About

I am a graduate student advised by Andrew J. Blumberg and Itsik Pe'er. My research interests are geometric/topological data analysis and computational biology.

Education

Ph.D. in Computer Science
Columbia University (2020 - present)

M.S. in Computer Science
Columbia University (2020 - 2022)

B.A. in Mathematics
University of California, Berkeley (2016 - 2020)

Teaching

I am not teaching this semester.

In the past, I was a:

TA for COMS 4771: Machine Learning (Su22)

TA for COMS 3251: Computational Linear Algebra (Su22)

instructor for COMS W3203-001: Discrete Mathematics (Fa21)

TA for COMS W4995-004: Geometric Data Analysis (Sp21)

In spring 2022, I helped with organizing a seminar on Non-Euclidean Embeddings in Computational Biology.

Prior to Columbia, I was a part of the wonderful teaching community at UC Berkeley:

co-instructor for CS70: Discrete Mathematics and Probability Theory (Su20)

TA for CS70: Discrete Mathematics and Probability Theory (Su18, Sp19)

TA for CS170: Algorithms and Complexity Theory (Fa18)

Research

CellStitch: 3D Cellular Anisotropic Image Segmentation via Optimal Transport [Paper]
Yining Liu, Yinuo Jin, Elham Azizi, Andrew J. Blumberg
BMC Bioinformatics, 2023

A Python library for probabilistic analysis of single-cell omics data [Paper]
A. Gayoso, R. Lopez, G. Xing, P. Boyeau, V.V.P. Amiri, J. Hong, K. Wu, M. Jayasuriya, E. Melhman, M. Langevin, Y. Liu, J. Samaran, G. Misrachi, A. Nazaret, O. Clivio, C. Xu, T. Ashuach, M. Lotfollahi, V.Svensson, E. da Veiga Beltrame, C. Talavera-Lopez, L. Pachter, F.J. Theis, A. Streets, M.I. Jordan, J. Regier, N. Yosef
Nature Biotechnology, 2022

A Recovery Algorithm and Pooling Designs for One-Stage Noisy Group Testing under the Probabilistic Framework [Paper]
Yining Liu, Sachin Kadyan, Itsik Pe'er
International Conference on Algorithms for Computational Biology (AlCoB), 2021