He Jia (贾赫)

Quantitative Portfolio Manager, with PhD in Astrophysics at Princeton.

Hello! My name is He Jia (贾赫, pronounced as /hɜ: dʒɑ:/ in Chinese, which roughly means famous businessman 😅). Born in Jingmen in 1998, I moved to Shenzhen in 2008 with my family, until I went to Beijing for college in 2016 and then Princeton for graduate school in 2020 (physically in 2021 though, due to the pandamic).

I was on the 2024/25 astrophysics postdoc job market, but I made a last-minute decision to give up the postdoc opportunities and leave academia, for now, to join a quantitative trading startup as a Portfolio Manager. I defended my PhD in Astrophysics on July 29, 2025, with Prof. Eliot Quataert as my main advisor. Unpopular opinion: quantitative trading can be more quantitative than some, although certainly not all, branches of astrophysics.

I am still a somewhat-active, part-time astrophysicist, broadly interested in using advanced statistical techniques to optimally extract quantitative information from astrophysical data, with the goal of driving new discoveries. While I was initially trained as a cosmologist, a field I continue to contribute to, my research has expanded to include black holes since graduate school. My focus on these two areas stems from the vast amounts of increasingly precise data being generated by ongoing and upcoming projects, where sophisticated statistical and machine learning models are crucial for unlocking the deeper insights that would otherwise remain inaccessible. Beyond cosmology and black holes, I am also open to exploring new areas depending on where the most exciting science opportunities are.

I was a visiting undergraduate researcher at UC Berkeley during parts of 2018 and 2019, working with Prof. Uroš Seljak. Unfortunately, I still owe him a BayesFast paper. This paper never came out because I wanted to release it together with the code. Back in 2020, however, there was no suitable autodiff framework available, so I ended up hand-writing my own, which was later criticized for not being very user-friendly. By the time JAX significantly improved its latency in 2022, Uroš’s group had already moved on to developing more general methods, although I believe BayesFast remains the most efficient option for simpler problems.

I am a speed enthusiast with a passion for aviation and auto racing. As a dual-rated FAA private pilot, I fly airplanes as well as helicopters. Aircraft I have flown include Cessna 172, Diamond DA40 (my favorite airplane so far), Cirrus SR20, Robinson R22, Robinson R44, and Cabri G2 (my favorite helicopter so far). When I want some fun on the ground, I enjoy driving cars like Tesla Model 3 Performance and Xiaomi SU7 Ultra on race tracks.

I play tennis and am currently self-rated NTRP 3.5. My favorite band is The Landlord’s Cats.