Anil Saini

Research Data Scientist

Los Angeles, California, United States
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Summary

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Senior
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Top School
Anil Saini is a research data scientist at Cedars-Sinai's Department of Computational Medicine, applying AI to address real-world healthcare and societal challenges. He collaborates with multidisciplinary teams to design fair machine learning and AutoML methods for medical data. He earned a PhD and MS in Computer Science from the University of Massachusetts Amherst and a B.Tech from IIT Roorkee, with his doctoral work centered on genetic programming. He was awarded the Best Paper Award at EuroGP 2020 for his work on parent selection methods, highlighting his contributions to evolutionary computation. His career spans a postdoctoral role at Cedars-Sinai and an industry internship at Adobe Research India, illustrating a strong blend of research and practical application. Based in Los Angeles with about eight years of experience, he continually translates academic insights into clinically impactful AI solutions.
code8 years of coding experience
job8 years of employment as a software developer
bookBachelor of Technology (B.Tech.), Computer Science, Bachelor of Technology (B.Tech.), Computer Science at IIT Roorkee
bookDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Massachusetts Amherst
bookIntermediate, Intermediate at D. A. V. Public School, Naraingarh
languagesPunjabi, Hindi, English
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Github Skills (11)

stack-based10
genetic10
system-programming10
genetic-programming10
interpreter9
programming-language9
clojure9
python1
nlp1
natural-language-processing1
evolution1

Programming languages (4)

MakefileJupyter NotebookClojurePython

Github contributions (5)

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theaksaini/Clojush

Jan 2018 - Jun 2023

The Push programming language and the PushGP genetic programming system implemented in Clojure.
Contributions:2 PRs, 67 pushes, 10 branches in 5 years 5 months
pushmodularitygeneticsystem-programminggenetic-programming
theaksaini/tpot2

Apr 2023 - Feb 2024

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Contributions:2 PRs, 16 pushes, 3 branches in 9 months
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