Samyak Parajuli
Student at Scale
Berkeley, California, United States
Summary
👤
Senior🎓
Top SchoolSamyak Parajuli is a research-driven AI engineer and PhD candidate with nine years of hands-on experience building and deploying machine learning systems across industry and academia. Trained at UC Berkeley (BS + MS EECS/Data Science) and now pursuing doctoral work in AI, he has shipped research-infused solutions at Perplexity, Scale AI, and Microsoft while contributing to BAIRearch projects in hierarchical and multi-agent reinforcement learning and traffic smoothing. His internships span edge-efficient inference, context-aware neural throttling, and computer vision for SETI, highlighting an unusual blend of systems-level efficiency work and core algorithmic research. Comfortable moving ideas from paper to production, he has experience in attention and GAN-based UI code generation, compression-aware training regimes, and scalable devops for deep learning. Based in Berkeley, he pairs rigorous mathematical training with pragmatic engineering to tackle resource-constrained and multi-agent AI problems.
9 years of coding experience
7 years of employment as a software developer
Master's degree Electrical Engineering and Computer Science, Master's degree Electrical Engineering and Computer Science at University of California, BerkeleyDoctor of Philosophy - PhD Artificial Intelligence, Doctor of Philosophy - PhD Artificial Intelligence at The University of Texas at AustinHigh School, High School at East Brunswick High School
Github Skills (18)
visual-question-answering8
sequence5
prompt-tuning5
benchmark4
multimodal4
sumo4
prompt4
deep-learning3
sequence-to-sequence3
reinforcement-learning3
traffic3
pytorch3
machine-learning3
architectures2
deep-reinforcement-learning2
Programming languages (4)
Github contributions (5)
samp830/samp830.github.io
Nov 2020 - Jul 2024
Contributions:3 pushes, 1 branch in 3 years 8 months
samp830/StudyOrDie-ChromeExtension
Nov 2016 - Nov 2016
Contributions:9 commits, 8 pushes, 1 branch in 7 days
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