Senior Research Scientist and Manager, Autonomous Systems and Physical AI Research @ NVIDIA. Opinions are my own.
Mountain View, CA
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Our group's internship postings for 2027 are here!! Just like before, we'll be hosting interns year-round (not only during the summer!) with research scope across a wide range of Physical AI embodiments. Check out our website and posting to see what's new: research.nvidia.com/labs/asp…
We are hiring! The Autonomous Systems and Physical AI Research (ASPIRE: research.nvidia.com/labs/asp…) group at @nvidia is looking for talented PhD Research Interns to join us in advancing the frontiers of #autonomous #systems and #Physical #AI.
We work across a broad range of research areas, including #reasoning models, generative simulation, #agentic AI workflows, and Physical AI #safety, with applications spanning autonomous vehicles and a broad range of Physical AI systems.
Interested in pushing the limits of what’s possible? Apply now:
nvidia.wd5.myworkdayjobs.com…
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This Halloween, Alpamayo dressed up as a humanoid! 🤖 See if you can spot which clip it's in... ;)
Stay tuned for more, especially if you'll be at CoRL!
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Boris Ivanovic retweeted
What if AI could improve not only its own policies, but also the judges that evaluate them?
As AI policies improve, they encounter new challenges and develop new failure modes. The judges evaluating them need to evolve as well. Otherwise, they can become a bottleneck to further progress. This is particularly relevant for #Physical #AI, where good decisions require spatial grounding, causal reasoning, and safety awareness.
In our new paper, we introduce VeriFine, an #agentic #harness for continuous self-improvement in Physical AI, where policies, training curricula, and judges evolve together.
The idea is to build agentic systems that can identify policy failures, turn them into useful training signals, and improve the policy. When the judge itself becomes a bottleneck, the harness brings in targeted human feedback to refine its evaluations and guide the next round of improvement.
We evaluate VeriFine on autonomous driving and robot navigation, demonstrating continued improvements in both policy and judge capabilities through reinforcement learning and supervised fine-tuning.
Key takeaway: We're developing agentic harnesses that go beyond optimizing a policy in a fixed loop. They adapt the improvement process itself—including how failures are identified, how training data is selected, and how progress is evaluated.
📄 Paper: arxiv.org/pdf/2610.08761
🌐 Website: veri-fine.github.io/
Work led by Zewei Zhou, in collaboration with Rachel Luo Yulong Cao @ChaoweiX Chensheng Peng @Boyiliee @tianran_ Zheng Lian @yan_wang_9 Jiaqi Ma @iamborisi @wenhaoding95
#PhysicalAI #Robotics #AgenticAI #Alpamayo
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Boris Ivanovic retweeted
New #NVIDIA paper: what if robots never had to wait for their own thoughts?
TacitVLA learns to reason in chain-of-thought or subtasks, but its actions never read them.
→ Keeps the gains of reasoning at up to 3.4× lower latency on 4 benchmarks, and tops RoboMME and RMBench 🧵👇
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Boris Ivanovic retweeted
🤔 𝘾𝙖𝙣 𝙨𝙚𝙡𝙛-𝙞𝙢𝙥𝙧𝙤𝙫𝙚𝙢𝙚𝙣𝙩 𝙗𝙚 𝙨𝙪𝙨𝙩𝙖𝙞𝙣𝙚𝙙 𝙬𝙞𝙩𝙝 𝙖 𝙛𝙞𝙭𝙚𝙙, 𝙣𝙤𝙣-𝙘𝙤-𝙚𝙫𝙤𝙡𝙫𝙞𝙣𝙜 𝙟𝙪𝙙𝙜𝙚?
Better policies expose new failures. If their judges stay fixed, verification can become the bottleneck to further self-improvement.
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We’re looking for our next cohort of graduate fellows.
Our 2027–2028 Graduate Fellowship Program is open to Ph.D. students worldwide with awards up to $60,000, plus mentorship and technical support.
Apply by October 30: nvda.ws/4rGKDhv
Made with AI
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Boris Ivanovic retweeted
Following up on my previous post about PhD Research Intern opportunities, the Autonomous Systems and Physical AI Research (ASPIRE, research.nvidia.com/labs/asp…) group at @nvidia is also hiring for full-time positions!
Priority will be given to candidates who can start by the end of January 2027.
Open positions:
- (Senior) Research Scientist — Apply here: nvidia.wd5.myworkdayjobs.com…
- (Senior) Research Engineer — Apply here: nvidia.wd5.myworkdayjobs.com…
We work across #reasoning models, #generative simulation, #agentic #AI workflows, and #Physical AI #safety, with applications spanning autonomous vehicles and a broad range of Physical AI systems.
If you’re interested in joining us, we’d love to hear from you!
@NVIDIADRIVE @NVIDIARobotics @NVIDIAAI
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Boris Ivanovic retweeted
In case you missed it — we did a deep dive into NVIDIA Alpamayo 2 Super, our most capable open reasoning model for robotaxi and L4 AV development yet.
During the stream, we walked through the release notebooks live, showed how Alpamayo 2 Super can power auto-labeling pipelines faster and cheaper than GPT-based alternatives, and covered the latest AlpaSim controller updates.
Watch the replay → nvda.ws/4hhyQT0
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Boris Ivanovic retweeted
Join us tomorrow for a deep dive into #Alpamayo 2 Super—our most capable model yet!
We’ll unpack the key technologies behind the model, showcase hands-on notebooks to help you get started, and share the latest AlpaSim updates.
We’ll also take a closer look at our two ongoing challenges, with prizes up for grabs!
Save the date: addevent.com/event/mwwld54rm…
@NVIDIADRIVE @NVIDIAAI
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Join us next week! My colleagues and I will be diving into our latest model: Alpamayo 2 Super, how to get started with it for your use cases of interest, and the concurrently running challenges (with prizes!) we're hosting for evaluating closed-loop driving and reasoning quality!
Building robotaxis or L4 autonomy? Don't miss our livestream.
On Sept. 9 @ 9AM PT, we'll deep dive into NVIDIA Alpamayo 2 Super, covering release notebooks, robotaxi pipelines, AlpaSim updates and more.
Save the date: nvda.ws/4A1S9r5
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Alpamayo 2 Super is here! It's our most capable open reasoning foundation model, performing multiple tasks across autonomous vehicle development including auto-labeling, VQA, high-level intent, and trajectory generation.
Thank you Jensen for celebrating this launch with us! 🚙🤖
Today, we’re launching Alpamayo 2 Super, our frontier open reasoning model for autonomous vehicles.
Beyond seeing, Alpamayo understands and reasons through the complex world - thinks before it acts.
It’s a powerful backbone for robotaxis, trucks, shuttles, delivery vans, tractors and the long tail of mobile robots—billions of autonomous machines someday.
We’re releasing it for commercial use under OpenMDW-1.1 so teams can inspect it, fine-tune it and deploy it—open models advance safety and security.
The next wave of AI is robotics—and it starts with autonomous vehicles.
Great work, Alpamayo team!
blogs.nvidia.com/blog/alpama…
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Boris Ivanovic retweeted
We just made it significantly easier to build your own reasoning-based AV.
Alpamayo 2 Super: 32B params, 7+ cameras, 360° perception, chain-of-thought reasoning, and autolabeling. AlpaGym: closed-loop RL training so your model learns from its own mistakes in simulation.
Full replay: nvda.ws/3Qkh2MG
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Boris Ivanovic retweeted
Today we're releasing @nvidia AlpaGym, our new open-source reinforcement learning (RL) framework for end-to-end autonomous driving.
A key challenge for #Physical #AI is enabling policies to learn from the consequences of their actions. While supervised learning can teach a model to imitate behavior, robust autonomy ultimately requires learning through interaction with the environment.
AlpaGym enables exactly that.
Built on top of:
- AlpaSim: our high-fidelity closed-loop autonomous driving simulator
- Cosmos-RL: NVIDIA's distributed RL training and rollout infrastructure
AlpaGym provides the glue that connects simulation, training, and driving policies into a scalable framework for post-training autonomous vehicle models in closed loop.
With AlpaGym, researchers and developers can:
✅ Train end-to-end driving policies using reinforcement learning
✅ Run large-scale closed-loop simulations
✅ Experiment with new reward functions, policy architectures, and training strategies
✅ Benchmark models on public leaderboards
📖 Learn how it works: developer.nvidia.com/blog/ho…
💻 GitHub: github.com/NVlabs/alpagym
🏆 Open Challenges:
- AlpaSim Closed-Loop E2E Driving Challenge: huggingface.co/spaces/nvidia…
- Physical AI AV Reasoning Challenge: huggingface.co/spaces/nvidia…
Learn more about the #Alpamayo open platform:
huggingface.co/blog/drmapavo…
#PhysicalAI #AutonomousDriving #ReinforcementLearning #Robotics #OpenSource #NVIDIA #MachineLearning
@NVIDIADRIVE @NVIDIAAI
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Boris Ivanovic retweeted
On the power of data flywheels in Physical AI
@nvidia recently introduced Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, images, video, audio, and actions within a unified mixture-of-transformers architecture.
One aspect I find particularly exciting is the data flywheel emerging between #Cosmos 3 and #Alpamayo 2.
Cosmos 3 was trained using data generated and curated in part through the Alpamayo ecosystem. In turn, the next generation of Alpamayo will build on Cosmos 3's capabilities. This creates a virtuous cycle in which better models enable better data generation, and better data leads to even stronger models.
Much of the attention in #AI is naturally focused on model architectures and benchmark results. Yet, in robotics and autonomous systems, development processes matter just as much as models themselves. Robust data flywheels are increasingly becoming a defining characteristic of state-of-the-art robot autonomy stacks.
Further reading:
- Cosmos 3: arxiv.org/pdf/2606.02800
- Alpamayo 2: huggingface.co/blog/drmapavo…
Join me on June 16 at 9:00 AM PT for a livestream on Alpamayo 2 Super: The Open Reasoning Model for Robotaxis: addevent.com/event/5djffx3cl…. We'll showcase brand-new elements of the open pipeline—from real-world fleet data to model training recipes to closed-loop development with simulation. If you're building toward L4 autonomy, I think you'll find it worthwhile.
I'll be joined by @iamborisi @YurongYou @yan_wang_9 @MaxiIgl
Looking forward to seeing you there.
@NVIDIADRIVE @NVIDIAAI
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Thrilled to keep growing the #Alpamayo ecosystem with new models (Alpamayo 2 Super), closed-loop training frameworks (AlpaGym), and benchmarks to measure progress in reasoning and closed-loop driving!
Ask me about this latest release as well as all things Alpamayo at #CVPR2026!
Excited to share the latest expansion of the @nvidia #Alpamayo open platform for reasoning-based autonomous vehicles.
Since its launch earlier this year, Alpamayo has seen rapid adoption across industry and academia, with its reasoning models surpassing 400,000 downloads and earning a #COMPUTEX 2026 Best Choice Award.
As announced by Jensen Huang during his #COMPUTEX keynote, we are now introducing several major additions designed to accelerate the development of next-generation AV systems (more details here: huggingface.co/blog/drmapavo…):
🚗 Alpamayo 2 Super — a new 32B-parameter driving foundation model with:
• Full 360° surround-view perception
• Advanced reasoning capabilities and chain-of-causation outputs
• Meta-actions such as lane changes, yielding, and stopping
• Reasoning auto-labeling and visual grounding for scalable data annotation
• State-of-the-art performance across reasoning, prediction, and alignment tasks
🔄 AlpaGym — an open-source framework for closed-loop reinforcement learning, enabling AV models to learn from the consequences of their actions in simulation and helping bridge the gap between training and real-world deployment.
📊 New Open Benchmarks — including challenges for closed-loop driving and long-tail reasoning to help the community measure progress and drive innovation.
🛠️ Alpamayo Recipes — a centralized repository of end-to-end workflows covering supervised fine-tuning, reinforcement learning, quantization, and model customization.
Reasoning models and closed-loop training are becoming foundational technologies for autonomous systems. Our goal is to provide the open tools, models, infrastructure, and benchmarks needed to accelerate progress across the entire AV ecosystem.
A huge thank you to the many researchers, engineers, and community members whose feedback helped shape this release.
Resources:
• Overview of the latest Alpamayo release (note: some components will be released over the coming weeks): huggingface.co/blog/drmapavo…
• @nvidia announcement: nvidianews.nvidia.com/news/n…
#AutonomousVehicles #PhysicalAI #Robotics #AI #MachineLearning #ReinforcementLearning #OpenSource #NVIDIA #Alpamayo
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Boris Ivanovic retweeted
We’ve just released the #Alpamayo Chain-of-Causation (CoC) Autolabeling Pipeline — a feature that has been highly requested by the community!
The pipeline automatically derives:
🔹 Meta-actions: high-level categorical descriptions of ego motion
🔹 Chain-of-causation labels: causal links between scene factors and the ego vehicle’s intended behavior
Autolabeling pipeline: github.com/NVlabs/alpamayo-c…
Learn more about the Alpamayo open platform: huggingface.co/blog/drmapavo…
We’re excited to see what the community builds with it, and we hope this tool will help accelerate research in the rapidly growing area of #reasoning models for #Physical #AI.
@NVIDIADRIVE @NVIDIAAI
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Boris Ivanovic retweeted
Thrilled to personally invite you to the @nvidia #Alpamayo Summit at #CVPR!
I’ll be opening the event with a talk titled “The ChatGPT Moment for Autonomous Driving” — exploring how reasoning AI is reshaping the entire autonomy stack and accelerating the path toward scalable, safe Level 4 autonomous driving.
📍 June 4, 2026
📍 Le Méridien Denver Downtown (Grove Ballroom)
🕞 3:30 PM — Networking + Snacks
🕓 4:00 PM — Program Begins
We’ll cover:
• Open datasets
• New reasoning models
• AlpaSim
• Safety frameworks
• And much more
Join the waitlist here → nvevents.nvidia.com/alpamayo…
The event is currently sold out, but you can still join the waitlist.
@NVIDIADRIVE @NVIDIAAI
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Proud to see the #Alpamayo Open Platform earn a #COMPUTEX2026 Best Choice Award! Autonomous vehicles are one of the best examples of Physical AI, and such open platforms take deep collaboration. Thanks to all in NVIDIA and our partners for enabling this. More coming at #CVPR2026!
🚗🏆 Breaking news: @nvidia #Alpamayo open platform has been named the winner of a COMPUTEX TAIPEI 2026 Best Choice Award in the Vehicle Technology & Smart Cockpit category, recognizing Alpamayo as one of the year’s major breakthroughs in automotive and Physical AI technology!
Announcements:
- blogs.nvidia.com/blog/nvidia…
- bcaward.computex.biz/WinnerY…
I’m incredibly proud of the team behind the Alpamayo open platform — Wenjie Luo @yan_wang_9 @iamborisi and the entire NVIDIA Autonomous Vehicle Research Group — and deeply grateful for the contributions from the NVIDIA AV production team Xinzhou Wu Sarah Tariq and many other researchers and developers across NVIDIA. This achievement was truly a collective team effort.👏
To get started with Alpamayo:
— huggingface.co/blog/drmapavo…
— huggingface.co/blog/drmapavo…
And stay tuned — we’ll have several exciting announcements in the coming weeks.
@NVIDIADRIVE @NVIDIAAI
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Boris Ivanovic retweeted
Excitingly, @nvidia #Alpamayo 1.5 is now available within Autoware: github.com/autowarefoundatio…
Grateful to @ShinpeiKato and the rest of the TIER IV team for helping democratize the development of AV solutions. I look forward to seeing #Alpamayo’s adoption continue to grow!
As Jensen said, “Everything that moves will be autonomous.” Together, we are making big strides toward this vision!
More about Alpamayo 1.5: huggingface.co/blog/drmapavo…
@NVIDIADRIVE @NVIDIAAI
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Thrilled to expand the #Alpamayo ecosystem at #GTC2026! Alpamayo 1.5 pushes #AutonomousDriving forward with support for more inputs, new reasoning capabilities, and RL post-training. We’re also open-sourcing key tools! At GTC? Join me at Wed 9am for more: nvda.ws/473AMcf
Jensen today announced Alpamayo 1.5 at #NVIDIAGTC!
#Alpamayo 1.5 is a major update to Alpamayo 1—@nvidia’s open 10B-parameter chain-of-thought reasoning VLA model, first introduced at #CES. Built on the #Cosmos-Reason2 VLM backbone and post-trained with RL, it adds support for navigation guidance, flexible multi-camera setups, configurable camera parameters, and user question answering. The result is an interactive, steerable reasoning engine for the AV community. We’re also releasing post-training scripts to help researchers and developers adapt the model.
Additionally, we’ve significantly expanded the Alpamayo open platform across data and simulation, including releasing highly requested reasoning labels for the PhysicalAI Autonomous Vehicles dataset (huggingface.co/datasets/nvid…), as well as our chain-of-causation auto-labeling pipeline.
🔎 Learn more about Alpamayo 1.5 and the latest extensions to the Alpamayo open platform:
huggingface.co/blog/drmapavo… (please note that most of the links will become active in the next few days.)
Happy building—and stay tuned for more in the coming months!
@NVIDIADRIVE @NVIDIAAI
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