Dr. Janis Leclerc

Professor of Machine Learning at UC Berkeley

Mexico City

About

Janis Leclerc is a Professor of Machine Learning at the University of California, Berkeley. She received her M.S. in Machine Learning from UC Berkeley in 2015 and her Ph.D. in Machine Learning from Stanford in 2019. Her research focuses on developing efficient and effective deep learning models and on understanding the underlying algorithms and data structures. She has published over 100 papers in high-impact journals, and her work has been featured in The New York Times, The Wall Street Journal, and Forbes.

Publications

Using Machine Learning to Derive Insights from Unstructured Data

International Journal of Machine Learning and Computing

2023

Interpreting the Results of Machine Learning Algorithms

IEEE Transactions on Knowledge and Data Engineering

2022

Exploring Applications of Machine Learning in Autonomous Vehicle Design

IEEE Transactions on Intelligent Transportation Systems

2021

Analyzing and Predictive Modeling with Machine Learning

International Journal of Machine Learning and Cybernetics

2020

The Role of Deep Learning in Image Recognition

Proceedings of the IEEE

2019

Evaluating the Accuracy of Machine Learning Models

ACM Transactions on Knowledge Discovery from Data

2018

Education

UC Berkeley

M.S., Machine Learning / November, 2015

Stanford

Ph.D, Machine Learning / March, 2019

Experience

UC Berkeley

Professor of Machine Learning / November, 2019 — Present

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