Publications

[CAV'23] Hoang Dung Tran, SungWoo Choi, Hideki Okamoto, Bardh Hoxha, Georgios Fainekos, and Danil Prokhorov. “Probabilistic Star Temporal Logic.” The 35th International Conference on Computer-Aided Verification (under preparation).

[LITES' 23] Hoang-Dung Tran, Luan Viet Nguyen, Patrick Musau, Weiming Xiang, and Taylor T. Johnson, "Real-Time Verification for Distributed Cyber-Physical Systems," Leibniz Transactions on Embedded Systems, 2023 (to appear). 

[IEEE TCNS'23] Luan Viet Nguyen, Hoang Dung Tran, Taylor T. Johnson, Vijay Gupta. “Decentralized Safe Control for Distributed Cyber-Physical Systems using Real-time Reachability Analysis.” The IEEE Transactions on Control of Networked Systems  (to appear).

[HSCC'23] Hoang Dung Tran, SungWoo Choi, Tomoya Yamaguchi, Bardh Hoxha, and Danil Prokhorov. “Verification of Recurrent Neural Networks using Star Reachability.” The 26th ACM International Conference on Hybrid Systems: Computation and Control (HSCC), May 2023 (to appear).

[HSCC'23] Hoang Dung Tran, SungWoo Choi, Hideki Okamoto, Bardh Hoxha, Georgios Fainekos,  and Danil Prokhorov. “Quantitative Verification of Neural Networks using ProbStars.” The 26th ACM International Conference on Hybrid Systems: Computation and Control (HSCC), May 2023 (to appear).

[IJCNN'23]  Kruttidipta Samal,  Hoang-Dung Tran, and Marilyn Wolf,  "A Markovian Error Model for DNNs in Perception-Driven Control Systems" International Joined  Conference on Neural Networks ((under review). 

[IROS'23] Apala Pramanik, Yuntao Li, Kyungki Kim, and Hoang-Dung Tran, "Vision-based safety monitoring for human-construction robot systems." The 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (under preparation).

[FormaLISE'23]  Michael Ivashchenko, SungWoo Choi, Luan Viet Nguyen, Stanley Bak, and Hoang-Dung Tran, "Verification of Binary Neural Networks." The International Conference on Formal Methods in Software Engineering, 2023 (to appear). 

[ACM-TECS'23] SungWoo Choi, Michael Ivashchenko, Luan Viet Nguyen, and Hoang-Dung Tran, "Reachability Analysis of Sigmoidal Neural Networks." The ACM Transaction on Embedded Computing Systems, Special Issue on Formal Methods and Models for System Design (under submission). 

[NFM'22] S. Bak and Hoang-Dung Tran, "Neural Network Compression of ACAS Xu Early Prototype is Unsafe: Closed-Loop Verification through Quantized State Backreachability," 14th NASA Formal Methods Symposium (NFM 2022), 33% acceptance rate. [pdf]

[JAT'22] Diego Manzanas Lopez, Taylor T. Johnson, Stanley Bak, Hoang-Dung Tran, Kerianne Hobbs, "Evaluation of Neural Network Verification Methods for Air to Air Collision Avoidance," In AIAA Journal of Air Transportation (JAT), vol. , no. , pp. , 2022, October. [pdf]

[FORMATS'22] Xiaodong Yang, Tom Yamaguchi, Hoang-Dung Tran, Taylor T. Johnson, Bardh Hoxha, Danil Prokhorov, "Neural Network Repair with Reachability Analysis." In 20th International Conference on Formal Modeling and Analysis of Timed Systems (FORMATS), vol. , no. , pp. , 2022, September. (Best Artifact Award). [pdf]

[CAV'21] Hoang-Dung Tran, Neelanjana Pal , Patrick Musau , Diego Manzanas Lopez , Nathaniel Hamilton , Xiaodong Yang, Stanley Bak , and Taylor T. Johnson.  "Robustness Verification of Semantic Segmentation Neural Networks using Relaxed Reachability ." The 33rd International Conference on Computer-Aided Verification (CAV 2021), July 18-23, 2021, [pdf].

[FAOC'21] Hoang-Dung Tran, Neelanjana Pal, Patrick Musau, Diego Manzanas Lopez, Xiaodong Yang, Luan Viet Nguyen, Weiming Xiang, Stanley Bak, and Taylor T. Johnson.  "Verification of Piecewise Deep Neural Networks: A Star Set Approach with Zonotope Pre-filter ." Formal Aspects of Computing, 2021, (Invited Paper). [pdf]

[TNNLS'21] Weiming Xiang, Hoang-Dung Tran, Xiaodong Yang, Taylor T. Johnson, "Reachable Set Estimation for Neural Network Control Systems: A Simulation-Guided Approach", In IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 5, pp. 1821-1830, 2021, May. [pdf]

[NeurIPS'21 Workshop] Safe Online Exploration with Nonlinear Constraints. Eleanor Quint, Ian Howell, Garrett Wirka, Stephen Scott, Hoang-Dung Tran. NeurIPS 2021 Workshop on Safe and Robust Control of Uncertain Systems. [pdf]

[HSCC'21] Xiaodong Yang, Taylor T. Johnson, Hoang Dung Tran, Tomoya Yamaguchi, Bardh Hoxha, and Danil Prokhorov. “Reachability Analysis of Deep ReLU Networks using Facet-Vertex Incidence.” The 24th ACM International Conference on Hybrid Systems: Computation and Control (HSCC), April 2021. [pdf]

[AIAA'21] Diego Manzanas Lopez, Taylor T. Johnson, Hoang-Dung Tran, Stanley Bak, Xin Chen, Kerianne Hobbs, "Verification of Neural Network Compression of ACAS Xu Lookup Tables with Star Set Reachability," In AIAA Scitech 2021 Forum, AIAA, 2021, January.

[CAV’20 ] Hoang-Dung Tran, Xiaodong Yang, Diego Manzanas Lopez, Patrick Musau, Luan Viet Nguyen, Weiming Xiang, Stanley Bak, and Taylor T. Johnson. “NNV: A Tool for Verification of Deep Neural Networks and Learning-Enabled Cyber-Physical Systems.” The 32nd International Conference on Computer-Aided Verification (CAV 2020), Los Angeles, California, USA, July 19-24, 2020, Acceptance Rate 27%.[pdf]

[CAV’20 ] Hoang-Dung Tran, Stanley Bak, Weiming Xiang, and Taylor T. Johnson. “Verification of Deep Convolutional Neural Networks using ImageStars..” The 32nd International Conference on Computer-Aided Verification (CAV 2020), Los Angeles, California, USA, July 19-24, 2020, Acceptance Rate 27%.[pdf]

[CAV’20 ] Stanley Bak, Hoang-Dung Tran, and Taylor T. Johnson. “Improved Geometric Path Enumeration for Verifying ReLU Neural Networks.” The 32nd International Conference on Computer-Aided Verification (CAV 2020), Los Angeles, California, USA, July 19-24, 2020, Acceptance Rate 27%.[pdf]

[IEEE-D&T’20 ] Hoang-Dung Tran, Weiming Xiang, Taylor T. Johnson. “Verification Approaches for Autonomous Learning-enabled Cyber-Physical Systems.” IEEE Design & Test, 2020.[pdf]