Archit Parnami
Graduate Research Assistant
Charlotte, North Carolina, United States
Summary
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Senior🎓
Top SchoolArchit Parnami is a PhD candidate and Graduate Research Assistant at UNC Charlotte with a decade of software and research experience focused on meta-learning and few-shot learning for data-scarce environments. He develops and evaluates state-of-the-art models across images, text, audio, and graph domains, and has applied deep learning to urban analytics, producing an automated traffic forecasting pipeline presented at KDD’s MUD3 workshop. Previously he built production ERP modules in C#/C++ and prototyped graph-embedding recommenders during a Siemens research internship, giving him a rare blend of applied engineering and rigorous research. Archit also has hands-on teaching and tooling experience—authoring autograders with Docker and Python while supporting computer vision and machine learning courses. His work emphasizes models that learn quickly from limited data and generalize across modalities, and he shares research insights publicly at metaml.org. Based in Charlotte, NC, he combines strong academic metrics with practical system-building and mentorship.
10 years of coding experience
3 years of employment as a software developer
Master’s Degree, Computer Science, 4.0, Master’s Degree, Computer Science, 4.0 at University of North Carolina at CharlotteBachelor of Technology - BTech, Computer Science, 3.6, Bachelor of Technology - BTech, Computer Science, 3.6 at Rajasthan Technical University
Github Skills (14)
keyword8
keyword-spotting7
mathematics6
rails6
python6
machine-learning5
service-management3
stacked2
bidirectional2
recurrent2
lstm1
nlp1
deep-learning1
neural-network1
Programming languages (2)
Github contributions (5)
ArchitParnami/Few-Shot-KWS
Oct 2019 - Jul 2020
Few-Shot Keyword Spotting
Contributions:51 commits, 2 pushes, 3 comments in 9 months
pythonkeywordfew-shotkeyword-spotting
ArchitParnami/Transportation-Cost-Optimizer
Dec 2015 - Aug 2019
Contributions:5 commits, 4 pushes, 1 branch in 3 years 9 months
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