Ethan Shaotran is a technology entrepreneur, AI researcher, and inventor known for his work in AI alignment, autonomous systems, and AI-powered productivity tools. He is the founder of Energize.ai, an AI venture focused on developing productivity and enterprise tools, and was a recipient of a grant from OpenAI for his work on democratic inputs to artificial intelligence. He is also a member of DOGE, a federal reform team led by Elon Musk. He attended Harvard University, where he conducted research at the John A. Paulson School of Engineering and Applied Sciences before leaving during his senior year to join the DOGE initiative. ^{[1] [2] [3]}

Education

Shaotran attended Harvard University, studying computer science and was affiliated with the John A. Paulson School of Engineering and Applied Sciences (SEAS). During his senior year, he left the university prior to completing his degree to join DOGE, a federal reform team under the Trump administration. ^[3] During his studies at the university, he also cross-registered for courses at the Massachusetts Institute of Technology (MIT) and Harvard Business School (HBS). Prior to his university studies, Shaotran was named a Research Science Institute (RSI) Scholar in 2019. ^{[1] [2]}​

Career

Shaotran's career began while he was still a student, with early work focused on deep learning applications and contributions to publications on the future of AI. He has founded the AI startup Energize.ai and has led several high-profile research and development projects, gaining recognition from organizations like OpenAI and xAI. In 2025, he joined the Department of Government Efficiency (DOGE), a federal reform team led by Elon Musk under the Trump administration. The program's goal is to bring tech-savvy individuals into government to improve efficiency and modernize federal technology; Shaotran was one of the young engineers recruited for this purpose. ^{[3] [4] [1] [2]}​

Early Work and Publications

In 2018, Shaotran authored the book Stock Prediction with Deep Learning, which was published via Amazon. The following year, he contributed to the book Stories from 2045: Artificial intelligence and the future of work, edited by Calum Chace. For this publication, Shaotran co-authored a case study titled "AI in Wall Street" in collaboration with Harvard's Future Society, which was formally announced on February 17, 2019. ^{[1] [2]}​

Academic Research and Energize.ai

Shaotran founded Energize.ai, an AI startup focused on developing enterprise and productivity tools designed to automate professional workflows. The venture's products include AI-powered scheduling assistants and email management tools, reflecting his interest in applying AI to practical business applications. During his time at Harvard SEAS, his research focused on autonomous systems. This work culminated in a published paper in 2021 for the IEEE International Conference on Autonomous Systems (ICAS). The paper, titled "Gesture Learning For Self-Driving Cars," detailed algorithms designed for autonomous vehicles and was co-authored with J. J. Cruz and V. J. Reddi. ^[1]​

AI Governance and OpenAI Grant

In 2024, Shaotran and his team were selected as one of ten grant recipients for OpenAI's Democratic Inputs to AI program. They received a $100,000 grant to develop "Aligned," a governance platform for Artificial General Intelligence (AGI) intended to explore methods for democratically steering machine learning models. ^{[1] [2]}​

The foundational research for this project was submitted to the preprint server arXiv in November 2023 in a paper titled "Aligned: A Platform-based Process for Alignment." The paper was co-authored by Shaotran, Ido Pesok, S. Jones, and E. Liu. On January 16, 2024, Shaotran announced the project's findings, reporting that their platform had achieved a 93% consensus on certain governance principles across a study involving 700 global users. Collaborators on the OpenAI grant project included Woj Zaremba, Teddy Lee, Jay Baxter, Vivian (@metaviv), Colin Megill, Andrew (@Werdnamai), and Michiel Bakker, alongside the team at Energize.ai. ^{[1] [2]}​

Software Development and Projects

Through Energize.ai and as an independent developer, Shaotran has released several AI-driven software projects.

Spark Email Assistant

On March 17, 2024, Shaotran showcased "Spark," an AI email assistant developed by his team at Energize.ai. The tool is designed to automate email correspondence and scheduling. A demonstration showed its capability to coordinate a meeting within a Gmail thread, create a Zoom call, and interpret time zone requirements. ^[2]​

macOS GPT-4 Integration

In February 2024, Shaotran developed and shared an open-source project that integrates GPT-4 directly with the macOS operating system. Created over a weekend, the tool allows users to issue natural language commands that the AI model executes live on the operating system. Shaotran cited AI researcher Andrej Karpathy as the inspiration for this project. ^[2]​

Recognitions and Public Appearances

Shaotran's work has been recognized at industry events and by major technology organizations. In January 2024, his work in AI governance was recognized with a grant from OpenAI's Democratic Inputs to AI program. Later that year, in October 2024, his team, "Team eXpect," was the runner-up at a hackathon hosted by xAI. The team, which included Ray Del Vecc and Giovanni D'Antoni, was awarded $5,000 in API credits for their performance. His performance at the xAI hackathon reportedly caught the attention of Elon Musk, leading to his recruitment into DOGE, a federal initiative to improve government efficiency with tech talent. He was profiled as one of the young engineers involved in the program in a February 2025 WIRED article. ^{[2] [3] [4]}

On October 26, 2017, Shaotran attended the MKT4Intel Machine Learning Conference, which was associated with the University of Toronto's Rotman School of Management and the Creative Destruction Lab. At the event, he met and was photographed with Canadian Prime Minister Justin Trudeau. ^[2]

Publications and Works

Books

• Stock Prediction with Deep Learning (2018) ^[1]
• Stories from 2045: Artificial intelligence and the future of work (2019) (as contributor) ^{[1] [2]}

Academic Papers

• Shaotran, E., Pesok, I., Jones, S., and Liu, E. (2023). "Aligned: A Platform-based Process for Alignment." arXiv. ^[1]
• Shaotran, E., Cruz, J. J., and Reddi, V. J. (2021). "Gesture Learning For Self-Driving Cars." 2021 IEEE International Conference on Autonomous Systems (ICAS). ^[1]