[Nomination] Debashish Chakraborty #61
Description
Select one:
- I am nominating myself for the PyTorch Ambassador Program.
- I am nominating someone else to become a PyTorch Ambassador.
Please confirm that the nominee meets the following requirements:
- The nominee is 18 years of age or older.
- The nominee agrees to abide by the PyTorch Code of Conduct.
- The nominee agrees to comply with the Linux Foundation Antitrust Policy.
- The nominee meets at least one of the qualifications listed in the PyTorch Ambassador Program Requirements.
Nominee Name
Debashish Chakraborty
Nominee Email
Nominee's GitHub or GitLab Handle
debashishc
(Optional) Organization / Affiliation
Johns Hopkins University
City, State/Province, Country
Baltimore, Maryland, USA
Your Name
No response
Your Email (Optional)
No response
How has the nominee contributed to PyTorch?
- An active contributor to PyTorch repositories (e.g., commits, PRs, discussions).
- A speaker at PyTorch events or workshops.
- A PyTorch user group organizer or meetup host.
- A researcher or educator using PyTorch in academic work or training.
- An active leader in the PyTorch community with at least one year of experience in:
- Organizing events (virtual/in-person).
- Speaking at AI/ML conferences.
- Mentoring others in PyTorch.
- Creating technical content (e.g., blogs, videos, tutorials).
🏆 How Would the Nominee Contribute as an Ambassador?
I have been actively using PyTorch since 2018 as the foundation for my research and development work. As a Research Fellow at JHU's Center for Language and Speech Processing, I specialize in multimodal machine learning with a focus on dimensionality reduction techniques and efficient model implementations. My expertise spans the development of scalable ML systems for both academic research and practical applications. I think there is more I can give back to the community than I have taken in the last 7 years.
My technical strengths include optimizing multimodal model architectures with PyTorch, implementing hardware-aware compression techniques for ML models, and developing custom CUDA and Triton kernels to accelerate machine learning workloads. This is evidenced by my GitHub projects such as KernelHeim, which provides custom Triton and CUDA kernel functions designed specifically for PyTorch-based ML workloads. I am also an active CUDA Mode member and contribute to discussions on the forum as well.
I actively contribute to open-source PyTorch projects, including recent contributions to HuggingFace's nanoVLM, a minimalist Vision-Language Model implementation in pure PyTorch. I've also developed classification systems for distinguishing between human-written and machine-generated text, demonstrating my ability to leverage PyTorch's full ecosystem for creating end-to-end solutions. However, I would like to increase my footprint for contribution to the ecosystem.
As a PyTorch Ambassador, I plan to:
1. Foster a community focused on efficient ML implementations by hosting quarterly workshops on PyTorch performance optimization techniques, including model distillation, quantization, and hardware acceleration.
2. Create and share educational content focused on developing custom kernels and backends for PyTorch, making advanced optimization techniques more accessible to developers.
3. Build open-source repositories showcasing multimodal ML applications with a focus on practical, production-ready code that follows best practices.
4. Mentor students and professionals in applying PyTorch to multidisciplinary problems, particularly at the intersection of NLP, computer vision, and audio processing.
5. Contribute to discussions around PyTorch's continued evolution, particularly in areas of model efficiency, distributed training, and hardware-specific optimizations.
This ambassadorship will enable me to bridge my technical expertise with community engagement, helping others leverage PyTorch's capabilities while simultaneously deepening my own involvement in the global PyTorch ecosystem.