Short Bio

Data Science Engineer with mid-level experience in developing machine-learning-based software using R and Python. Successfully managed analytics projects in industry and academia from conception to production.

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Academic News:

• October 2019 : Top 11% for the most performing model (92.8% AUC) at IEEE Competition for Fraud detection Competition. Check out some of my contributions. [solution will be published soon!]

• September 2019 : NSF Student Funding Award for IEOM Conference in Toronto, Canada

• September 2019 : Paper of Early detection of sepsis has been accepted and presented in CinC 2019 Conference in Singapore.

• July 2019 : Talk in tech school about Machine Learning 101

• April 2019: Google Award for sepsis Research Google accepted our research proposal for early detection of sepsis. The project has been granted with $5,000 of computational resources to work on sepsis. See publications section.

• April 2019: San Francisco: Kaggle Days & Google Next’19 Proud to be part of the first Kaggle event in the US at San Francisco along with GoogleNext19. I was happy to connect and speak with other data science practitioners from Silicon Valley and Bay Area.