Pratyush Maini

Co-Founder

San Francisco, California, United States6 yrs 5 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

PhD candidate specializing in Machine Learning.
Published research on cost-effective LLM pre-training.
Experience in high-impact AI and biotechnology projects.

Stackforce AI infers this person is a Machine Learning expert with a focus on AI and Biotechnology.

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Skills

Core Skills

Machine Learning

Other Skills

Natural Language Processing (NLP)TensorFlowDeep LearningData StructuresComputer VisionArtificial Intelligence (AI)JavaStochastic ProcessesSynthetic BiologyEthical HackingPython (Programming Language)

About

http://pratyushmaini.github.io/

Experience

6 yrs 5 mos

Total Experience

1 yr 9 mos

Average Tenure

4 yrs 8 mos

Current Experience

Datologyai

Founding Member

Jan 2024 – Present · 2 yrs 4 mos · Redwood City, California, United States

Founding Member of Technical Staff. Charting new frontiers for high quality data research.

Apple

Research Intern

May 2023 – Sep 2023 · 4 mos · Cupertino, California, United States

Released a new research paper called Rephrasing the Web. This allows pre-training LLMs at 3x lesser cost. https://arxiv.org/abs/2401.16380

Machine LearningNatural Language Processing (NLP)

Carnegie mellon university

Doctoral Researcher

Sep 2021 – Present · 4 yrs 8 mos · Pittsburgh, Pennsylvania, United States

Samsung electronics

Computer Vision Research Engineer

Oct 2020 – Aug 2021 · 10 mos · South Korea

University of toronto

Research Intern

May 2020 – Sep 2020 · 4 mos · Zoom

Samsung electronics

Research And Development Intern

May 2019 – Jul 2019 · 2 mos · Suwon, Gyeonggi-do, Korea

Carnegie mellon university

Research Intern

Dec 2018 – Jan 2019 · 1 mo · Pittsburgh, PA

Epfl (école polytechnique fédérale de lausanne)

Research Intern

May 2018 – Jul 2018 · 2 mos · Lausanne Area, Switzerland

Very Large Scale Computing Laboratory at EPFL, Switzerland
Worked on a TensorFlow based Cluster-scale, high-throughput framework to make gene sequencing computationally affordable.
Implemented a Striped Smith-Waterman Algorithm to speed-up the sub-process of protein alignment by over 6 times