I am a fourth-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 safe deployment of intelligent systems. Much of my work combines machine learning and rare-event theories to efficiently simulate catastrophic rare 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, 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." To appear in the 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]
- 04/04/22: I submit the journal version of our Deep IS work.
- 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.