Gavin Guo (国振)


PhD student at MIT EECS

zguo0525 AT
Google Scholar
Curriculum Vitae

Value Creation + Investment = Wealth

I am an entrepreneur and physicist, obtained my Ph.D. at MIT on data-efficient machine learning.

Prior to MIT, I received my B.A. with the highest honor in physics and minors in English and EECS from UC Berkeley. In the past, I have co-founded multiple startups and a venture DAO, each driven by the common goal of pushing the boundaries of what’s possible and making a lasting impact with practical solutions.


In summer 2024, I will be joining Apple AIML Residency Program for vision language models.

In summer 2023, I interned at MIT-IBM Watson AI Lab to develop large language models for code generation.


Octo-planner: On-device Language Model for Planner-Action Agents

Wei Chen, Zhiyuan Li, Zhen Guo, Yikang Shen
Technical report.

More Compute Is What You Need

Zhen Guo

JetMoE: Reaching Llama2 Performance with 0.1M Dollars

Yikang Shen, Zhen Guo, Tianle Cai, Zengyi Qin
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, Shashank Muddu, Yi Wei, Deborah Pereg, Neda Nazemifard, Charles Papageorgiou, Yihui Yang, Wenlong Tang, Richard D. Braatz, Allan S. Myerson
Nature, Light: Science & Applications.

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.

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.

AuthentiGPT: Detecting Machine-Generated Text via Black-Box Language Models Denoising

Zhen Guo, Shangdi Yu
NeurIPS 2023 on Generative AI for Education.

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).

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).

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, Xiaoze Liu, Yuan Wang, Shi-Jing Gong, Hao Zeng, Hua Zhang, Athos Petrou
Nature Communications (2023).

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).


System and Method for Real-Time Determination of Particle Size Distributions in Dry Powders

Qihang Zhang, Ajinkya Pandit, Allan S. Myerson, George Barbastathis, Janaka C. Gamekkanda Gamaethige, Richard D. Braatz, and Zhen Guo


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]


Fall 2020: Teaching Assistant, MIT

6.728: Applied Quantum and Statistical Physics


MIT Chinese Entrepreneur Organization