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]
News & Updates:
  • 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.
Older news