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ORCIDLu Feng 0001
Person information
- affiliation: University of Virginia, School of Engineering and Applied Science, Charlottesville, VA, USA
- affiliation (PhD 2014): University of Oxford, UK
Other persons with the same name
- Lu Feng — disambiguation page
- Lu Feng 0002 — NEC Laboratories China, Beijing, China
- Lu Feng 0003 — Beihang University, Department of Computer Science, Beijing, China
- Lu Feng 0004 — Saint Louis University, Department of Mathematics and Computer Science, MO, USA
- Lu Feng 0005 — Nanjing University of Information Science and Technology, School of Computer and Software, China
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2020 – today
- 2025
[c46]Shuyang Dong, Meiyi Ma, Josephine Lamp, Sebastian G. Elbaum, Matthew B. Dwyer, Lu Feng:
Quantitative Predictive Monitoring and Control for Safe Human-Machine Interaction. AAAI 2025: 26203-26210- [c45]Sarit Kraus, Kayla Boggess, Robert Kim, Bryan H. Choi, Lu Feng:
Towards Computational Foreseeability. AAAI 2025: 28586-28593 - [i32]Shenghui Chen, Yunhao Yang, Kayla Boggess, Seongkook Heo, Lu Feng, Ufuk Topcu:
Evaluating Human Trust in LLM-Based Planners: A Preliminary Study. CoRR abs/2502.20284 (2025) - 2024
- [j10]Shili Sheng
, Pian Yu, David Parker, Marta Kwiatkowska, Lu Feng:
Safe POMDP Online Planning Among Dynamic Agents via Adaptive Conformal Prediction. IEEE Robotics Autom. Lett. 9(11): 9946-9953 (2024) - [j9]Lu Feng, Abhishek Dubey:
Introduction to the Special Issue on ICCPS 2023. ACM Trans. Cyber Phys. Syst. 8(4): 44:1-44:2 (2024) - [c44]Shili Sheng, David Parker, Lu Feng:
Safe POMDP Online Planning via Shielding. ICRA 2024: 126-132 - [c43]Pian Yu, Shuyang Dong, Shili Sheng, Lu Feng, Marta Kwiatkowska:
Trust-Aware Motion Planning for Human-Robot Collaboration under Distribution Temporal Logic Specifications. ICRA 2024: 12949-12955 - [c42]Sören Schleibaum, Lu Feng, Sarit Kraus, Jörg P. Müller:
ADESSE: Advice Explanations in Complex Repeated Decision-Making Environments. IJCAI 2024: 7904-7912 - [c41]Ingy Elsayed-Aly, David Parker, Lu Feng:
Distributional Probabilistic Model Checking. NFM 2024: 57-75 - [i31]Shili Sheng, Pian Yu, David Parker, Marta Kwiatkowska, Lu Feng:
Safe POMDP Online Planning among Dynamic Agents via Adaptive Conformal Prediction. CoRR abs/2404.15557 (2024) - [i30]Josephine Lamp, Lu Feng, David Evans:
DP-RuL: Differentially-Private Rule Learning for Clinical Decision Support Systems. CoRR abs/2405.09721 (2024) - [i29]Sören Schleibaum, Lu Feng, Sarit Kraus, Jörg P. Müller:
ADESSE: Advice Explanations in Complex Repeated Decision-Making Environments. CoRR abs/2405.20705 (2024) - [i28]Minjae Kwon, Ingy Elsayed-Aly, Lu Feng:
Adaptive Reward Design for Reinforcement Learning in Complex Robotic Tasks. CoRR abs/2412.10917 (2024) - [i27]Shuyang Dong, Meiyi Ma, Josephine Lamp, Sebastian G. Elbaum, Matthew B. Dwyer, Lu Feng:
Quantitative Predictive Monitoring and Control for Safe Human-Machine Interaction. CoRR abs/2412.13365 (2024) - 2023
- [j8]Lu Feng, Dana Fisman:
Introduction to the Special Issue on Runtime Verification. Int. J. Softw. Tools Technol. Transf. 25(4): 519-520 (2023) - [c40]Maryam Bagheri, Josephine Lamp, Xugui Zhou, Lu Feng, Homa Alemzadeh:
Towards Developing Safety Assurance Cases for Learning-Enabled Medical Cyber-Physical Systems. SafeAI@AAAI 2023 - [c39]Christopher Morse, Lu Feng, Matthew B. Dwyer, Sebastian G. Elbaum:
A Framework for the Unsupervised Inference of Relations Between Sensed Object Spatial Distributions and Robot Behaviors. ICRA 2023: 901-908 - [c38]Kayla Boggess, Sarit Kraus, Lu Feng:
Explainable Multi-Agent Reinforcement Learning for Temporal Queries. IJCAI 2023: 55-63 - [c37]Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David E. Evans:
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces. NeurIPS 2023 - [c36]Negin Moghadasi, Amar Kulkarni, Dustin Crayton, Robert J. Grissom, James H. Lambert, Lu Feng:
Formal Methods in Unmanned Aerial Vehicle Swarm Control for Wildfire Detection and Monitoring. SysCon 2023: 1-8 - [e2]Sayan Mitra, Nalini Venkatasubramanian, Abhishek Dubey, Lu Feng, Mahsa Ghasemi, Jonathan Sprinkle:
Proceedings of the ACM/IEEE 14th International Conference on Cyber-Physical Systems, ICCPS 2023, (with CPS-IoT Week 2023), San Antonio, TX, USA, May 9-12, 2023. ACM 2023 [contents] - [d2]Ingy Elsayed-Aly, David Parker, Lu Feng:
Artifact for: Distributional Probabilistic Model Checking. Version 1. Zenodo, 2023 [all versions]
- [d1]Ingy Elsayed-Aly, David Parker, Lu Feng:
Artifact for: Distributional Probabilistic Model Checking. Version 2. Zenodo, 2023 [all versions] - [i26]Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David Evans:
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces. CoRR abs/2303.01621 (2023) - [i25]Kayla Boggess, Sarit Kraus, Lu Feng:
Explainable Multi-Agent Reinforcement Learning for Temporal Queries. CoRR abs/2305.10378 (2023) - [i24]Josephine Lamp, Yuxin Wu, Steven Lamp, Prince Afriyie, Kenneth C. Bilchick, Lu Feng, Sula Mazimba:
CARNA: Characterizing Advanced heart failure Risk and hemodyNAmic phenotypes using learned multi-valued decision diagrams. CoRR abs/2306.06801 (2023) - [i23]Ingy Elsayed-Aly, David Parker, Lu Feng:
Distributional Probabilistic Model Checking. CoRR abs/2309.05584 (2023) - [i22]Shili Sheng, David Parker, Lu Feng:
Safe POMDP Online Planning via Shielding. CoRR abs/2309.10216 (2023) - [i21]Pian Yu, Shuyang Dong, Shili Sheng, Lu Feng, Marta Kwiatkowska:
Trust-Aware Motion Planning for Human-Robot Collaboration under Distribution Temporal Logic Specifications. CoRR abs/2310.01163 (2023) - 2022
- [j7]Shili Sheng, Erfan Pakdamanian, Kyungtae Han, Ziran Wang, John Lenneman, David Parker, Lu Feng:
Planning for Automated Vehicles with Human Trust. ACM Trans. Cyber Phys. Syst. 6(4): 31:1-31:21 (2022) - [c35]Erfan Pakdamanian, Erzhen Hu, Shili Sheng, Sarit Kraus, Seongkook Heo, Lu Feng:
Enjoy the Ride Consciously with CAWA: Context-Aware Advisory Warnings for Automated Driving. UI 2022: 75-85 - [c34]Shenghui Chen, Kayla Boggess, David Parker, Lu Feng:
Multi-Objective Controller Synthesis with Uncertain Human Preferences. ICCPS 2022: 170-180 - [c33]Kayla Boggess, Sarit Kraus, Lu Feng:
Toward Policy Explanations for Multi-Agent Reinforcement Learning. IJCAI 2022: 109-115 - [c32]Shili Sheng, Erfan Pakdamanian, Kyungtae Han, Ziran Wang, Lu Feng:
A Study on Learning and Simulating Personalized Car-Following Driving Style. ITSC 2022: 1208-1215 - [i20]Kayla Boggess, Sarit Kraus, Lu Feng:
Toward Policy Explanations for Multi-Agent Reinforcement Learning. CoRR abs/2204.12568 (2022) - [i19]Ingy Elsayed-Aly, Lu Feng:
Logic-based Reward Shaping for Multi-Agent Reinforcement Learning. CoRR abs/2206.08881 (2022) - [i18]Shili Sheng, Erfan Pakdamanian, Kyungtae Han, Ziran Wang, Lu Feng:
A Study on Learning and Simulating Personalized Car-Following Driving Style. CoRR abs/2208.08002 (2022) - [i17]Erfan Pakdamanian, Erzhen Hu, Shili Sheng, Sarit Kraus, Seongkook Heo, Lu Feng:
Enjoy the Ride Consciously with CAWA: Context-Aware Advisory Warnings for Automated Driving. CoRR abs/2208.13900 (2022) - [i16]Maryam Bagheri, Josephine Lamp, Xugui Zhou, Lu Feng, Homa Alemzadeh:
Towards Developing Safety Assurance Cases for Learning-Enabled Medical Cyber-Physical Systems. CoRR abs/2211.15413 (2022) - 2021
- [j6]Meiyi Ma, John A. Stankovic, Lu Feng:
Toward Formal Methods for Smart Cities. Computer 54(9): 39-48 (2021) - [j5]John A. Stankovic, Homa Alemzadeh, Brad Campbell, John C. Lach, Lu Feng, Cody H. Fleming, Jonathan L. Goodall, Toluwalogo Odumosu, Daniel Quinn, Yuan Tian, Kelley Tobler:
A Graduate Curriculum in Cyber-Physical Systems. IEEE Des. Test 38(3): 112-120 (2021) - [j4]Meiyi Ma, Ezio Bartocci, Eli Lifland, John A. Stankovic, Lu Feng:
A Novel Spatial-Temporal Specification-Based Monitoring System for Smart Cities. IEEE Internet Things J. 8(15): 11793-11806 (2021) - [j3]Meiyi Ma, John A. Stankovic, Ezio Bartocci, Lu Feng:
Predictive Monitoring with Logic-Calibrated Uncertainty for Cyber-Physical Systems. ACM Trans. Embed. Comput. Syst. 20(5s): 101:1-101:25 (2021) - [c31]Ingy Elsayed-Aly, Suda Bharadwaj, Christopher Amato, Rüdiger Ehlers, Ufuk Topcu, Lu Feng:
Safe Multi-Agent Reinforcement Learning via Shielding. AAMAS 2021: 483-491 - [c30]Erfan Pakdamanian, Shili Sheng, Sonia Baee, Seongkook Heo, Sarit Kraus, Lu Feng:
DeepTake: Prediction of Driver Takeover Behavior using Multimodal Data. CHI 2021: 103:1-103:14 - [c29]Shili Sheng, Erfan Pakdamanian, Kyungtae Han, Ziran Wang, John Lenneman, Lu Feng:
Trust-based route planning for automated vehicles. ICCPS 2021: 1-10 - [c28]Shuyang Dong, Meiyi Ma, Lu Feng:
A smart city simulation platform with uncertainty. ICCPS 2021: 229-230 - [c27]Sonia Baee, Erfan Pakdamanian, Inki Kim, Lu Feng, Vicente Ordonez, Laura E. Barnes:
MEDIRL: Predicting the Visual Attention of Drivers via Maximum Entropy Deep Inverse Reinforcement Learning. ICCV 2021: 13158-13168 - [e1]Lu Feng, Dana Fisman:
Runtime Verification - 21st International Conference, RV 2021, Virtual Event, October 11-14, 2021, Proceedings. Lecture Notes in Computer Science 12974, Springer 2021, ISBN 978-3-030-88493-2 [contents] - [i15]Shili Sheng, Erfan Pakdamanian, Kyungtae Han, Ziran Wang, John Lenneman, Lu Feng:
Trust-Based Route Planning for Automated Vehicles. CoRR abs/2101.03267 (2021) - [i14]Ingy Elsayed-Aly, Suda Bharadwaj, Christopher Amato, Rüdiger Ehlers, Ufuk Topcu, Lu Feng:
Safe Multi-Agent Reinforcement Learning via Shielding. CoRR abs/2101.11196 (2021) - [i13]Meiyi Ma, Ezio Bartocci, Eli Lifland, John A. Stankovic, Lu Feng:
A Novel Spatial-Temporal Specification-Based Monitoring System for Smart Cities. CoRR abs/2104.04904 (2021) - [i12]Shenghui Chen, Kayla Boggess, David Parker, Lu Feng:
Multi-Objective Controller Synthesis with Uncertain Human Preferences. CoRR abs/2105.04662 (2021) - 2020
- [c26]Erfan Pakdamanian, Nauder Namaky, Shili Sheng, Inki Kim, James Arthur Coan, Lu Feng:
Toward Minimum Startle After Take-Over Request: A Preliminary Study of Physiological Data. AutomotiveUI (adjunct) 2020: 27-29 - [c25]Meiyi Ma, Ezio Bartocci, Eli Lifland, John A. Stankovic, Lu Feng:
SaSTL: Spatial Aggregation Signal Temporal Logic for Runtime Monitoring in Smart Cities. ICCPS 2020: 51-62 - [c24]Shenghui Chen, Kayla Boggess, Lu Feng:
Towards Transparent Robotic Planning via Contrastive Explanations. IROS 2020: 6593-6598 - [c23]Meiyi Ma, Ji Gao, Lu Feng, John A. Stankovic:
STLnet: Signal Temporal Logic Enforced Multivariate Recurrent Neural Networks. NeurIPS 2020 - [c22]Meiyi Ma, Ezio Bartocci, John A. Stankovic, Lu Feng:
Predictive monitoring with uncertainty for deep learning enabled smart cities: poster abstract. SenSys 2020: 711-712 - [i11]Shenghui Chen, Kayla Boggess, Lu Feng:
Towards Transparent Robotic Planning via Contrastive Explanations. CoRR abs/2003.07425 (2020) - [i10]Meiyi Ma, John A. Stankovic, Ezio Bartocci, Lu Feng:
CityPM: Predictive Monitoring with Logic-Calibrated Uncertainty for Smart Cities. CoRR abs/2011.00384 (2020) - [i9]Kayla Boggess, Shenghui Chen, Lu Feng:
Towards Personalized Explanation of Robotic Planning via User Feedback. CoRR abs/2011.00524 (2020) - [i8]Meriel von Stein, Sebastian G. Elbaum, Lu Feng, Shili Sheng:
Probabilistic Conditional System Invariant Generation with Bayesian Inference. CoRR abs/2012.06615 (2020) - [i7]Erfan Pakdamanian, Shili Sheng, Sonia Baee, Seongkook Heo, Sarit Kraus, Lu Feng:
DeepTake: Prediction of Driver Takeover Behavior using Multimodal Data. CoRR abs/2012.15441 (2020)
2010 – 2019
- 2019
- [j2]BaekGyu Kim, Lu Feng, Oleg Sokolsky, Insup Lee:
Determining Timing Parameters for the Code Generation from Platform-Independent Timed Models. ACM Trans. Cyber Phys. Syst. 3(3): 28:1-28:32 (2019) - [c21]Josephine Lamp, Simone Silvetti, Marc D. Breton, Laura Nenzi, Lu Feng:
A Logic-Based Learning Approach to Explore Diabetes Patient Behaviors. CMSB 2019: 188-206 - [c20]Shili Sheng, Erfan Pakdamanian, Kyungtae Han, BaekGyu Kim, Prashant Tiwari, Inki Kim, Lu Feng:
A Case Study of Trust on Autonomous Driving. ITSC 2019: 4368-4373 - [c19]Shenghui Chen, Zhiming Fan, Haiying Shen, Lu Feng:
Performance Modeling and Verification of Load Balancing in Cloud Systems Using Formal Methods. MASS Workshops 2019: 146-151 - [i6]Shili Sheng, Erfan Pakdamanian, Kyungtae Han, BaekGyu Kim, Prashant Tiwari, Inki Kim, Lu Feng:
A Case Study of Trust on Autonomous Driving. CoRR abs/1904.11007 (2019) - [i5]Josephine Lamp, Simone Silvetti, Marc D. Breton, Laura Nenzi, Lu Feng:
A Logic-Based Learning Approach to Explore Diabetes Patient Behaviors. CoRR abs/1906.10073 (2019) - [i4]Meiyi Ma, Ezio Bartocci, Lu Feng, John A. Stankovic:
Runtime Monitoring of Real time Safety Requirements in Smart Cities. CoRR abs/1908.02366 (2019) - [i3]Sonia Baee, Erfan Pakdamanian, Vicente Ordonez, Inki Kim, Lu Feng, Laura E. Barnes:
EyeCar: Modeling the Visual Attention Allocation of Drivers in Semi-Autonomous Vehicles. CoRR abs/1912.07773 (2019) - 2018
- [c18]Meiyi Ma, John A. Stankovic, Lu Feng:
Cityresolver: a decision support system for conflict resolution in smart cities. ICCPS 2018: 55-64 - [c17]Lu Feng, Mahsa Ghasemi, Kai-Wei Chang, Ufuk Topcu:
Counterexamples for Robotic Planning Explained in Structured Language. ICRA 2018: 7292-7297 - [c16]William Young, John Corbett, Matthew S. Gerber, Stephen Patek, Lu Feng:
DAMON: A Data Authenticity Monitoring System for Diabetes Management. IoTDI 2018: 25-36 - [c15]Pengyuan Lu, Limin Zhang, B. Brian Park, Lu Feng:
Attack-Resilient Sensor Fusion for Cooperative Adaptive Cruise Control. ITSC 2018: 3955-3960 - [i2]Lu Feng, Mahsa Ghasemi, Kai-Wei Chang, Ufuk Topcu:
Counterexamples for Robotic Planning Explained in Structured Language. CoRR abs/1803.08966 (2018) - [i1]Erfan Pakdamanian, Lu Feng, Inki Kim:
The Effect of Whole-Body Haptic Feedback on Driver's Perception in Negotiating a Curve. CoRR abs/1810.07294 (2018) - 2017
- [c14]Meiyi Ma, John A. Stankovic, Lu Feng:
Runtime Monitoring of Safety and Performance Requirements in Smart Cities. SafeThings@SenSys 2017: 44-50 - 2016
- [j1]Lu Feng, Clemens Wiltsche, Laura R. Humphrey, Ufuk Topcu:
Synthesis of Human-in-the-Loop Control Protocols for Autonomous Systems. IEEE Trans Autom. Sci. Eng. 13(2): 450-462 (2016) - [c13]Lu Feng, Laura R. Humphrey, Insup Lee, Ufuk Topcu:
Human-interpretable diagnostic information for robotic planning systems. IROS 2016: 1673-1680 - 2015
- [c12]BaekGyu Kim, Lu Feng, Linh T. X. Phan, Oleg Sokolsky, Insup Lee:
Platform-specific timing verification framework in model-based implementation. DATE 2015: 235-240 - [c11]Lu Feng, Clemens Wiltsche, Laura R. Humphrey, Ufuk Topcu:
Controller synthesis for autonomous systems interacting with human operators. ICCPS 2015: 70-79 - [c10]Sanjian Chen, Lu Feng, Michael R. Rickels, Amy Peleckis, Oleg Sokolsky, Insup Lee:
A Data-Driven Behavior Modeling and Analysis Framework for Diabetic Patients on Insulin Pumps. ICHI 2015: 213-222 - [c9]BaekGyu Kim, Lu Feng, Oleg Sokolsky, Insup Lee:
Platform-Specific Code Generation from Platform-Independent Timed Models. RTSS 2015: 75-86 - [c8]Andrew L. King, Lu Feng, Sam Procter, Sanjian Chen, Oleg Sokolsky, John Hatcliff, Insup Lee:
Towards Assurance for Plug & Play Medical Systems. SAFECOMP 2015: 228-242 - 2014
- [b1]Lu Feng:
On learning assumptions for compositional verification of probabilistic systems. University of Oxford, UK, 2014 - [c7]Anitha Murugesan, Lu Feng, Mats Per Erik Heimdahl, Sanjai Rayadurgam, Michael W. Whalen, Insup Lee:
Exploring the twin peaks using probabilistic verification techniques. TwinPeaks 2014: 18-23 - [c6]Lu Feng, Andrew L. King, Sanjian Chen, Anaheed Ayoub, Junkil Park, Nicola Bezzo, Oleg Sokolsky, Insup Lee:
A Safety Argument Strategy for PCA Closed-Loop Systems: A Preliminary Proposal. MCPS 2014: 94-99 - 2013
- [c5]Andrew L. King, Lu Feng, Oleg Sokolsky, Insup Lee:
Assuring the safety of on-demand medical cyber-physical systems. CPSNA 2013: 1-6 - [c4]Andrew L. King, Lu Feng, Oleg Sokolsky, Insup Lee:
A Modal Specification Approach for On-Demand Medical Systems. FHIES 2013: 199-216 - 2011
- [c3]Lu Feng, Tingting Han, Marta Z. Kwiatkowska, David Parker:
Learning-Based Compositional Verification for Synchronous Probabilistic Systems. ATVA 2011: 511-521 - [c2]Lu Feng, Marta Z. Kwiatkowska, David Parker:
Automated Learning of Probabilistic Assumptions for Compositional Reasoning. FASE 2011: 2-17 - 2010
- [c1]Lu Feng, Marta Z. Kwiatkowska, David Parker:
Compositional Verification of Probabilistic Systems Using Learning. QEST 2010: 133-142
Coauthor Index
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