rizal.fathony.com

rizal@fathony.com

I am an Applied Researcher in the AI Foundations team at Capital One, working on developing foundation models of human behaviors. My research interests span across various machine learning areas, including theoretically motivated learning algorithms, performance metric optimization, fair and safe learning, anomaly detection, graph neural networks, sequence and structured prediction, deep learning, transformer architectures, and foundation models.

Before joining Capital One, I was a lead data scientist at Grab (Southeast Asia’s leading superapp for ride-hailing, food delivery, transport, services, and payments), driving the AI and ML initiatives for mitigating unknown, new, and emerging fraudulent behaviors. In particular, I led the research and development of graph neural network models (both supervised and unsupervised) for mitigating various types of fraudulent behaviors.

I received my Ph.D. in Computer Science from the University of Illinois at Chicago. I was fortunate to have Prof. Brian Ziebart as my advisor and Prof. Xinhua Zhang as one of my collaborators. After completing my PhD, I joined Carnegie Mellon University (CMU) and Bosch Center for Artificial Intelligence (BCAI), as a post-doctoral research fellow, hosted by Prof. Zico Kolter.

I was born and raised in a small village in Java island, Indonesia. After high school, I moved to Jakarta to complete my bachelor degree at the Institute of Statistics. I was also very lucky to be awarded Fulbright scholarship in 2012. Being a Fulbright grantee was a milestone to pursue my passion in machine learning and artificial intelligence.

I am fond of nature. In my spare time, I enjoy hiking in national parks and local forests with my family.