[Nomination] Usamah Zaheer #179
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
Usamah Zaheer
Nominee Email
Nominee's GitHub or GitLab Handle
usamahz
(Optional) Organization / Affiliation
Arm
City, State/Province, Country
United Kingdom
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 am a PyTorch practitioner and advocate with extensive industry experience applying PyTorch in real-world robotics and AI systems.
My contributions include:
1. Building multi-task deep learning systems using PyTorch for floor stain detection, segmentation, and depth perception at Dyson, optimized for edge deployment on the Ambarella CV25.
2. Developing quantized and pruned PyTorch models for robotic hardware, leveraging techniques like knowledge distillation and TorchScript.
3. Mentoring over 10 engineers and interns in ML with PyTorch at Dyson.
4. Publishing detailed technical content and ML system designs that include PyTorch-powered inference pipelines, particularly in robotics and LLM applications.Any additional details you'd like to share?
As an Ambassador, I would:
1. Run practical PyTorch workshops and tutorials targeting robotics, edge AI, and LLM applications, especially for underrepresented or emerging communities.
2. Continue mentoring junior engineers in using PyTorch effectively for real-world deployment.
3. Share knowledge via blogs, GitHub repos, and live webinars that deconstruct complex ML systems and architectures using PyTorch.
4. Bridge the academic–industry gap by showing how PyTorch is applied in robotics, embedded systems, and enterprise-grade LLM tooling.
5. Represent PyTorch in conferences and community groups focusing on AI for hardware-constrained environments.