[Nomination] Naeem Khoshnevis #264
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
Naeem Khoshnevis
Nominee Email
Nominee's GitHub or GitLab Handle
naeemkh
(Optional) Organization / Affiliation
Harvard University (Kempner Institute)
City, State/Province, Country
Cambridge, MA, 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?
As a PyTorch Ambassador, I will focus on bridging the gap between cutting-edge research in NeuroAI and scalable engineering practices by activating and supporting the machine learning community at the Kempner Institute at Harvard, as well as at other leading universities in the Greater Boston area. This includes collaborations with affiliated neuroscience and AI labs, and broader engagement with institutions such as MIT, Northeastern, BU, and UMass, to foster a robust research-to-engineering pipeline grounded in PyTorch.
My contributions will include:
- Running hands-on workshops for research teams and undergraduates—particularly those transitioning from cognitive science, neuroscience, or psychology to deep learning. These workshops will focus on building PyTorch-based pipelines for modeling biological and artificial agents, including reinforcement learning setups, grid cell-inspired architectures, and transformer-based cognitive modeling.
- Launching a PyTorch training series for SLURM-based HPC AI clusters, designed for researchers using Harvard’s FASRC and similar academic computing environments. Topics will include PyTorch DDP, FSDP, mixed-precision training on A100/H100 GPUs, and profiling workflows—addressing a critical bottleneck in reproducible, large-scale experiments.
- Developing public infrastructure and tooling, including a GitHub-hosted HPC Handbook (already initiated), to help academic and research institutions adopt PyTorch for distributed training. These materials will directly support teams at Harvard, MIT, BU, Northeastern, and UMass.
- Contributing modular open-source components based on my current work developing artificial agents in simulated environments (e.g., PyTorch-based modules for memory, navigation, and sensory processing in reinforcement learning). These will be reusable, well-documented, and targeted at both research and education.
With over a decade of experience in HPC and numerical analysis, and more than five years in statistical modeling and machine learning using a range of established frameworks, I bring a systems-level understanding to AI development. As a Senior ML Research Engineer at the Kempner Institute, I work at the intersection of neuroscience and artificial intelligence, deeply embedded in real-world scientific workflows. My role gives me access to a broad spectrum of domain specialists—from cognitive scientists to systems engineers—enabling me to connect diverse communities and catalyze interdisciplinary collaboration around PyTorch. I see this ambassadorship as an opportunity to help establish PyTorch as the de facto standard for neuro-inspired AI at scale, not only as a modeling framework, but as a foundation for shared insight into the nature of intelligence itself.Any additional details you'd like to share?
- LinkedIn: https://www.linkedin.com/in/nkhshnvs/
- HPC Handbook: https://github.com/KempnerInstitute/kempner-computing-handbook (https://handbook.eng.kempnerinstitute.harvard.edu/intro.html)
- Github: https://github.com/Naeemkh