Ankur Goel
Director Of Engineering at BrowserStack
Mumbai, Maharashtra, India
Summary
🤩
Rockstar🎓
Top SchoolAnkur Goel is a Director of Engineering based in Mumbai with 13 years of experience building high-velocity Developer SaaS and fintech platforms. He coaches and scales engineering teams while driving pragmatic system and backend design focused on performance, simplicity, and collaboration. His career at BrowserStack and Drip Capital spans hands-on roles from software engineer to senior leadership, giving him deep operational and product-facing experience. Ankur contributes to open-source probabilistic graphical models—adding EM-based parameter estimation to pgmpy—which reflects a strong interest in applied ML and rigorous probabilistic methods beyond typical infra work. He blends a practical engineering mindset with formal learning in databases and machine learning from Stanford and BerkeleyX, enabling him to translate complex algorithms into production-ready services.
12 years of coding experience
11 years of employment as a software developer
Machine Learning Computer Science, Machine Learning Computer Science at Stanford University, CourseraSoftware as a Service Computer Software Engineering, Software as a Service Computer Software Engineering at BerkeleyXIntroduction to Databases Data Modeling/Warehousing and Database Administration, Introduction to Databases Data Modeling/Warehousing and Database Administration at Stanford OnlineHigh School Computer Science, High School Computer Science at New State AcademyB.Tech Computer Science Engineering, B.Tech Computer Science Engineering at Guru Gobind Singh Indraprastha University
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (5)
probabilistic-graphical-models10
jupyter-notebook10
python10
documentation10
machine-learning8
Programming languages (4)
Github contributions (5)
pgmpy/pgmpy_notebook
Nov 2014 - May 2022
Short Tutorial to Probabilistic Graphical Models(PGM) and pgmpy
Role in this project:
Technical Writer
Technical WriterContributions:68 commits, 19 PRs, 56 pushes in 7 years 6 months
Contributions summary:Ankur's commits primarily focus on creating and updating documentation for a tutorial on Probabilistic Graphical Models (PGM) using the `pgmpy` library. The initial commit introduces the tutorial with a notebook on PGM, and subsequent commits add content, structure, and formatting to both a Jupyter Notebook and a slideshow presentation of the tutorial. This suggests a focus on explaining complex concepts, and creating easy to understand examples.
pythonstatistical-inferencegraphical-modelsmissing-datashort
pgmpy/pgmpy
Sep 2013 - Jan 2023
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
Role in this project:Back-end Developer
Back-end DeveloperContributions:15 releases, 169 reviews, 1643 commits in 9 years 5 months
Contributions summary:Ankur implemented and modified the `BayesianEstimator.py` module to add functionality for estimating parameters using the Expectation-Maximization algorithm. They incorporated the weighted version of the Maximum Likelihood Estimator in EM and improved tests for this functionality, showcasing work on parameter estimation for Bayesian Networks. The user also added code for a custom function to measure the likelihood.
causal-modelspythondagbayesian-inferencecausal
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.