Ali Taghibakhshi
Deep Learning Algorithm at NVIDIA
Austin, Texas Metropolitan Area United States
Summary
🤩
Rockstar🎓
Top SchoolAli Taghibakhshi is a Deep Learning Algorithm Engineer at NVIDIA specializing in reinforcement learning, graph neural networks, and large-scale multimodal generative vision–language models. He holds a PhD in Scientific Machine Learning from UIUC (2023) with publications at NeurIPS and ICML and brings four years of industry experience bridging research and production. At John Deere he combined perception and deep Q-learning to automate navigation and precision planting, and during an NVIDIA internship he developed a hierarchical GNN with cross-attention that improved cross-device user matching by ~5% and was presented at a VP-level event. His mechanical engineering and math‑olympiad teaching background gives him a rare mix of systems-level intuition and theoretical rigor that informs both model design and applied deployments.
4 years of coding experience
2 years of employment as a software developer
Mathematical Olympiad, Mathematical Olympiad at Young Scholars ClubMaster of Science - MS, Mechanical Engineering, 3.97, Master of Science - MS, Mechanical Engineering, 3.97 at University of Illinois Urbana-ChampaignBachelor of Science (B.Sc.), Mechanical Engineering, 3.91/4, Bachelor of Science (B.Sc.), Mechanical Engineering, 3.91/4 at Sharif University of Technology
Persian, English
Github Skills (44)
speaker-diarization10
speech-to-text10
machine-translation10
language-model10
speech-synthesis10
deeplearning10
multimodal10
text-normalization10
large-language-models10
nmt10
deep-learning10
neural-networks10
generative-ai10
speaker-recognition10
asr10
Programming languages (2)
Github contributions (5)
compdyn/rl_grid_coarsen
May 2021 - Oct 2021
Contributions:13 commits, 16 pushes in 4 months
JRD971000/scale-mggnn
Jan 2023 - Feb 2023
Contributions:38 pushes, 6 branches in 29 days
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