I am a fifth-year Ph.D. student in the Mechanical Engineering Department, College of Engineering at Carnegie Mellon University. I received my bachelor's degree from the Industrial and Systems Engineering Department at ITS and master's degree from the Industrial and Operations Engineering Department at the University of Michigan.
I work in the CMU Safe AI Lab supervised by Prof. Ding Zhao. Our group’s work focuses on the development of trustworthy AI and safe deployment of intelligent systems in general. Much of my work combines machine learning and rare-event theories to efficiently simulate rare catastrophic events. The applications of this line of work include the accelerated safety testing of autonomous vehicles. Here is the link to my CV.
Some of my most recent publications:- Arief, Mansur, Zhepeng Cen, Zhenyuan Liu, Zhiyuan Huang, Bo Li, Henry Lam, and Ding Zhao. "Test Against High-Dimensional Uncertainties: Accelerated Evaluation of Autonomous Vehicles with Deep Importance Sampling." Under review. [Link]
- Arief, Mansur, Yuanlu Bai, Wenhao Ding, Shengyi He, Zhiyuan Huang, Henry Lam, and Ding Zhao. "Certifiable deep importance sampling for rare-event simulation of black-box systems." Under review. [Link]
- Arief, Mansur, Zhepeng Cen, Zhenyuan Liu, Zhiyuan Huang, Bo Li, Henry Lam, and Ding Zhao. "Certifiable Evaluation for Autonomous Vehicle Perception Systems Using Deep Importance Sampling (Deep IS)." To appear in 2022 25th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2022. [Link]
- Arief, Mansur, Zhiyuan Huang, Guru Koushik Senthil Kumar, Yuanlu Bai, Shengyi He, Wenhao Ding, Henry Lam, and Ding Zhao. "Deep Probabilistic Accelerated Evaluation: A Certifiable Rare-Event Simulation Methodology for Black-Box Autonomy." In Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS). PMLR, 2021. [Link]
- Arief, Hasan Asy’ari, Mansur Arief, Guilin Zhang, Zuxin Liu, Manoj Bhat, Ulf Geir Indahl, Håvard Tveite, and Ding Zhao. "SAnE: Smart Annotation and Evaluation Tools for Point Cloud Data." IEEE Access 8 (2020): 131848-131858. [Link]
- Chen, Rui, Mansur Arief, Weiyang Zhang, and Ding Zhao. "How to Evaluate Proving Grounds for Self-Driving? A Quantitative Approach." IEEE Transactions on Intelligent Transportation Systems (2020). [Link]
- Liu, Zuxin, Mansur Arief, and Ding Zhao. "Where should we place lidars on the autonomous vehicle?-an optimal design approach." In 2019 International Conference on Robotics and Automation (ICRA), pp. 2793-2799. IEEE, 2019. [Link]
- Arief, Mansur, Peter Glynn, and Ding Zhao. "An accelerated approach to safely and efficiently test pre-production autonomous vehicles on public streets." In 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 2006-2011. IEEE, 2018. [Link]
- 09/27/22: I present Deep IS work at ITSC 2022.
- 09/25/22: I start as a volunteer at AFS USA Western PA and attend the exchange student orientation in Mars.
- 08/01/22: I submit the journal version of our Deep IS work.
- 06/15/22: Two other papers I co-authoed accepted at ITSC 2022.
- 06/15/22: Deep IS paper accepted at ITSC 2022.
- 03/15/22: I help colleagues from KTH Royal Institute of Technology (Sweden), ITS (Indonesia), and CMU ESTP (USA) and submit two more papers to ITSC 2022.
- 03/02/22: We submit a survey paper on safety-critical driving scenario generation for journal publication.
- 03/01/22: I submit one paper to ITSC 2022.
- 01/31/22: I present a summary of our past work on "Certifiable Deep Importance Sampling for Rare-Event Simulation of Black-Box Systems" to SISL lab meeting (Stanford).
- 11/07/21: I present at SkolaTalk with Aditya (Digital Skola CEO) about the comparison in tech education between Indonesia & US.
- 11/02/21: We submit the journal version of our Deep-PrAE work.
- 08/29/21: Together with Sabrina, I share some insights regarding How to be Global Student and Student Life as an Exchange Student to ITS ISE Undergraduate Students.
- 05/27/21: I present Research Opportunities for ISE Graduate Students to ITS ISE Graduate Students.
- 05/21/21: I start internship at Bosch as Machine Learning/Computer Vision Research Intern.
- 03/03/21: I present Deep-PrAE work at SIAM CSE 2021.
- 01/22/21: One paper accepted to AISTATS 2021.
- 11/09/20: I present a work on certifiable efficiency for rare-event probability estimation and its relaxation at INFORMS Annual Meeting 2020.