Ameya Patil in

Ameya Patil

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Senior Applied Scientist at Amazon Lab126
📍 San Francisco Bay Area, United States

Ameya Patil is a Senior Applied Scientist at Amazon, specializing in robust and energy-efficient machine learning. A PhD graduate from the University of Illinois Urbana-Champaign, his work spans the entire design stack, from developing adversarially robust deep learning algorithms to designing efficient hardware and circuits for their implementation.

His academic journey shows an interest in applying complex technology to practical human challenges. His early undergraduate research, for instance, involved developing a framework to evaluate the driving performance of power wheelchair users, indicating a focus on assistive technologies and real-world impact.

He is a recipient of the M. E. Van Valkenburg Graduate Research Award, given to outstanding PhD students in circuits, systems, or computers.

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Experience
6 Years
Current Role
Senior Applied Scientist
Location
San Francisco Bay Area, United States
Personality Overview

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Priorities

Topics Ameya cares about

Robust Machine Learning
His PhD thesis and numerous recent publications focus on making ML models robust against adversarial attacks and missing data, particularly in multimodal systems.
Energy-Efficient AI
A core theme of his research is the energy-efficient implementation of ML classifiers, exploring everything from circuit design to in-memory computing architectures.
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Career

Work history

5-2024
Senior Applied Scientist
Amazon Lab126
9-2021 - 5-2024
Applied Scientist
Amazon Lab126
8-2016 - 10-2021
Doctoral Student
University of Illinois at Urbana-Champaign
5-2018 - 8-2018
Research Intern
Intel Labs
5-2013 - 8-2013
Undergraduate Research Intern
University of Illinois Urbana-Champaign
In the press

Media appearances

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Education
2016 - 2019
Doctor of Philosophy - PhD
University of Illinois Urbana-Champaign
2014 - 2016
Master's Degree
University of Illinois Urbana-Champaign
Social presence
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Behavioral profile

DISC profile (public)

DISC behavioral profile

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