TIANAO LI 李天骜

I'm a senior undergraduate student majoring in Electronic Engineering at Tsinghua University. I'm currently a research intern at the Bio Inspired Vision Lab at Northwestern University, advised by Prof. Emma Alexander. My research interest lies at the intersection of computational imaging, signal processing, and optimization. I'm especially interested in inverse problems, bio-inspired vision, and astronomical imaging. I was previously a research assistant at the Tsinghua Visual Intelligence and Computational Imaging Lab.

I graduated from Beijing No.4 High School in 2019.

Outside of research, I enjoy playing basketball and amateur astronomy. I spent three wonderful years at the Tsinghua Astronomy Society as a core member. I'm also a huge fan of the Golden State Warriors 🏆🏆🏆🏆 the HARRY POTTER series.

I'm looking for a PhD opportunity starting from fall 2023.

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We introduce a physics-informed deep learning approach to the Point Spread Function (PSF) deconvolution problem in galaxy surveys.

The Transiting Exoplanet Survey Satellite (TESS) is an all-sky survey mission led by MIT and NASA in search of exoplanets. A certain number of planet candidates (PC) discovered by TESS are not actual transiting exoplanets, which are usually referred as "false positives", therefore follow-up ground-based photometry is performed for verifications. We conduct ground-based transit photometry on two planets candidates declared in TESS, TOI-5278.01 and TOI-4439.01 with an 80cm telescope at Xinglong Observatory, P.R. China. Our data processing pipeline comprises of three parts: image reduction, aperture photometry and EXOFAST fit. For TOI-4439.01, our result is in accordance with TESS data, proving the exoplanet nature, while the EXOFAST fit did not converge for TOI-5278.01 due to low SNR of the light curve.

This repo contains my code and data for astronomical image reduction. The images were taken at Huairou, Beijing with a 25cm telescope of DoA. Targets include M13, M51, M3, etc.

Developed an algorithm to create a video from a given set of video clips and a piece of background music to best match the clips' audio rhythm with the background music. This project is implemented with Matlab.

Built an algorithm using Guassian Process Regression to predict the stock prices from previous observations. This project is implemented with Python and Scikit Learn.

Website template from Dr. Jon Barron