Aman Malali
PHD Student at University of Massachusetts Amherst
Amherst, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolAman Malali is a PhD student at UMass Amherst with nine years of software and research experience focused on automated ML model maintenance, detecting model failure, and handling input data drift. Advised by Peter J. Haas and Yanlei Diao in the DREAM lab, he develops techniques to quantify model performance without ground truth and aims to build a lightweight framework that maintains multiple models under changing data distributions. His internships and industry work span practical calibration methods (feature-based temperature scaling at Dolby) to real-time robotics teleoperation and visual SLAM at IISc, showing a rare blend of theoretical rigor and systems engineering. Comfortable teaching data management and shipping end-to-end pipelines, he brings both strong academic credentials and hands-on production experience to problems at the intersection of ML reliability and scalable systems.
10 years of coding experience
2 years of employment as a software developer
Bachelor of Engineering - BE, Computer Science, 9.50/10.0, Bachelor of Engineering - BE, Computer Science, 9.50/10.0 at Ramaiah Institute Of TechnologyDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Massachusetts Amherst
English, Hindi, Kannada
Github Skills (22)
transfer-learning8
structured-data7
automated-machine-learning6
natural-language-processing6
gluon6
python6
ensemble-learning6
backend5
forecast5
object-detection5
computer-vision5
automl5
autogluon5
forecasting5
machine-learning5
Programming languages (3)
Github contributions (5)
amanmalali/CompilerDock
Jun 2020 - Aug 2020
Sandbox code compiler API with support for multiple languages. It can be used as the backend for a web based code compiler.
Contributions:22 commits, 6 PRs, 19 pushes in 1 month
backendcompiler
amanmalali/MSER-Object-Detection
Aug 2017 - Nov 2017
Contributions:13 commits, 2 PRs, 11 pushes in 2 months
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