[Nomination] <Akilsurya Sivakumar> #211
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
Akilsurya Sivakumar
Nominee Email
Nominee's GitHub or GitLab Handle
AkilsuryaS
(Optional) Organization / Affiliation
No response
City, State/Province, Country
Scottsdale
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?
As a PyTorch Ambassador, my contributions would revolve around community engagement, education, and fostering innovation within the PyTorch ecosystem. Here’s how I plan to make an impact:
### 1. Community Engagement & Knowledge Sharing
- Content Creation:
- Write blogs, tutorials, and case studies** on PyTorch best practices, new features (e.g., `torch.compile`, PyTorch 2.x), and real-world ML applications.
- Create video tutorials (YouTube/social media) covering PyTorch fundamentals, debugging tips, and optimization techniques.
- Open-Source Contributions:
- Contribute to PyTorch documentation, fix issues, and develop small utility libraries to simplify workflows.
- Maintain a GitHub repository with PyTorch starter projects (e.g., LLM fine-tuning, dynamic quantization).
### 2. Hosting & Organizing Events
- Local Meetups & Workshops:
- Organize PyTorch study groups and hands-on coding sessions for beginners/intermediate users.
- Collaborate with universities and tech communities to host hackathons focused on PyTorch.
- Webinars & Live Demos:
- Conduct live coding sessions on advanced topics (e.g., custom autograd functions, deploying PyTorch models with ONNX).
- Invite industry experts to discuss PyTorch use cases in research and production.
### 3. Mentorship & Support
- Beginner-Friendly Guidance:
- Mentor newcomers via PyTorch forums, Discord, or Office Hours—helping debug models, optimize training loops, etc.
- Create a "PyTorch Roadmap" guide for different skill levels (from tensors to distributed training).
- Supporting Underrepresented Groups:
- Partner with organizations like **Women in ML & Data Science** to encourage diversity in PyTorch adoption.
### 4. Advocacy & Feedback Loop
- Promote PyTorch Adoption:
- Share PyTorch success stories (research/industry) via LinkedIn/Twitter to attract more users.
- Bridge Between Users & Devs:
- Gather community feedback and report pain points to PyTorch core teams (e.g., UX improvements, feature requests).
### 5. Long-Term Vision
- Build a local PyTorch user group to sustain engagement beyond the ambassadorship.
- Work toward **official certifications or workshops** recognized by PyTorch.
By combining education, hands-on support, and community-building**, I aim to make PyTorch more accessible and empower the next wave of ML practitioners.