Shen Zhuoran (Zhuoran is the first name) is a Founding Scientist at a stealth startup on RSI and AI Scientists. He believes rollout efficiency for RL is a bottleneck challenge for RSI and other long-horizon, high-cost/high-complexity tasks and works on innovative RL recipes to address this issue.

He was most recently at xAI, working on agentic grading, self-play, and large-scale coding RL, including leading the potentially largest-scale agentic grading RL run at the time. Previously, he worked at Augment Code on coding model pre-training, post-training, and harness engineering, which reached state-of-the-art performance on coding pre-training benchmarks and SWE-bench Verified. Early in his career, he worked on early linear attention mechanisms and Transformer-based vision foundation models during his Google AI Residency.

He holds a BEng in Computer Science from The University of Hong Kong with First-Class Honours and the top-1 GPA in the Class of 2019.

Education

The University of Hong Kong, Hong Kong

• Sep. 2015 - Jun. 2019.
• Bachelor of Engineering in Computer Science.
• GPA: 3.85/4.30. Standing: 1/111.

University of California, Davis, Davis, CA, United States

• Sep. 2017 - Dec. 2017.
• Bachelor’s Reciprocity Student in Computer Science.
• GPA: 4.00/4.00.

Work Experience

xAI, San Francisco Bay Area, United States

• Sep. 2025 - Present.
• Member of Technical Staff
• Working on Grok and Grok Code post-training for reasoning and coding.

Augment Code, San Francisco Bay Area, United States

• Dec. 2023 - Sep. 2025.
• Research Scientist
• Lead Augment’s code LLM pre-training, matched state-of-the-art performance (DeepSeek-Coder).
• Post-trained several component models of Augment’s state-of-the-art enterprise coding agent. An open-source version reached no. 1 on SWE-bench Verified.

Cruise, San Francisco Bay Area, United States

• Jan. 2023 – Dec. 2023.
• Senior ML/Robotics Engineer, Behaviors Data, AI • Established a continuous training mechanism for Cruise’s planning models. • Lead an ML-based solution for misbehaviors around emergency vehicles.

Pony.ai, San Francisco Bay Area, United States

• Nov. 2021 - Oct. 2023.
• Software Engineer, Prediction Department • Lead the motion prediction module’s transition from heuristics to end-to-end deep learning.

Google, Seattle, United States

• Oct. 2019 - Aug. 2021.
• AI Resident, Google Brain, Google Research
• Proposed an early Transformer arhictecture for computer vision, the global self-attention networks (GSA-Nets). Details in Research Experience.
• Worked on zero-shot detection using image-text pretrained Transformers. Collaboratively proposed vision Transformer for open-world localization (OWL-ViT). Details in Research Experience.

Tencent, Shenzhen, China

• Jul. 2019 - Sep. 2019.
• Research Intern, Applied Research Center, Platform and Content Group
• Proposed a linear attentive memory mechanism for video understanding, the global context module. Details in Research Experience.

SenseTime, Hong Kong

• Jun. 2017 - Jun. 2019.
• Research Intern, Intelligent Perception and Services Team, Smart City Group
• Proposed one of the first linear-complexity attention mechanisms, efficient attention. Details in Research Experience.

Memberships

• Sigma Xi Full Member
• ACM Professional Member
• IEEE Member
• IEEE Young Professional

Awards

• Dean’s Honours List 2018-2019, Faculty of Engineering, The University of Hong Kong
• Dean’s Honours List 2017-2018, Faculty of Engineering, The University of Hong Kong
• Dean’s Honours List 2016-2017, Faculty of Engineering, The University of Hong Kong
• Dean’s Honours List 2015-2016, Faculty of Engineering, The University of Hong Kong
• Dean’s Honor List, Fall Quarter 2017, College of Letters and Science, University of California, Davis
• YC Cheng Engineering Scholarship, 2017, Faculty of Engineering, The University of Hong Kong

Programming Contests

• First Runner-up, ACM-HK Programming Contest 2017
• Second Runner-up, ACM-ICPC Hong Kong PolyU International Invitational 2017
• Second Runner-up, hackUST 2017 Radica Challenge
• First Prize, National Olympiad of Informatics in Provinces (China) 2014

Research Experience

Vision Transformer for Open-World Localization, Google

• Dec. 2020 - Aug. 2021.
• Supervised by Dr. Mostafa Dehghani, Senior Research Scientist, Google Brain, Google Research, Google.
• Worked on vision Transformer for open-world localization (OWL-ViT), a simple zero/few-shot detection framework that transfers from image-text pretraining.
• Set a new state-of-the-art for one-shot detection by a wide margin.
• Published a paper at ECCV 2022.

Global Self-Attention Networks, Google

• Dec. 2019 - Oct. 2020.
• Supervised by Dr. Raviteja Vemulapalli, Senior Research Scientist and Dr. Jia Xuhui, Senior Software Engineer, Google Research, Google.
• Proposed global self-attention networks (GSA-Nets), one of the first to use efficient attention mechanisms to fully replace convolution for computer vision applications.
• Demonstrated superior trade-offs for accuracy vs. parameters, computation, and latency over CNNs.
• Shared a preprint on arXiv.

Global Context Module, Tencent

• Jul. 2019 - Sep. 2019.
• Supervised by Dr. Shan Ying, Director of Applied Research Center, Platform and Content Group, Tencent.
• Proposed the global context module, which effectively and efficiently propagates information through an arbitrarily long video with constant complexity w.r.t. video length and linear complexity w.r.t. resolution.
• Developed the first real-time video object segmenter that has state-of-the-art accuracy.
• Presented a first-author paper at ECCV 2020.

Efficient Attention, SenseTime

• Sep. 2018 - Jun. 2019.
• Supervised by Dr. Yi Shuai, Research Director, SenseTime.
• In collaboration with Dr. Li Hongsheng, Assistant Professor, Multimedia Laboratory, Chinese University of Hong Kong.
• Proposed efficient attention, which reduces the memory and computational complexities of the attention mechanism from quadratic to linear.
• Demonstrated significant improvement in performance-cost trade-offs on a variety of tasks including object detection, instance segmentation, stereo depth estimation, and temporal action localization.
• Presented a first-author paper at WACV 2021.

Visual Embedding of Chinese, Bachelor’s Final-Year Project

• Sep. 2018 - Apr. 2019.
• Supervised by Dr. Kwan-Yee Kenneth Wong, Associate Professor, Computer Vision Group, The University of Hong Kong.
• Designed OceanText, a novel character embedding algorithm for Chinese that extracts a semantic embedding from the image of a Chinese character with a convolutional neural network.
• Developed a PyTorch embedding library. Reduced single-GPU training time from 82 days to 28.1 hours compared to existing open-source implementations.
• Significantly improved accuracy for word similarity estimation from character embeddings for Chinese.

Teaching Experience

Software Engineering, Teaching Assistant

• Jan. 2019 - May 2019.
• Assisted George Mitcheson, Guest Lecturer, Department of Computer Science, The University of Hong Kong.
• Developed a Django server as the external HR server for student projects and deployed it to Heroku.
• Answered questions from and held consultations with students on Git, the Unified Modeling Language, and software design and engineering principles.

Personal Projects

BeautyNet

• May 2018 - Oct. 2019.
• Personal open-source project.
• Developed the 2nd most popular PyTorch template on GitHub with 190+ stars and very high code quality.

The Walled Planet

• Sep. 2016 - Nov. 2016.
• Course Project, Virtual Worlds, Real Bodies, The University of Hong Kong
• Built a maze runner game for virtual reality. Used Unity as the game engine and SketchUp for 3D modeling.
• The game is set in a dystopian future where the entire globe become similar to the former Kowloon Walled City. The game aims to arouse players’ awareness about the quality of life in a modern metropolis.

Rush to 1202!

• Jan. 2016 - Mar. 2016.
• Course Project, Introduction to Computer Science, The University of Hong Kong
• Developed a Super Mario-like game. Used Scratch as the development platform.
• The game sets on the day of the final exam of the very course, making it highly immersive for classmates. It features extremely counter-intuitive traps, making it very fun to play.

Publications and Preprint

• M. Minderer, A. Gritsenko, A. Stone, M. Neumann, D. Weissenborn, A. Dosovitskiy, A. Mahendran, A. Arnab, M. Dehghani, Shen Z., X. Wang, X. Zhai, T. Kipf, N. Houlsby. (2022). Simple Open-Vocabulary Object Detection with Vision Transformers. ECCV 2022.
• Shen Z., Zhang M., Zhao H., Yi S., Li H. (2021). Efficient Attention: Attention with Linear Complexities. WACV 2021.
• Shen Z., I. Bello, R. Vemulapalli, Jia X., Chen C.-H. (2020). Global Self-Attention Networks for Image Recognition. arXiv: 2010.03019.
• Li Y.*, Shen Z.*, Shan Y. (2020). Fast Video Object Segmentation using the Global Context Module. ECCV 2020. *Equal contributions.

Patents

• Shen Z., Wu Y. (2026). Processing Method for Vehicle Driving Data, Relevant Devices, Computer Equipment, and Storage Media. CN Patent CN115465290B. Beijing, China: China National Intellectual Property Administration.
• Shen Z., Zhang M., Zhao H., Yi S., Yan J. (2021). Method for Obtaining Attention Features for Neural Networks, Relevant Devices, and Storage Media. CN Patent CN109635926B. Beijing, China: China National Intellectual Property Administration.
• Shen Z., I. Bello, Jia X., Chen C.-H., R. Vemulapalli.
  • (2025). Computing System, Method and Medium for Modeling Dependencies. CN Patent CN115885289B. Beijing, China: China National Intellectual Property Administration.
  • (2023). Modeling Dependencies with Global Self-Attention Neural Networks. European Patent Application EP4154185A2. Munich, Germany: European Patent Office.
  • (2021). Modeling Dependencies with Global Self-Attention Neural Networks. Int’l Patent Application (PCT) WO2020257812A3. Geneva, Switzerland: World Intellectual Property Organization.

Non-Professional Experience

Urumqi Middle School Student StarCraft II League (UM3SL)

• Jun. 2012 - Oct. 2012
• Organizer, commentator
• Organized an online e-Sport tournament for StarCraft II. Promoted the tournament on online forums. Set up broadcasting infrastructure on own3D.tv and ZhiboBox. Commentated and broadcasted the games.
• 8 players from 6 schools joined. The tournament finished after a group stage and a top-four playoff.

Skills

• Programming: Python, C++, Shell script, Markdown, LaTeX
• Technologies: TensorFlow, Keras, PyTorch, NumPy, OpenCV, Horovod, Slurm, Git, Bazel, Django
• Hobbies: e-sports, StarCraft II, Karaoke
• Languages: Mandarin Chinese (native), English (working proficiency, TOEFL 116)