Hello and Welcome! I do research in optimization, signal processing and statistics, along with various computational problems more generally. I got my PhD in Electrical Engineering from Stanford under Emmanuel Candès in 2021, followed by 1-year postdoc at UT Austin. Earlier I graduated with two bachelors (in Electrical Engineering + Statistics) and a minor in Applied Math in 2015 from Rice University, and spent a lovely summer at EPFL before grad school.
- Subgradient Descent Learns Orthogonal Dictionaries, ICLR '19. with Yu Bai, Ju Sun
- Near-Optimal Method For Highly Smooth Convex Optimization, COLT '19. with Sébastien Bubeck, Yin Tat Lee, Yuanzhi Li, Aaron Sidford
- Complexity of Highly Parallel Non-Smooth Convex Optimization, NeurIPS '19 (Spotlight Presentation). with Sébastien Bubeck, Yin Tat Lee, Yuanzhi Li, Aaron Sidford
- Optimizing Black-box Metrics with Adaptive Surrogates, ICML '20 (work done while intern@Google Research). with Oliver Adigun, Hari Narasimhan, Mahdi Milani Fard, Maya Gupta
- Acceleration with a Ball Optimization Oracle, NeurIPS '20 (Oral Presentation). with Yair Carmon, Arun Jambulapati, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian
- Learning the Truth from Only One Side of the Story, AISTATS '21. with Heinrich Jiang, Aldo Pacchiano
- Randomized Alternating Direction Methods for Efficient Distributed Optimization. with Emmanuel Candès, Mert Pilanci
- Mirror Langevin Monte Carlo: the Case Under Isoperimetry, NeurIPS '21.
- Near-Isometric Properties of Kronecker-Structured Random Tensor Embeddings, NeurIPS '22.
- On the Dissipation of Ideal Hamiltonian Monte Carlo Sampler.
- Fourier Interpolation with Magnitude Only, SampTA '23.
- From Estimation to Sampling for Bayesian Linear Regression with Spike-and-Slab Prior, Draft.
Teaching & Mentorship
I had fun TAing for High-dimensional Statistics, Convex Optimization, Machine Learning classes in the past, and serving as a technical mentor for the Data Science for Social Good program at Stanford. I quite enjoy applications of statistics and algorithmic tools for answering social science questions.
Feel free to email me at qjiang2 AT alumni DOT stanford DOT edu. Off research, you will most likely find me lost in books, art or nature (and these days, more philosophy than I probably need).