maria (at) stat (dot) cmu (dot) edu

I am a fourth-year PhD student in the Department of Statistics and the Machine Learning Department at Carnegie Mellon University, advised by Ryan Tibshirani. My general interests are in computational statistics, particularly for sequential decision-making and online forecasting.

As part of CMU’s Delphi group, I am researching nowcasting algorithms using digital surveillance data. We are currently focusing our efforts to develop forecasting and nowcasting models for COVID-19. During my PhD, I also studied machine learning approaches for motion planning with applications in self-driving cars at Argo AI.

Current groups

WinS
Delphi, Epidemiological Forecasting Women in Statistics @CMU

Previous projects and groups

2019 Returned to Argo AI as a research intern exploring preference-based trajectory selection.
2018 Worked as a motion planning intern for Argo AI, developing machine learning features for self-driving cars.
2015–2017 Researched at Laber Labs under Eric Laber in the Department of Statistics, building educational games demonstrating reinforcement learning algorithms. You can read about it in AMSTAT or play some of the games.
2016 Worked on constructing prediction regions for multiple-objective Markov decision processes with Daniel Lizotte at University of Western Ontario [1].
2016 Interned at Duke-National University of Singapore Medical School supervised by Bibhas Chakraborty working on dynamic treatment regimes.
2014–2017 Prototyped anomaly detection methods for high-frequency data at SAS Institute [2, 3].
laber labs
Argo AI NC State, Laber Labs SAS Institute

© 2020 Maria Jahja