Conferences / PyTorch Conference
PyTorch Conference 2025
Oct 22–23, 2025 · Moscone West, San Francisco, CA, United States
- Conference
- PyTorch Conference Data science & ML
- Dates
- Oct 22, 2025 – Oct 23, 2025
- Venue
- Moscone West
- Place
- San Francisco, CA, United States
- Format
- In person
- Status
- Past
- Attendance
- 3,432LF post-event report: '3,432 attendees registered'.
- Website
- events.linuxfoundation.org
- Recorded
- 54 sponsors · 388 speaker appearances
- Notes
- Co-located events on 21 Oct (part of Open Source AI Week). Main-conference Sched programme (22-23 Oct) recorded in full, ~131 sessions excluding breaks and 21 Oct co-located events; affiliations as shown on Sched.
Ticket prices
| Ticket | Price | Valid until | Notes | Source |
|---|---|---|---|---|
| Attendee (super early bird) | $499 | Mar 21, 2025 | events.linuxfoundation.org | |
| Attendee (early bird) | $599 | Aug 6, 2025 | events.linuxfoundation.org | |
| Attendee (standard) | $799 | Sep 12, 2025 | events.linuxfoundation.org | |
| Attendee (late) | $999 | Oct 23, 2025 | events.linuxfoundation.org | |
| Academic | $249 | — | Same price in all periods; proof of academic ID required. | events.linuxfoundation.org |
Sponsors 54
Platinum 12
Gold 11
Silver 11
Startup 10
- dstack · Startup + Non-Profit + VC
- FriendliAI · Startup + Non-Profit + VC
- LMCache Tensormesh · Startup + Non-Profit + VC
- Perforated · Startup + Non-Profit + VC
- Portex AI · Startup + Non-Profit + VC
- Runhouse · Startup + Non-Profit + VC
- Thesys · Startup + Non-Profit + VC
- Tigris Data · Startup + Non-Profit + VC
- Velda · Startup + Non-Profit + VC
- WoolyAI · Startup + Non-Profit + VC
Speakers and talks 388
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Adam Jones | Anthropic | Keynote | Keynote Panel Discussion: Agentic AI | — |
| Alban Desmaison | Meta | Keynote | Keynote: PyTorch Technical Deep Dive | — |
| Andrew Ling | Groq | Keynote | Keynote: Enabling PyTorch’s Thousand Ops for Software First Silicon Design | — |
| Animashree Anandkumar | California Institute of Technology | Keynote | Keynote: Foundations for AI+Science | — |
| Anna Tong | FORBES | Keynote | Keynote: Jeremy Howard, Founding Researcher at fast.ai in Conversation with Anna Tong, Reporter, Forbes | — |
| Anush Elangovan | AMD | Keynote | Sponsor Keynote: Build AI Anywhere with ROCm™ Software: AMD and PyTorch Bring Cloud-to-Client Power to Developers | — |
| Aparna Dhinakaran | Arize AI | Keynote | Keynote Panel Discussion: Agentic AI | — |
| Ben Lorica | Gradient Flow | Keynote | Keynote Panel Discussion: Agentic AI | — |
| Brian Zhan | Something New | Keynote | Keynote Panel Discussion: Signal vs. Noise: Betting on AI’s Next Wave | — |
| Dawn Song | UC Berkeley | Keynote | Keynote: Towards Building Safe and Secure Agentic AI | — |
| Dr. Christian Jacobi | IBM | Keynote | Sponsored Keynote: From Transactions to Transformers: Hardware Built for Enterprise AI | — |
| Dylan Patel | SemiAnalysis | Keynote | Keynote Panel Discussion: Hardwares & Accelerators | — |
| Edward Yang | Meta | Keynote | Keynote: PyTorch Technical Deep Dive | — |
| Eli Uriegas | Meta | Keynote | Keynote: Recognizing the PyTorch Foundation CICD Infrastructure Community | — |
| Eric P. Xing | Mohamed bin Zayed University of Artificial Intelligence | Keynote | Keynote: An OPEN Path to Super Intelligence | — |
| Ion Stoica | UC Berkeley | Keynote | Keynote: Ray: A Distributed Compute Engine for AI | — |
| Jeff Gehlhaar | Qualcomm | Keynote | Sponsored Keynote: Unlocking AI at Scale for PyTorch Developers | — |
| Jeremy Howard | fast.ai | Keynote | Keynote: Jeremy Howard, Founding Researcher at fast.ai in Conversation with Anna Tong, Reporter, Forbes | — |
| Jerry Liu | LlamaIndex | Keynote | Keynote Panel Discussion: Agentic AI | — |
| Jim Fan | NVIDIA | Keynote | Keynote: The Physical Turing Test: Solving General Purpose Robotics | — |
| Joe Spisak | Reflection AI | Keynote | Keynote: Welcome Back | — |
| Joe Spisak | Reflection AI | Keynote | Keynote Panel Discussion: Signal vs. Noise: Betting on AI’s Next Wave | — |
| Joe Spisak | Reflection AI | Keynote | Keynote: Joe Spisak, Product Director, Meta & Lysandre Debut, Chief Open Source Officer, Hugging Face | — |
| Lysandre Debut | Hugging Face | Keynote | Keynote: Joe Spisak, Product Director, Meta & Lysandre Debut, Chief Open Source Officer, Hugging Face | — |
| Mark Saroufim | GPU Mode | Keynote | Keynote: PyTorch Technical Deep Dive | — |
| Mark Saroufim | GPU Mode | Keynote | Keynote Panel Discussion: Hardwares & Accelerators | — |
| Matt White | The Linux Foundation | Keynote | Keynote: Welcome & Opening Remarks | — |
| Matt White | The Linux Foundation | Keynote | Keynote: Closing Remarks | — |
| Matt White | The Linux Foundation | Keynote | Keynote: Welcome Back | — |
| Matt White | The Linux Foundation | Keynote | Keynote: Welcome Back | — |
| Nathan Lambert | Ai2 | Keynote | Keynote: Olmo-Thinking: Training a Fully Open Reasoning Model | — |
| Nitin Perumbeti | Crusoe | Keynote | Keynote Panel Discussion: Hardwares & Accelerators | — |
| Olatunji Ruwase | Snowflake | Keynote | Keynote: vLLM & Deepspeed Updates | — |
| Peng Wu | Meta | Keynote | Keynote: PyTorch Technical Deep Dive | — |
| Percy Liang | Stanford University | Keynote | Keynote: Marin: An Open Lab for Frontier AI | — |
| Peter Deng | Felicis | Keynote | Keynote Panel Discussion: Signal vs. Noise: Betting on AI’s Next Wave | — |
| Peter Salanki | CoreWeave | Keynote | Keynote Panel Discussion: Hardwares & Accelerators | — |
| Robert Nishihara | Anyscale | Keynote | Keynote: Ray: A Distributed Compute Engine for AI | — |
| Samuel Colvin | Pydantic | Keynote | Keynote Panel Discussion: Agentic AI | — |
| Sarah Catanzaro | Amplify Partners | Keynote | Keynote Panel Discussion: Signal vs. Noise: Betting on AI’s Next Wave | — |
| Sarah Guo | Conviction | Keynote | Keynote Panel Discussion: Signal vs. Noise: Betting on AI’s Next Wave | — |
| Sergey Levine | UC Berkeley | Keynote | Keynote: Robot Foundation Models | — |
| Sharon Zhou | AMD | Keynote | Keynote Panel Discussion: Hardwares & Accelerators | — |
| Simon Mo | vLLM | Keynote | Keynote: vLLM & Deepspeed Updates | — |
| Abhishek Gaikwad | NVIDIA | Poster | Poster Presentations: Industry & Infrastructure | — |
| Abhishek Jain | Fujitsu Research of India Pvt. Ltd | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Adam Stewart | Technical University of Munich | Poster | Poster Presentations: Ecosystem & Performance | — |
| Adam Zhao | Amazon Web Services | Speaker | Sponsored Session: Accelerating GenAI Inference: From AWS Deep Learning Containers to Scaling Amazon Rufus on Trainium | — |
| Adeem Jassani | AMD | Poster | Poster Presentations: Ecosystem & Performance | — |
| Ahmad Sharif | Meta | Poster | Poster Presentations: Industry & Infrastructure | — |
| Alban Desmaison | Meta | Speaker | Meet the Developers of PyTorch Module Maintainers | — |
| Albin Joy | Intel | Poster | Poster Presentations: Generative & Large Models | — |
| Aleksandr Malyshev | AMD | Speaker | Enabling VLLM V1 on AMD GPUs With Triton | — |
| Allen Miyazawa | Meta | Poster | Poster Presentations: Industry & Infrastructure | — |
| Allen Wang | Meta | Speaker | PyTorch-Native Stack for Agents | — |
| Alon Yariv | Crusoe | Speaker | Sponsored Session: Beyond the Node: Scaling Inference with Cluster-Wide KVCache Management | — |
| Amal Joe R S | IIT Bombay & BharatGen | Poster | Poster Presentations: Generative & Large Models | — |
| Amit Rustagi | DeeplearningAPI | Poster | Poster Presentations: Applied AI | — |
| Andrea Frittoli | IBM | Speaker | Meet the Developers of PyTorch Dev Infra | — |
| Andrea Frittoli | IBM | Poster | Poster Presentations: Responsible AI & Community | — |
| Andrew Or | Meta | Poster | Poster Presentations: Generative & Large Models | — |
| Andrey Talman | Meta | Speaker | Meet the Developers of PyTorch Dev Infra | — |
| Andy Lugo | AMD | Lightning talk | Lightning Talk: Improved GEMM and SDPA Performance on ROCm With Composable Kernel | — |
| Angela Yi | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Angela Yi | Meta | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Angela Yi | Meta | Poster | Poster Presentations: Generative & Large Models | — |
| Animesh Jain | Meta | Poster | Poster Presentations: Compilers & Kernels | — |
| Animesh Jain | Meta | Speaker | Meet the Developers of PyTorch Compiler and Helion | — |
| Anita Katahoire | Meta | Speaker | Meet the Developers of PyTorch Dev Infra | — |
| Ankita George | Meta | Poster | Poster Presentations: Industry & Infrastructure | — |
| Apurva Jain | Meta | Poster | Poster Presentations: Generative & Large Models | — |
| Arjun Upadhyay | Oracle | Lightning talk | Sponsored Session: Lightning Talk: Build and Deploy AI Flows with an Agent Factory | — |
| Armen Donigian | Meta | Speaker | Meet the Developers of PyTorch Dev Infra | — |
| Arnold Pereira | Meta | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Aroma Rodrigues | Independent | Poster | Poster Presentations: Applied AI | — |
| Arthur Zucker | Hugging Face | Speaker | Transformers: Standardizing Model Definitions Across the PyTorch Ecosystem | — |
| Ashok Emani | Intel | Lightning talk | Lightning Talk: Challenges and Standardization in PyTorch Ecosystem Accelerators | — |
| Ashok Emani | Intel | Poster | Poster Presentations: Industry & Infrastructure | — |
| Ashvant Ram Selvam | MathWorks | Speaker | Bridging the Gap: Embedded Deployment of PyTorch Deep Learning Models in Complex Engineered Systems | — |
| Aurick Qiao | Snowflake | Speaker | Sponsored Session: Arctic Inference: Breaking the Speed-Cost Tradeoff in LLM Serving | — |
| Avik Chaudhuri | Meta | Speaker | Meet the Developers of PyTorch Compiler and Helion | — |
| Avik Chaudhuri | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Benjamin Consolvo | AMD | Poster | Poster Presentations: Applied AI | — |
| Bhavya Shah | Apple | Poster | Poster Presentations: Generative & Large Models | — |
| Bin Bao | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Bin Bao | Meta | Speaker | Meet the Developers of PyTorch Compiler and Helion | — |
| Bob Ren | Meta | Lightning talk | Lightning Talk: Dynamic Shape Recompilations | — |
| Bowen Peng | Nous Research | Speaker | Rethinking the Transformer: Toward Native Multimodal Architectures | — |
| Boyu Wang | TrueFoundry | Poster | Poster Presentations: Industry & Infrastructure | — |
| Boyuan Feng | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Boyuan Feng | Meta | Lightning talk | Lightning Talk: Flex Attention for Inference | — |
| Brian Hirsh | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Brittany Rockwell | Speaker | Sponsored Session: Everything Everywhere all at Once: vLLM Hardware Optionality with Spotify and Google | — | |
| Burkhard Ringlein | IBM | Lightning talk | Lightning Talk: Vllm-triton-backend: How To Get State-of-the-art Performance on NVIDIA and AMD With Just Triton | — |
| Can Balioglu | Meta | Poster | Poster Presentations: Generative & Large Models | — |
| Carlos Costa | IBM | Poster | Poster Presentations: Generative & Large Models | — |
| Cemal Bilgin | Meta | Speaker | ExecuTorch 1.0: General Availability Status for Mobile and Embedded Application Developers | — |
| Chen Lai | Metea | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Chenyang Zhao | LMSYS Org | Speaker | Optimizing Long-Tail and MoE Challenges in Reinforcement Learning with SGLang | — |
| Chia-Wei Chen | Speaker | Fault Tolerance Training at Pinterest | — | |
| Chien-Chin Huang | Meta | Speaker | PyTorch Symmetric Memory: A New Programming Paradigm for Distributed AI | — |
| Chien-Chin Huang | Meta | Lightning talk | Lightning Talk: FlexCP: FlexAttention for Long Sequence Training Using Context Parallel | — |
| Chip Huyen | Tep Studio | Speaker | Coding with AI | — |
| Christian Cania | TrueFoundry | Poster | Poster Presentations: Industry & Infrastructure | — |
| Christopher Nuland | Red Hat | Poster | Poster Presentations: Industry & Infrastructure | — |
| Chuin Wei Tan | Harvard University | Poster | Poster Presentations: Industry & Infrastructure | — |
| chunlei men | Beijing Academy of Artificial Intelligence aka Zhiyuan Institute | Poster | Poster Presentations: Compilers & Kernels | — |
| Colin Taylor | Meta | Speaker | Monarch: A Distributed Execution Engine for PyTorch | — |
| Cong Liu | Poster | Poster Presentations: Generative & Large Models | — | |
| Cong Liu | Speaker | Serving PyTorch LLMs at Scale: Disaggregated Inference With Kubernetes and Llm-d | — | |
| Corey Lowman | Staff Machine Learning Engineer | Speaker | Sponsored Session: Distributed Training in PyTorch: Zero to Hero | — |
| Cory Ye | NVIDIA | Speaker | Enabling Lightweight, High-Performance FSDP With NVIDIA GPU | — |
| Daniel Brooks | Statistical Drafting | Poster | Poster Presentations: Applied AI | — |
| Daniel Flores | Meta | Poster | Poster Presentations: Ecosystem & Performance | — |
| Daniel Han | Unsloth | Speaker | Maximizing Luck in Reinforcement Learning | — |
| Daniel Han | Unsloth | Poster | Poster Presentations: Generative & Large Models | — |
| Daniel Haziza | Meta | Poster | Poster Presentations: Generative & Large Models | — |
| Daniel Vega-Myhre | Meta | Speaker | PyTorch APIs for High Performance MoE Training and Inference | — |
| David Pitt | Ultra | Poster | Poster Presentations: Industry & Infrastructure | — |
| Davide Testuggine | Meta | Speaker | PyTorch-Native Stack for Agents | — |
| Devang Choudhary | Fujitsu Research of India Pvt. Ltd | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Digant Desai | Meta | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Driss Guessous | Meta | Speaker | mxfp8, mxfp4, nvfp4 formats and applications in PyTorch | — |
| Driss Guessous | Meta | Lightning talk | Lightning Talk: Flex Attention for Inference | — |
| E cao | Intel | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Eikan Wang | Intel | Poster | Poster Presentations: Generative & Large Models | — |
| Eikan Wang | Intel | Speaker | Sponsored Session: Empowering AI Everywhere: Democratizing PyTorch with Intel AIPCs & More | — |
| Eikan Wang | Intel | Poster | Poster Presentations: PyTorch Core | — |
| Eikan Wang | Intel | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Eli Uriegas | Meta | Lightning talk | Lightning Talk: Hardware-Aware Python Packages ~ PyTorch and WheelNext Grab the Wheel! | — |
| Eli Uriegas | Meta | Speaker | Meet the Developers of PyTorch Dev Infra | — |
| Elias Ellison | Meta | Speaker | Meet the Developers of PyTorch Compiler and Helion | — |
| Elias Ellison | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Elizabeth Santorella | Meta | Poster | Poster Presentations: Compilers & Kernels | — |
| Emma Lin | Meta | Poster | Poster Presentations: Industry & Infrastructure | — |
| Fan Zhao | Intel | Speaker | Sponsored Session: Empowering AI Everywhere: Democratizing PyTorch with Intel AIPCs & More | — |
| Faran Ahmad | Meta | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Farshid Mahdavi | Prancer | Poster | Poster Presentations: Applied AI | — |
| Fatih E. Nar | Red Hat | Poster | Poster Presentations: Applied AI | — |
| Fengchun Hua | Ltd | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Fengchun Hua | Ltd | Lightning talk | Sponsored Session: Lightning Talk: PyTorch in Production: Boosting LLM Training and Inferencing on Ascend NPU | — |
| Francisco Massa | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Ganesh Gopalakrishnan | University of Utah | Poster | Poster Presentations: Ecosystem & Performance | — |
| Garrett Goon | IBM | Speaker | Our Journey With TorchTitan | — |
| Gary O'Neall | Source Auditor Inc | Speaker | SPDX: Tackling System Risk in Modern Supply Chains | — |
| George Gekov | Arm | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| George Williams | Ansible AI | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Gerson Kroiz | Lightning talk | Lightning Talk: In-Cluster Distributed Checkpointing: Optimizing Training Goodput Through GPU Node Locality | — | |
| Gian Marco Iodice | Arm | Speaker | Deploying GenAI for Audio Generation on Mobile CPUs With ExecuTorch | — |
| Greg Lindahl | Common Crawl Foundation | Speaker | Addressing the Challenges of Public Web Data | — |
| Greg Osuri | Akash Network | Speaker | Sponsored Session: Powering PyTorch: Decentralized Training for an Energy-Hungry Future | — |
| Guilherme Leobas | OpenTeams | Poster | Poster Presentations: PyTorch Core | — |
| Han Qi | Poster | Poster Presentations: Compilers & Kernels | — | |
| Harry Kim | NVIDIA | Speaker | Sponsored Session: Amazingly Fast and Incredibly Scalable Inference with NVIDIA's Dynamo and TensorRT-LLM | — |
| Harvey Dam | University of Utah | Poster | Poster Presentations: Ecosystem & Performance | — |
| Henry Tsang | Meta | Speaker | Generating State-of-the-Art GEMMs for Heterogeneous Hardware with TorchInductor | — |
| Henry Tsang | Meta | Poster | Poster Presentations: Generative & Large Models | — |
| Hong-Seok Kim | Rebellions | Lightning talk | Sponsored Session: Lightning Talk: PyTorch and Democratization of AI Accelerators | — |
| Hongpeng Guo | ByteDance Seed | Speaker | Verl: A Flexible and Efficient RL Framework for LLMs | — |
| Howard Huang | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Huy Do | Meta | Poster | Poster Presentations: Ecosystem & Performance | — |
| Ilina Mitra | Meta | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Isaac Corley | Wherobots | Poster | Poster Presentations: Ecosystem & Performance | — |
| Jacob Murel | Princeton University | Poster | Poster Presentations: Industry & Infrastructure | — |
| Jane Xu | Meta | Speaker | Meet the Developers of PyTorch Module Maintainers | — |
| Jane Xu | Meta | Lightning talk | Lightning Talk: A Stable Limited LibTorch ABI? How?! (and Why?) | — |
| Jannik Malte Meissner | Neuralfinity | Poster | Poster Presentations: Applied AI | — |
| Jared US | NVIDIA | Speaker | The Future Is Tiled: Using CuTile and TileIR To Write Portable, High-performance GPU Kernels | — |
| Jason Ansel | Meta | Speaker | Meet the Developers of PyTorch Compiler and Helion | — |
| Jason Ansel | Meta | Speaker | Helion: A High-level DSL for Kernel Authoring | — |
| Jay Dawani | Lemurian Labs | Lightning talk | Sponsored Session: Lightning Talk: Accelerated Software for a Post-Moore World | — |
| Jean Kossaifi | NVIDIA | Poster | Poster Presentations: Industry & Infrastructure | — |
| Jean Kossaifi | NVIDIA | Poster | Poster Presentations: Ecosystem & Performance | — |
| Jeff Diecks | OpenSSF | Speaker | Birds of a Feather: Applying DevSecOps Lessons to MLSecOps | — |
| Jeffrey Wan | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Jeffrey Wan | Meta | Speaker | Meet the Developers of PyTorch Module Maintainers | — |
| Jerry Zhang | Meta | Poster | Poster Presentations: Generative & Large Models | — |
| Jevin Jiang | Poster | Poster Presentations: Compilers & Kernels | — | |
| Jewon Im | Yale University | Poster | Poster Presentations: Industry & Infrastructure | — |
| Jiahao Wu | Meta | Poster | Poster Presentations: Industry & Infrastructure | — |
| Jianan Gu | Intel | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Jianbin Chang | NVIDIA | Speaker | Enabling Lightweight, High-Performance FSDP With NVIDIA GPU | — |
| Jiani Wang | Meta | Lightning talk | Lightning Talk: Unlock the Future of Generative AI: TorchTitan's Latest Breakthroughs | — |
| Jiannan Wang | Meta | Speaker | Unlocking Performance: Harnessing LLMs To Streamline GPU Kernel Development in PyTorch | — |
| Jiawei Li | Huawei | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Jie-Si Yang | University of Utah | Poster | Poster Presentations: Ecosystem & Performance | — |
| Jimmy Ahlberg | Ericsson | Speaker | Behind Every AI SBOM Lies a Minefield: Here's How to Not Step On it | — |
| Jing Li | Huawei | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Joel Schlosser | Meta | Poster | Poster Presentations: Generative & Large Models | — |
| Jonathan DEKHTIAR | NVIDIA | Lightning talk | Lightning Talk: Hardware-Aware Python Packages ~ PyTorch and WheelNext Grab the Wheel! | — |
| Jongsok Choi | Meta | Speaker | Meet the Developers of PyTorch Compiler and Helion | — |
| Jordan Conway | The Linux Foundation | Speaker | Meet the Developers of PyTorch Dev Infra | — |
| Juechu Dong | Meta | Poster | Poster Presentations: Compilers & Kernels | — |
| Junchen Jiang | University of Chicago | Speaker | Scaling KV Caches for LLMs: How LMCache + NIXL Handle Network and Storage Heterogeneity | — |
| Junjie Wang | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Junpu Fan | Amazon Web Services | Poster | Poster Presentations: Industry & Infrastructure | — |
| Justin Chu | Microsoft | Lightning talk | Lightning Talk: What's New in Torch.onnx | — |
| Kapil Poreddy | Walmart | Poster | Poster Presentations: Applied AI | — |
| Karthik Anantha Padmanabhan | Speaker | Fault Tolerance Training at Pinterest | — | |
| Kate Stewart | The Linux Foundation | Speaker | SPDX: Tackling System Risk in Modern Supply Chains | — |
| Kausik Maiti | Intel | Poster | Poster Presentations: Generative & Large Models | — |
| Kaustubh Vartak | Meta | Poster | Poster Presentations: Industry & Infrastructure | — |
| Ke Wen | Meta | Speaker | PyTorch APIs for High Performance MoE Training and Inference | — |
| Ke Wen | Meta | Speaker | PyTorch Symmetric Memory: A New Programming Paradigm for Distributed AI | — |
| Keith Bergelt | Open Invention Network | Poster | Poster Presentations: Applied AI | — |
| Kimish Patel | Meta | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Kousik Rajesh | Speaker | Scaling Inference of O(10K)-length Sequence Recommendation Models Using CudaGraph and Triton Kernels | — | |
| Kris Gao | EA | Poster | Poster Presentations: Industry & Infrastructure | — |
| Krutarth Bhatt | Amazon Web Services | Poster | Poster Presentations: Generative & Large Models | — |
| Lahari Chowtoori | Amazon Web Services | Poster | Poster Presentations: Responsible AI & Community | — |
| Laikh Tewari | NVIDIA | Speaker | Sponsored Session: Amazingly Fast and Incredibly Scalable Inference with NVIDIA's Dynamo and TensorRT-LLM | — |
| Laith Sakka | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Liangfu Chen | Amazon Web Services | Speaker | Multi-Accelerator PyTorch Serving With NxD Inference and vLLM | — |
| Lin Sun | Solo.io | Lightning talk | Sponsored Session: Lightning Talk: Efficient Inference Serving with Kubernetes Gateway API Inference Extension | — |
| Linsong Chu | IBM | Speaker | Our Journey With TorchTitan | — |
| Liz Li | AMD | Speaker | Efficient MoE Pre-training at Scale on AMD GPUs With TorchTitan | — |
| Luca Antiga | Lightning AI | Lightning talk | Thunder: Distribute and Optimize Your PyTorch Models With Zero Code Changes | — |
| Luca Antiga | Lightning AI | Lightning talk | Sponsored Session: Lightning Talk: Accelerating Experimentation and Unlocking Real-Time Inference on Microcontrollers with Lightning | — |
| Lucas Pasqualin | PyTorch | Poster | Poster Presentations: Industry & Infrastructure | — |
| Lucy Qiu | Meta | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Luis Preciado Bayardo | Poster | Poster Presentations: Edge & Hardware Acceleration | — | |
| Lysandre Debut | Hugging Face | Speaker | Transformers: Standardizing Model Definitions Across the PyTorch Ecosystem | — |
| Maanav Dalal | Microsoft | Lightning talk | Lightning Talk: What's New in Torch.onnx | — |
| Manish Kumar Thota | S&P Global | Poster | Poster Presentations: Industry & Infrastructure | — |
| Manuel Candales | Meta | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Manvi Gupta | Adobe | Poster | Poster Presentations: Industry & Infrastructure | — |
| Mark Saroufim | GPU Mode | Lightning talk | Lightning Talk: KernelBot: The World's First Competitive GPU Programming Platform | — |
| Maroon Ayoub | IBM | Poster | Poster Presentations: Generative & Large Models | — |
| Maroon Ayoub | IBM | Speaker | Serving PyTorch LLMs at Scale: Disaggregated Inference With Kubernetes and Llm-d | — |
| Masahiro Hiramori | Mitsubishi Electric Corporation | Poster | Poster Presentations: Compilers & Kernels | — |
| Matt Archer | University of Michigan | Lightning talk | Lightning Talk: FTorch: A Library To Couple PyTorch ML Models With Fortran Climate Models | — |
| Matthew Crawford | Arm | Speaker | Behind Every AI SBOM Lies a Minefield: Here's How to Not Step On it | — |
| Matthew US | NVIDIA | Poster | Poster Presentations: Compilers & Kernels | — |
| Matthias Cremon | Meta | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Matthias Reso | Meta | Speaker | Efficient MoE Pre-training at Scale on AMD GPUs With TorchTitan | — |
| Mayank Kumar | DeepTempo | Poster | Poster Presentations: Generative & Large Models | — |
| Mehant Kammakomati | IBM | Poster | Poster Presentations: Generative & Large Models | — |
| Mengwei Liu | Meta | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Mergen Nachin | Meta | Speaker | ExecuTorch 1.0: General Availability Status for Mobile and Embedded Application Developers | — |
| Mert Toslali | IBM | Speaker | No GPU Left Behind: Scaling Online LLM Training With Co-located VLLM in TRL | — |
| Miaolai Zhou | Amazon Web Services | Poster | Poster Presentations: Responsible AI & Community | — |
| Michael Goin | Red Hat | Speaker | Meet the vLLM Maintainers | — |
| Michael Lazos | Meta | Speaker | Generating State-of-the-Art GEMMs for Heterogeneous Hardware with TorchInductor | — |
| Mihai Maruseac | OpenAI | Speaker | From Model To Trust: Building Upon Tamper-proof ML Metadata Records | — |
| Mihai Maruseac | OpenAI | Poster | Poster Presentations: Responsible AI & Community | — |
| Mikayla Gawarecki | Meta | Speaker | Meet the Developers of PyTorch Module Maintainers | — |
| Milos Puzovic | Arm | Poster | Poster Presentations: Compilers & Kernels | — |
| Mit Kotak | Massachusetts Institute of Technology | Poster | Poster Presentations: Industry & Infrastructure | — |
| Moein Khazraee | NVIDIA | Speaker | Scaling KV Caches for LLMs: How LMCache + NIXL Handle Network and Storage Heterogeneity | — |
| Muna Nwaiwu | Cornell University | Poster | Poster Presentations: Industry & Infrastructure | — |
| N Maajid Khan | Fujitsu Research of India Pvt. Ltd | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Nader Al Awar | NVIDIA | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Nariaki Tateiwa | Inc | Lightning talk | Lightning Talk: Accelerating PyTorch FSDP Via Overlapping Collectives With In-Network Computing and Multicast | — |
| Natalia Gimelshein | Meta | Speaker | PyTorch APIs for High Performance MoE Training and Inference | — |
| Nathan Lambert | Ai2 | Speaker | Mapping the Open Model Landscape in 2025 | — |
| Ngoc Bao Han Nguyen | Amazon Web Services | Poster | Poster Presentations: Generative & Large Models | — |
| Niall Lyons | Infineon Technologies | Lightning talk | Sponsored Session: Lightning Talk: Accelerating Experimentation and Unlocking Real-Time Inference on Microcontrollers with Lightning | — |
| Nick Terrell | Meta | Lightning talk | Lightning Talk: Model Checkpoint Compression With OpenZL | — |
| Nicolas Hug | Meta | Poster | Poster Presentations: Ecosystem & Performance | — |
| Niels Bantilan | Union.ai | Speaker | Designing and Building Custom Reinforcement Learning Environments for Fine-tuning LLMs | — |
| Nikhil Gupta | TensorWave | Poster | Poster Presentations: Compilers & Kernels | — |
| Nikita Shulga | Meta | Speaker | Meet the Developers of PyTorch Dev Infra | — |
| Nikita Shulga | Meta | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Nishank Chandawala | NVIDIA | Poster | Poster Presentations: Compilers & Kernels | — |
| Noah Flynn | Amazon Web Services | Poster | Poster Presentations: Applied AI | — |
| Oguz Ulgen | Meta | Speaker | Meet the Developers of PyTorch Compiler and Helion | — |
| Olatunji Ruwase | Snowflake | Speaker | DeepSpeed: Efficient Training Scalability for Deep Learning | — |
| Panagiotis Kourdis | Intel | Poster | Poster Presentations: Industry & Infrastructure | — |
| Pankaj Gupta | Baseten | Speaker | Sponsor Session: Low-Precision Inference without Quality Loss: Selective Quantization and Microscaling | — |
| Parichay Das | LTM | Speaker | Birds of a Feather: Deploying LLMs at the Edge: Lessons from the Field | — |
| Patric Zhao | Intel | Poster | Poster Presentations: PyTorch Core | — |
| Pauline Sho | Poster | Poster Presentations: Edge & Hardware Acceleration | — | |
| Peter St. John | NVIDIA | Poster | Poster Presentations: Generative & Large Models | — |
| Phi Nguyen | Amazon Web Services | Speaker | Sponsored Session: Accelerating GenAI Inference: From AWS Deep Learning Containers to Scaling Amazon Rufus on Trainium | — |
| Philip Bontrager | Meta | Speaker | Lifecycle of a Parameter | — |
| Philip Kiely | Baseten | Speaker | Sponsor Session: Low-Precision Inference without Quality Loss: Selective Quantization and Microscaling | — |
| Piotr Żelasko | NVIDIA | Poster | Poster Presentations: Industry & Infrastructure | — |
| Puxuan Yu | Snowflake | Poster | Poster Presentations: Generative & Large Models | — |
| Rachel Guo | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Rahul Vishwakarma | WorkOnward | Poster | Poster Presentations: Industry & Infrastructure | — |
| Rajesh Arsid | Synopsys | Poster | Poster Presentations: Industry & Infrastructure | — |
| Ranganath Selagamsetty | University of Wisconsin-Madison | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Richard Zou | Meta | Speaker | Blazing Fast GenAI Inference With Torch.compile | — |
| Richard Zou | Meta | Speaker | Meet the Developers of PyTorch Compiler and Helion | — |
| Rishit Dagli | NVIDIA | Lightning talk | Lightning Talk: But How Do You Autograd Through Your Simulator? Making a Differentiable Simulator in PyTorch | — |
| Robert Nishihara | Anyscale | Speaker | An Open Source Post-Training Stack: Kubernetes + Ray + PyTorch + vLLM | — |
| Robert Shaw | — | Speaker | Meet the vLLM Maintainers | — |
| Rodrigo Silva Ferreira | Posit | Poster | Poster Presentations: Applied AI | — |
| Roy Allela | Amazon Web Services | Poster | Poster Presentations: Industry & Infrastructure | — |
| Ruben Rodriguez Buchillon | Meta | Poster | Poster Presentations: Compilers & Kernels | — |
| Sahdev P. Zala | IBM | Poster | Poster Presentations: PyTorch Core | — |
| Sangkug Lym | NVIDIA | Speaker | Enabling Lightweight, High-Performance FSDP With NVIDIA GPU | — |
| Sanjana Kamath | Intel | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Sarah Kaiser | Microsoft | Speaker | Sponsored Session: Fine Tune Your AI Toolbox with GitHub Copilot, Azure AI Foundry, & MCP | — |
| Sarah Mohamed | MathWorks | Speaker | Bridging the Gap: Embedded Deployment of PyTorch Deep Learning Models in Complex Engineered Systems | — |
| Satya Chivatam | Amazon Web Services | Poster | Poster Presentations: Generative & Large Models | — |
| Saurabh Mishra | Meta | Lightning talk | Lightning Talk: In-Cluster Distributed Checkpointing: Optimizing Training Goodput Through GPU Node Locality | — |
| Saurabh Mishra | Meta | Poster | Poster Presentations: Industry & Infrastructure | — |
| Saurabh Vishwas Joshi | Speaker | Scaling Inference of O(10K)-length Sequence Recommendation Models Using CudaGraph and Triton Kernels | — | |
| Scott Wolchok | Meta | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Sebastian Raschka | RAIR Lab | Speaker | The Building Blocks of Today’s and Tomorrow’s Language Models | — |
| Serge Panev | NVIDIA | Poster | Poster Presentations: Generative & Large Models | — |
| Shane Slattery | Embecosm | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Shangdi Yu | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Shantanu Tripathi | Amazon Web Services | Poster | Poster Presentations: Industry & Infrastructure | — |
| Sharbani Roy | Arm | Speaker | Sponsored Session: Architecting AI: Efficient Models, Everywhere | — |
| Sherlock Huang | Meta | Speaker | Beyond TorchScript: The Future of C++ Inference in PyTorch | — |
| Sherlock Huang | Meta | Speaker | Meet the Developers of PyTorch Compiler and Helion | — |
| Shireen Kheradpey | Spotify | Speaker | Sponsored Session: Everything Everywhere all at Once: vLLM Hardware Optionality with Spotify and Google | — |
| Shrinath Thube | IBM | Speaker | Birds of a Feather: Ethical and Responsible AI: PyTorch’s Framework for Safer Model Deployment | — |
| Shruti Verma | clockwork.io | Lightning talk | Sponsored Session: Lightning Talk: Per-iteration PyTorch Visibility for Fast Debugging and Smarter Optimization | — |
| Shuai Yang | Meta | Poster | Poster Presentations: Generative & Large Models | — |
| Shuao Xiong | Meta | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Shulin Chen | Snowflake | Speaker | “Many-model” Time Series Forecasting: Scaling PyTorch Training Across 1000s of Models | — |
| Sibasish Acharya | Meta | Poster | Poster Presentations: Industry & Infrastructure | — |
| Siddartha Pothapragada | Meta | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Simon Axelrod | The D. E. Shaw Group | Lightning talk | Sponsored Session: Lightning Talk: Improving Drug Discovery with Machine Learning and Molecular Dynamics | — |
| Simon Fan | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Simon Mo | vLLM | Speaker | vLLM: Easy, Fast, and Cheap LLM Serving for Everyone | — |
| Simon Mo | vLLM | Speaker | Meet the vLLM Maintainers | — |
| Sinchan Banerjee | UST | Poster | Poster Presentations: Industry & Infrastructure | — |
| Spenser Bauman | Modular | Speaker | Mojo + PyTorch: A Simpler, Faster Path To Custom Kernels | — |
| Steve Winslow | The Linux Foundation | Speaker | The OpenMDW License Agreement: Simple, Permissive Terms for AI Model Materials | — |
| Steven Troxler | Meta | Poster | Poster Presentations: Ecosystem & Performance | — |
| Surya Subramanian | Meta | Poster | Poster Presentations: Compilers & Kernels | — |
| Suvaditya Mukherjee | Magnopus / University of Southern California | Poster | Poster Presentations: Generative & Large Models | — |
| Teja Rao | Meta | Lightning talk | Lightning Talk: Model Checkpoint Compression With OpenZL | — |
| Thanh Ha | The Linux Foundation | Speaker | Meet the Developers of PyTorch Dev Infra | — |
| Thomas Neff | Luma AI | Speaker | How Modern PyTorch Supercharges Multimodal Training and Inference at Luma AI | — |
| Thomas Ortner | IBM | Poster | Poster Presentations: PyTorch Core | — |
| Thomas Parnell | IBM | Speaker | Enabling VLLM V1 on AMD GPUs With Triton | — |
| Thomas Viehmann | Lightning AI | Lightning talk | Thunder: Distribute and Optimize Your PyTorch Models With Zero Code Changes | — |
| Tianyu Liu | Meta | Lightning talk | Lightning Talk: Unlock the Future of Generative AI: TorchTitan's Latest Breakthroughs | — |
| Tiejun Chen | Individual Contributor | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Tina Tsou | TSC Chair of InfiniEdge AI (LF Edge) and TSC Member of OPEA (LF AI & Data) | Speaker | Leveraging PyTorch for Generative AI in Distributed Edge Clouds | — |
| Travis Oliphant | OpenTeams | Speaker | Sponsored Session: Building the Next Generation of Open Source AI Tooling | — |
| Tristan Rice | Meta | Poster | Poster Presentations: Industry & Infrastructure | — |
| Tristan Rice | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Tristan Rice | Meta | Speaker | Sponsored Session: PyTorch Distributed and Fault Tolerance | — |
| Tristan Webb | d-Matrix | Poster | Poster Presentations: Ecosystem & Performance | — |
| Tyler Michael Smith | Red Hat | Poster | Poster Presentations: Generative & Large Models | — |
| Vaclav Knapp | Smíchovská střední průmyslová škola a gymnázium | Speaker | Controllable Generation of Synthetic Video Data With Human Motion | — |
| Vaibhav Tupe | Equinix | Speaker | Birds of a Feather: Ethical and Responsible AI: PyTorch’s Framework for Safer Model Deployment | — |
| Valentin Duruisseaux | California Institute of Technology | Poster | Poster Presentations: Industry & Infrastructure | — |
| Varun Khare | NimbleEdge | Poster | Poster Presentations: Generative & Large Models | — |
| Vasiliy Kuznetsov | Meta | Speaker | mxfp8, mxfp4, nvfp4 formats and applications in PyTorch | — |
| Venkat Vishwanath | Argonne National Laboratory | Poster | Poster Presentations: Industry & Infrastructure | — |
| Victor Bourgin | Meta | Poster | Poster Presentations: Industry & Infrastructure | — |
| Vijay Pawar | Cadence | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Vinay Sridhar | Snowflake | Speaker | “Many-model” Time Series Forecasting: Scaling PyTorch Training Across 1000s of Models | — |
| Vít Růžička | NASA | Speaker | AI On-board of Satellites, Towards Autonomous Scientific Instruments - Vit Ruzicka, NASA - Jet Propulsion Laboratory | — |
| Vivek Kumar | Intel | Poster | Poster Presentations: Generative & Large Models | — |
| Warren Zhu | Harvard University | Poster | Poster Presentations: Industry & Infrastructure | — |
| Wei Wang | NVIDIA | Poster | Poster Presentations: PyTorch Core | — |
| Weiwei Zhang | Intel | Poster | Poster Presentations: Generative & Large Models | — |
| Weiwen Xia | Intel | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Will Constable | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Will Feng | — | Speaker | Meet the Developers of PyTorch Compiler and Helion | — |
| William Jones | Embecosm | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| William Wen | Meta | Poster | Poster Presentations: Compilers & Kernels | — |
| Woosuk Kwon | UC Berkeley | Speaker | Meet the vLLM Maintainers | — |
| Xiaojun Fu | Meta | Poster | Poster Presentations: Industry & Infrastructure | — |
| Xilun Wu | Meta | Lightning talk | Lightning Talk: FlexCP: FlexAttention for Long Sequence Training Using Context Parallel | — |
| Xin Wang | d-Matrix | Poster | Poster Presentations: Ecosystem & Performance | — |
| Xuwen Chen | NVIDIA | Speaker | Enabling Lightweight, High-Performance FSDP With NVIDIA GPU | — |
| Yahav Biran | Amazon Web Services | Speaker | Multi-Accelerator PyTorch Serving With NxD Inference and vLLM | — |
| Yang Wang | Engineer | Speaker | Meet the Developers of PyTorch Dev Infra | — |
| Yanyuan Qin | AMD | Speaker | Efficient MoE Pre-training at Scale on AMD GPUs With TorchTitan | — |
| Yarong Mu | Poster | Poster Presentations: Compilers & Kernels | — | |
| Yi-Ting Wu | clockwork.io | Lightning talk | Sponsored Session: Lightning Talk: Per-iteration PyTorch Visibility for Fast Debugging and Smarter Optimization | — |
| Yidi WU | Meta | Poster | Poster Presentations: PyTorch Core | — |
| Yikun Jiang | Huawei | Poster | Poster Presentations: Edge & Hardware Acceleration | — |
| Yineng Zhang | Together AI | Speaker | Open Source Model Performance Optimization With SGLang | — |
| Ying Chen | Poster | Poster Presentations: Edge & Hardware Acceleration | — | |
| Yonghua Lin | BAAI | Speaker | Breaking Heterogeneity Barriers: Unified Cloud-to-Robot AI System SW Stack for Embodied Intelligence | — |
| Yu Chin Fabian Lim | IBM | Speaker | No GPU Left Behind: Scaling Online LLM Training With Co-located VLLM in TRL | — |
| Yu Guangye | Intel | Poster | Poster Presentations: PyTorch Core | — |
| Yuxin Wu | Moonshot AI | Speaker | Kimi K2 and Our Contributions to Open Source | — |
| Yuxuan Jiang | University of Michigan | Poster | Poster Presentations: Ecosystem & Performance | — |
| Zach Lasiuk | Arm | Speaker | Birds of a Feather: Strong Model, Weak Product? Let’s Fix That. | — |
| Zachary DeVito | Meta | Speaker | Monarch: A Distributed Execution Engine for PyTorch | — |
| Zeina Migeed | Meta | Poster | Poster Presentations: Ecosystem & Performance | — |
| Zesheng Zong | Huawei | Lightning talk | Lightning Talk: Challenges and Standardization in PyTorch Ecosystem Accelerators | — |
| Zesheng Zong | Huawei | Poster | Poster Presentations: Responsible AI & Community | — |
| Zeyuan Yang | NVIDIA | Poster | Poster Presentations: Industry & Infrastructure | — |
| Zhe Zhang | NVIDIA | Speaker | Meet the Developers of PyTorch Dev Infra | — |
| Zifei Xu | d-Matrix | Poster | Poster Presentations: Ecosystem & Performance | — |
| Ziheng Jiang | ByteDance Seed | Speaker | Verl: A Flexible and Efficient RL Framework for LLMs | — |
Sources
- https://events.linuxfoundation.org/archive/2025/pytorch-conference/
- https://events.linuxfoundation.org/archive/2025/pytorch-conference/attend/venue-travel/
- https://events.linuxfoundation.org/archive/2025/pytorch-conference/register/
- https://pytorchconference.sched.com/list/descriptions/
- https://events.linuxfoundation.org/wp-content/uploads/2025/11/pytorchcon25_post-event_report_111025.pdf