Archiki Prasad
Graduate Research Assistant
Chapel Hill, North Carolina, United States
Summary
👤
Senior🎓
Top SchoolArchiki Prasad is a PhD student and applied ML researcher with eight years of experience bridging electrical engineering and machine learning, focused on time-series forecasting and end-to-end speech recognition. He has interned at top research labs (Adobe Research, AI2, Meta FAIR, Google DeepMind) and published work on accent effects in ASR at ACL and a cold-start forecasting method presented at WWW with an associated US patent filing. Comfortable moving between theory and engineering, he devised a novel Continuous Dynamic Key-Value Memory Network that considerably outperformed LSTM baselines for cold-start prediction. Based in Chapel Hill, he blends rigorous academic training from IIT Bombay with hands-on deployment experience and mentorship roles, making him adept at turning research insights into production-ready solutions.
8 years of coding experience
1 year of employment as a software developer
Indian Institute of Technology BombayJubilee Hills Public School, HyderabadSri Chaitanya Junior College, HyderabadDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of North Carolina at Chapel Hill
English, Hindi
Github Skills (54)
python10
residual-networks9
machine-learning9
tensorflow9
neural-network9
deep-learning9
sequence8
loss8
ctc8
deep-neural-networks8
ml8
facebook8
data-science8
speech7
noise7
Programming languages (3)
Github contributions (5)
SConsul/audio-source-separation
Oct 2018 - Nov 2018
Contributions:36 commits, 1 push in 1 month
archiki/Robust-E2E-ASR
Feb 2021 - Apr 2021
Contributions:46 commits, 41 pushes, 8 comments in 2 months
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