Omar Khursheed - MATS Scholar at MATS Research

Omar Khursheed

MATS Scholar at MATS Research

Sunnyvale, California, United States

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Summary

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Senior

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Top School

Omar Khursheed is an Applied Scientist with a decade of experience building and researching deep learning systems for speech, ASR, keyword spotting, and NLP, currently on leave from Amazon as a MATS Scholar exploring AI safety. At Amazon Alexa Speech he bridges research and production, applying mechanistic interpretability and computational social science to make voice systems robust and fair. His graduate work at UMass Amherst produced a 1.7M-item dataset and novel genderedness metrics for analyzing cultural bias in media, reflecting a strong interdisciplinary bent. Omar also contributes to open-source spatial analysis (PySAL), improving numerical correctness and usability, showing attention to engineering rigor beyond core speech tasks. Based in Sunnyvale, he combines academic depth with pragmatic product experience and a curiosity for how ML systems interact with society.

10 years of coding experience

3 years of employment as a software developer

Bachelor of Technology (B.Tech.) Computer Engineering, Bachelor of Technology (B.Tech.) Computer Engineering at Aligarh Muslim University

MS Computer Science, MS Computer Science at University of Massachusetts Amherst

English, Hindi, Urdu

Github Skills (5)

spatial-analysis10

python10

data-analysis10

numpy9

doctest7

Programming languages (2)

JavaScriptPython

Github contributions (5)

pysal/pysal

Mar 2017 - Apr 2017

PySAL: Python Spatial Analysis Library Meta-Package

Role in this project:

Data Scientist

Contributions:5 commits, 2 PRs, 4 comments in 25 days

Contributions summary:Omar primarily focused on refining the `assuncao_rate` function, making corrections to handle negative values and address indentation issues within the `pysal/esda/smoothing.py` file. They also updated file paths in the doctests for the reading file examples and used `.get_path()` instead of explicit file paths. These changes indicate a focus on improving the correctness and usability of spatial analysis functionalities.

meta-packagepythonspatial-analysispysalspatial

omarkhursheed/finance-ml

Aug 2017 - Jan 2018

Contributions:33 commits, 28 pushes, 1 branch in 5 months

stock-markettechniquespythondata-sciencestock-market-data

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