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Michael Maire

Computer Vision Image Segmentation Deep Learning For Visual Recognition Object Detection
University of Chicago Department of Computer Science

About

Michael Maire is an associate professor in the Department of Computer Science at the University of Chicago. He was previously a research assistant professor at the Toyota Technological Institute at Chicago (TTIC), where he maintains a courtesy appointment. Prior to TTIC, he was a postdoctoral scholar at the California Institute of Technology. He received a PhD in computer science from the University of California, Berkeley in 2009.

Research Performance Summary

83
Total Papers
87413
Total Citations
37
H-Index
2003-2026
Active Research Span

First Recorded Paper

Dynamic Code Updates

Year: 2003

Citations: 0

Venue: California Institute of Technology

Latest Recorded Paper

Keeper: Automated Testing and Fixing of Machine Learning Software—RCR Report

Year: 2026

Citations: 0

Venue: ACM Transactions on Software Engineering and Methodology 35 (2)

Last 10 Years Publication Activity

This timeline shows the professor's yearly publication activity.

2026
1
2025
4
2024
12
2023
9
2022
4
2021
7
2020
9
2019
1
2018
2
2017
1
2016
4

Publication Venues and Collaboration

Journal, Conference, and Book Publication Breakdown

Conference 40
Journal 3
Book 2

Top Coauthors

Maire Savarese

Research Impact by Period

2025-2026

Period Stats
Papers 5
Citations 11
Avg. Citations / Paper 2.2
H-Index 3

2020-2024

Period Stats
Papers 41
Citations 1478
Avg. Citations / Paper 36
H-Index 16

2015-2019

Period Stats
Papers 11
Citations 4250
Avg. Citations / Paper 386.4
H-Index 11

2010-2014

Period Stats
Papers 15
Citations 77954
Avg. Citations / Paper 5196.9
H-Index 13

2005-2009

Period Stats
Papers 5
Citations 2999
Avg. Citations / Paper 599.8
H-Index 5

2000-2004

Period Stats
Papers 6
Citations 721
Avg. Citations / Paper 120.2
H-Index 5

Contact and Professional Links

Contact Information

mmaire@cs.uchicago.edu

Detected Research Keywords

Microsoft Coco Common Coco Common Objects Common Objects Context Computer Vision Eccv Visual Representation Learning Machine Learning Cloud Learning Cloud Apis Cloud Apis Used Apis Used Correctly Machine Learning Apis