Scholar
Amitash Nanda
Google Scholar ID: 9wCusGMAAAAJ
University of California San Diego
Citations & Impact
Citations
23
H-index
3
i10-index
0
Publications
15
Co-authors
7
list available
Publications
Resume (English only)
Research Experience
- 2024: Graduate Student Researcher in the Load Balancing Team at the National Energy Research Scientific Computing Center (NERSC), Lawrence Berkeley National Laboratory (LBNL)
- 2025: Graduate Student Researcher in the Data and Analytics Team at NERSC, supervised by Steven Farrell, Kevin Gott, and Hannah Ross
- Worked as a Software Engineer in R&D at Accenture Research and Teradata US (Technology Innovation Office and Optimizer Development Team)
- Completed four quarters of full-time graduate internships in Machine Learning and Software Development Engineering in the U.S.
- Built end-to-end ML pipelines, developed algorithms, optimized models, and deployed large-scale machine learning systems
Background
- Third-year Ph.D. student in the Department of Electrical and Computer Engineering at the University of California San Diego (UCSD)
- Research interests: Distributed Machine Learning, Generative AI, Vision AI, DNN/LLM Optimization, AI/ML Systems, Bioinformatics
- Develops novel optimization techniques for deep neural networks (DNNs) and transformer-based models, focusing on efficient model architectures and scalable learning frameworks
- Works on quantization, pruning, and fine-tuning strategies to enhance efficiency and performance of vision and language models
- Explores distributed learning frameworks to address challenges in decentralized and dynamic data environments
- Integrates software and systems design with data science methodologies to build scalable AI solutions for real-world applications in bioinformatics, computer vision, and natural language processing
