Value Creation + Investment = Wealth

I am an investor, entrepreneur, and researcher with a Ph.D. in data-efficient machine learning from MIT.

Before MIT, I earned a B.A. in Physics and English from UC Berkeley. I’ve founded several startups and a venture DAO, driven by the desire to push the boundaries of what’s possible and to create lasting impact with elegant solutions.

In my free time, I enjoy reading, writing, and reflecting.

News Highlights

September 2024: PIN AI secures $10 million in pre-seed funding, led by a16z crypto. Read more
August 2024: Nature paper on achieving 60× faster processing in pharmaceutical manufacturing. Read more
July 2024: Joined the Apple AIML Residency Program to work on Apple Intelligence and Siri.
June 2024: Collaboration on Octo-planner with Nexa AI, featured by MIT CSAIL. Read more
May 2024: Congrats to Nexa AI from Stanford raises 15 million in seed funding. Read more
April 2024: Foundation model research on JetMoE highlighted by MIT CSAIL. Read more
March 2024: MyShell AI raises $11 million in pre-A round, led by Dragonfly. Read more
June 2023: Internship at MIT-IBM Watson AI Lab, focused on developing large language models for code generation.
June 2023: Nature paper on emergent ferromagnetism from low dimensional materials. Read more
May 2023: MIT-Takeda develops AI models for medicine manufacturing, reported by MIT News. Read more
Feb 2020: Appointed as Vice President at MIT Chinese Entrepreneurs Organization (MIT CEO). Read more
July 2019: Congrats to Prof. Xiang Zhang appointed President and Vice-Chancellor of the University of Hong Kong. Read more

Opportunities

If you’re seeking advisorship for venture funds or startups in AI, Web3, and emerging technologies, feel free to email me.

Publications

Scaling Law Hypothesis for Multimodal Model
Qingyun Sun, Zhen Guo
PIN AI White Paper
[paper]
Octo-planner: On-device Language Model for Planner-Action Agents
Wei Chen, Zhiyuan Li, Zhen Guo, Yikang Shen
Nexa AI Technical Report
[paper]
More Compute Is What You Need
Zhen Guo
LLM Theory on arXiv
[paper]
JetMoE: Reaching Llama2 Performance with 0.1M Dollars
Yikang Shen, Zhen Guo, Tianle Cai, Zengyi Qin
MyShell AI Technical Report
[paper] [code] [demo]
Non-invasive Estimation of the Powder Size Distribution from a Single Speckle Image
Qihang Zhang, George Barbastathis, Ajinkya Pandit, Zhiguang Liu, Zhen Guo, et al.
Nature, Light: Science & Applications
[paper]
API Pack: A Massive Multi-Programming Language Dataset for API Call Generation
Zhen Guo, Adriana Meza Soria, Wei Sun, Yikang Shen, Rameswar Panda
NeurIPS 2024 conference submission
[paper]
Diversity Measurement and Subset Selection for Instruction Tuning Datasets
Peiqi Wang, Yikang Shen, Zhen Guo, Matthew J. Stallone, Yoon Kim, Polina Golland, Rameswar Panda
EMNLP 2024 conference submission
[paper]
AuthentiGPT: Detecting Machine-Generated Text via Black-Box Language Models Denoising
Zhen Guo, Shangdi Yu
NeurIPS 2023 on Generative AI for Education
[paper]
Improving Small Language Models on PubMedQA via Generative Data Augmentation
Zhen Guo, Peiqi Wang, Yanwei Wang, Shangdi Yu
KDD 2023 Foundations and Applications in Large-scale AI Models
[paper] [code]
On the Use of Deep Learning for Three-Dimensional Computational Imaging
George Barbastathis, Subeen Pang, Iksung Kang, Zhiguang Liu, Zhen Guo, and Fucai Zhang
SPIE Photonics West (2023)
[paper]
Noise-resilient Deep Tomographic Imaging
Zhen Guo, Zhiguang Liu, George Barbastathis, Qihang Zhang, Michael E. Glinsky, Bradley K. Alpert, Zachary H. Levine
Optica Open (2022)
[paper] [code]
Physics-assisted Generative Adversarial Network for X-ray Tomography
Zhen Guo, Jung Ki Song, George Barbastathis, Michael E. Glinsky, Courtenay T. Vaughan, Kurt W. Larson, Bradley K. Alpert, Zachary H. Levine
Optics Express (2022)
Conference proceeding at Electronic Imaging: Machine Learning for Scientific Imaging (2022)
[paper] [slide] [code] [link]
LION: Learning to Invert 3D Objects by Neural Networks
George Barbastathis, Jungki Song, Zilin Wu, Subeen Pang, Zhen Guo
Microsystems Technology Laboratories Annual Research Report (2021)
[paper]
Randomized Probe Imaging Through Deep k-learning
Zhen Guo, Abraham Levitan, George Barbastathis, Riccardo Comin
Optics Express (2022)
Conference proceeding at Computational Optical Sensing and Imaging (2021)
[paper] [slide] [code] [link]
Ferromagnetism Emerged from Non-ferromagnetic Atomic Crystals
Cheng Gong, Xiang Zhang, Peiyao Zhang, Tenzin Norden, Quanwei Li, Zhen Guo, Apoorva Chaturvedi, Arman Najafi, Shoufeng Lan, et al.
Nature Communications (2023)
[paper]
Wafer-scale On-chip Synthesis and Field Emission Properties of Vertically Aligned Boron Nitride Based Nanofiber Arrays
Hu Long, Thang Pham, Aiming Yan, Zhen Guo, Hiroya Ishida, Wu Shi, Sally Turner, S. Matt Gilbert, and Alex Zettl
Applied Physics Letters (2019)
[paper]

Writing

Pride Can Hold You Back: Lessons from My Time at Berkeley and MIT

This first post focuses on my personal experiences at Berkeley and MIT, highlighting how pride in my initial decisions led to both practical and emotional consequences.
Why Standing Still Is the Riskiest Move in a Changing World

This blog post dives into the broader industry insights I gained after ChatGPT’s release, and how pride in one’s current status can blind people to the rapid changes happening in technology.

Patents

System and Method for Real-Time Determination of Particle Size Distributions in Dry Powders
Qihang Zhang, Ajinkya Pandit, Allan S. Myerson, George Barbastathis, Richard D. Braatz, and Zhen Guo

Projects

Gen-VQA: Generative Visual Question Answering with Abstract Scenes
Yifan Yang, Zhen Guo
MIT 6.869 Advances in Computer Vision, Fall 2019
[report] [code]
Hardware Efficient Quantum Computing via Circuit Decomposition
Tianyi Peng, Linsen Li, Kaidong Peng, Yufeng Ye, Zhen Guo
iQuHACK MIT Quantum Hackathon (first place), Winter 2019
[report] [code]

Experience

Fall 2020: Teaching Assistant, MIT
6.728: Applied Quantum and Statistical Physics

Extracurricular

MIT Chinese Entrepreneur Organization