-ending Reinforcement Learning, International Conference of Learning Representations (ICLR), 2021

[W17] Maximilian Lam, Sharad Chitlangia, Srivatsan Krishnan, Zishen Wan, Gabe Barth-Maron, Aleksandra Faust, Vijay Japana Reddi, ActorQ: Quantization for Actor-Learner Distributed Reinforcement Learning,” Hardware Aware Efficient Training @ International Conference of Learning Representations (ICLR), 2021

[W16] John D. Co-Reyes, Yingjie Miao, Daiyi Peng, Esteban Real, Sergey Levine, Quoc Le, Honglak Lee, Aleksandra Faust, “Evolving Reinforcement Learning Algorithms,” DeepRL, Conference on Neural Information Processing Systems (NeurIPS) 2020.

[W15] Izzeddin Gur, Natasha Jaques, Kevin Malta, Manoj Tiwari, Honglak Lee, Aleksandra Faust, “Adversarial Environment Generation for Learning to Navigate the Web,” DeepRL, Conference on Neural Information Processing Systems (NeurIPS) 2020.

[W14] Somil Bansal, Varun Tolani, Aleksandra Faust, Claire Tomlin, “Visual Navigation Among Humans with OptimalControl as a Supervisor,Machine Learning in Planning and Control of Robot Motion Workshop (MLPC), IEEE International Conference on Robotics and Automation (ICRA), 2020. Press: VentureBeat, Techxplore 

[W13] Srivatsan Krishnan, Sharad Chitlangia, Maximilian Lam, Zishen Wan, Aleksandra Faust, Vijay Janapa Reddi, Quantized Reinforcement Learning (QuaRL),” 1st Workshop on Resource-Constrained Machine Learning, Machine Learning Systems, 2020. Press: Medium 

[W12] Srivatsan Krishnan, Colby Banbury, Bardienus Duisterhof, Aleksandra Faust, Vijay Janapa Reddi, “Air Learning: An End-to-end Learning Gym For Aerial Robots,” MLSyS Demo Track, 2020. (36% acceptance rate)

[W11] Yinlam Chow, Ofir Nachum, Aleksandra Faust, Mohammad Ghavamzadeh, Edgar Duenez-Guzman, “Lyapunov-based Safe Policy Optimization for Continuous Control,” Reinforcement Learning four Real World (RL4RL) at International Conference on Machine Learning (ICML), 2019. Best Paper Award.

[W10] Aleksandra Faust, Anthony Francis, Dar Mehta, Evolving Rewards to Automate Reinforcement Learning,AutoML Workshop, International Conference on Machine Learning (ICML), 2019. 58% acceptance rate. Press: Jeff Dean's keynote

[W9] Brian Ichter, Aleksandra Faust, “Learned Critical Probabilistic Roadmaps for Robotic Motion Planning,” Topological Methods in Robot Planning, IEEE International Conference on Robotics and Automation (ICRA), 2019.

[W8] Srivatsan Krishnan, Behzad Boroujerdian, Aleksandra Faust, Vijay Janapa Reddi, “Toward Exploring End-to-End Learning Algorithms for Autonomous Aerial Machines,” Algorithms and Architectures for Learning in-the-Loop Systems in Autonomous Flight, IEEE International Conference on Robotics and Automation (ICRA), 2019.

[W7] Behzad Boroujerdian, Hasan Genc, Srivatsan Krishnan, Aleksandra Faust, Vijay Janapa Reddi, “Why Compute Matters for UAV Energy Efficiency?,” International Symposium on Aerial Robotics, June 2018.

[W6] Pararth Shah, Marek Fiser, Aleksandra Faust, J. Chase Kew, Dilek Hakkani-Tur, “FollowNet: Robot Navigation by Following Natural Language Directions with Deep Reinforcement Learning,” Third Machine Learning in Planning and Control of Robot Motion Workshop at IEEE International Conference on Robotics and Automation (ICRA), 2018.

[W6] Hao-Tien Chiang, Aleksandra Faust, Lydia Tapia, “A Deep Neural Network for Swept Volume Prediction Between Configurations,” Third Machine Learning in Planning and Control of Robot Motion Workshop at IEEE International Conference on Robotics and Automation (ICRA), 2018.

[W5] Timothy Draelos, Matthew Peterson, Benjamin Lawry, Hunter Knox, Aleksandra Faust, Eric Chael, and Christopher Young, “Adaptive Self-Tuning Networks,” American Geophysical Union, San Francisco, 2015.

[W4] Aleksandra Faust, Hao-Tien Chiang, Nathanael Rackley and Lydia Tapia, "Dynamic Obstacle Avoidance with PEARL: PrEference Appraisal Reinforcement Learning," Second Annual Machine Learning in Planning and Control of Robot Motion at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015.

[W3] Aleksandra Faust, Nick Malone, Lydia Tapia, "Planning Preference-balancing Motions with Stochastic Disturbances," Machine Learning in Planning and Control of Robot Motion at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Chicago, IL, 2014.

[W2] Aleksandra Faust, Ivana Palunko, Patricio Cruz, Rafael Fierro, Lydia Tapia, "Learning Swing-free Trajectories for UAVs with a Suspended Load in Obstacle-free Environments," Autonomous Learning at IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 2013.

[W1] Nick Malone, Aleksandra Faust, Brandon Rohrer, John Wood, Lydia Tapia, "Efficient Motion-based Task Learning," Robot Motion Planning at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2012.

Technical Reports

[T6] Rishabh Agarwal, Avi Singh, Lei M. Zhang, Bernd Bohnet, Stephanie Chan, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal Behbahani, Aleksandra Faust, Hugo Larochelle, “Many-Shot In-Context Learning,” CoRR 2024. Press: VentureBeat

[T5] Hiroki Furuta, Yutaka Matsuo, Aleksandra Faust, Izzeddin Gur, “Exposing Limitations of Language Model Agents in Sequential-Task Compositions on the Web,” CoRR 2024.

[T4] Gregory Serapio-García, Mustafa Safdari, Clément Crepy, Luning Sun, Stephen Fitz, Marwa Abdulhai, Aleksandra Faust, Maja Matarić, Personality Traits in Large Language Models,” CoRR 2023. Press: Discover Magazine, Techxplore, MarkTechPost, Synced. 

[T3] Bardienus P. Duisterhof, Srivatsan Krishnan, Jonathan J. Cruz, Colby R. Banbury, William Fu, Aleksandra Faust, Guido C. H. E. de Croon, Vijay Janapa Reddi, “Deep Reinforcement Learning for Autonomous Source Seeking on a Nano Drone,” CoRR 2019. (Video, GitHub) Press: BitCraze blog 

[T2] Aleksandra Faust, Hao-Tien Chiang, Lydia Tapia, “PEARL: PrEference Appraisal Reinforcement Learning for Motion Planning,” CoRR 2018. 

[T1] Lazar Supic, Rawan Naous, Ranko Sredojevic, Aleksandra Faust, Vladimir Stojanovic, “MPDCompress - Matrix Permutation Decomposition Algorithm for Deep Neural Network Compression,” CoRR 2018.