I graduated from the Department of Biostatistics at Harvard University in 2018. My advisors are Professor Franziska Michor and Professor James M. Robins. My current research lies in nonparametric, semiparametric and high-dimensional statistics, robust statistical methods, causal inference, computational and mathematical biology.
I am also interested in the theory of deep learning, estimation and inference in inverse problems and applying causal inference tools in biomedical research.
I will join the Institute of Natural Sciences (INS) at Shanghai Jiao Tong University (SJTU) in Fall 2020. I will also be affiliated with the School of Mathematical Sciences and the SJTU-YALE Joint Center for Biostatistics.
(You can also find my articles on my Google Scholar profile.) (Italic: co-first authorship)
LL, Rajarshi Mukherjee, James M Robins, and Eric Tchetgen Tchetgen. Adaptive estimation of nonparametric functionals. (2020+).
LL, Rajarshi Mukherjee, and James M Robins. On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning. In press in Statistical Science. Journal preprint.
LL, Rajarshi Mukherjee, and James M Robins. An assumption-lean skepticism test of inference validity for doubly robust functionals. Technical Report.
Statistical methodology and causal inference:
- LL, Zach Shahn, James M Robins and Andrea Rotnitzky. Efficient estimation of optimal regimes under a no direct effect assumption. (2020+).
Kimiyo N Yamamoto, LLL, Akira Nakamura, Hiroshi Haeno, and Franziska Michor. Stochastic evolution of pancreatic cancer metastases during logistic clonal expansion. JCO Clinical Cancer Informatics 3, (2019): 1-11.
Helena A Yu, Camelia Sima, Daniel Feldman, LLL, Bhavapriya Vaitheesvaran, Justin Cross, Charles M Rudin, Mark G Kris, William Pao, Franziska Michor, and Gregory J Riely. Phase 1 study of twice weekly pulse dose and daily low-dose erlotinib as initial treatment for patients with EGFR-mutant lung cancers. Annals of Oncology 28, no. 2 (2017): 278-284.
LLL, Justin Brumbaugh, Ori Bar-Nur, Zachary Smith, Matthias Stadtfeld, Alexander Meissner, Konrad Hochedlinger, and Franziska Michor. Probabilistic modeling of reprogramming to induced pluripotent stem cells. Cell Reports 17, no. 12 (2016): 3395-3406.
Philipp M Altrock, LLL, and Franziska Michor. The mathematics of cancer: integrating quantitative models. Nature Reviews Cancer 15, no. 12 (2015): 730-745.
Jasmine Foo, LLL, Kevin Leder, Markus Riester, Yoh Iwasa, Christoph Lengauer, and Franziska Michor. An evolutionary approach for identifying driver mutations in colorectal cancer. PLoS Computational Biology 11, no. 9 (2015): e1004350.
Statistical and Machine Learning Applications:
- Sheng’en Hu, Dawei Huo, Zhaowei Yu, Yujie Chen, Jing Liu, LL, Xudong Wu, and Yong Zhang. ncHMR detector: a computational framework to systematically reveal non-classical functions of histone modification regulators. Genome Biology 21, no. 1 (2020): 48.
Kyle S Smith, LLL, Shridar Ganesan, Franziska Michor, and Subhajyoti De. Nuclear topology modulates the mutational landscapes of cancer genomes. Nature Structural & Molecular Biology 24, no. 11 (2017): 1000-1006.
Michalina Janiszewska, LL, Vanessa Almendro, Yanan Kuang, Cloud Paweletz, Rita A Sakr, Britta Weigelt, Ariella B Hanker, Sarat Chandarlapaty, Tari A King, Jorge S Reis-Filho, Carlos L Arteaga, So Yeon Park, Franziska Michor, and Kornelia Polyak. In situ single-cell analysis identifies heterogeneity for PIK3CA mutation and HER2 amplification in HER2-positive breast cancer. Nature Genetics 47, no. 10 (2015): 1212-1219.
LL, Subhajyoti De, and Franziska Michor. DNA replication timing and higher-order nuclear organization determine single-nucleotide substitution patterns in cancer genomes. Nature Communications 4, (2013): 1502.
LL, Yiqian Zhang, Jianxing Feng, Ning Zheng, Junfeng Yin, and Yong Zhang. GeSICA: Genome segmentation from intra-chromosomal associations. BMC Genomics 13, no. 1 (2012): 164.
GeSICA: software link
- Qi Liu, Han Zhou, LL, Xi Chen, Ruixin Zhu, and Zhiwei Cao. Multi-target QSAR modelling in the analysis and design of HIV-HCV co-inhibitors: an in-silico study. BMC Bioinformatics 12, no. 1 (2011): 294.