Rajat Sainju
Postdoctoral Appointee at Argonne National Laboratory
Chicago, Illinois, United States
Summary
👤
Senior🎓
Top SchoolRajat Sainju is an AI/ML-focused postdoctoral appointee with nine years of experience applying deep learning and computer vision to scientific instrumentation and materials research. Based at Argonne National Laboratory after a PhD in Materials Engineering from UConn, he builds Retrieval-Augmented Generation systems and anomaly-detection models to extract actionable insights from experimental logbooks, schematics, and publications for large-scale particle accelerators. His background in computational microscopy and in-situ ETEM informs a pragmatic approach to fusing domain knowledge with ML, improving uptime and experimental throughput at the Advanced Photon Source. Earlier work spans materials characterization, robotics-enabled assistive design, and campus IT operations—an uncommon mix that blends hands-on lab expertise, production ML, and systems troubleshooting. Located in Chicago, he brings both academic rigor and operational focus to cross-disciplinary AI deployments.
9 years of coding experience
9 years of employment as a software developer
Budhanilkantha SchoolDoctor of Philosophy - PhD, Materials Engineering, Doctor of Philosophy - PhD, Materials Engineering at University of ConnecticutBS, Engineering Physics, Computer Science, BS, Engineering Physics, Computer Science at Ramapo College of New Jersey
English, Nepali, Hindi, Spanish, Chinese
Github Skills (12)
computer-vision7
object-detection7
pytorch6
tensorrt6
inference6
deep-learning6
onnx6
coreml5
3d-detection5
pose-estimation4
ultralytics2
multi-object-tracking2
Programming languages (1)
Github contributions (5)
rajatsainju/rajatsainju.github.io
Nov 2021 - Sep 2024
Contributions:37 pushes, 1 branch in 2 years 10 months
rajatsainju/DefectSegNet
Oct 2019 - Feb 2020
Contributions:11 commits, 10 pushes, 1 branch in 3 months
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