Publications

A full list of my publications can be found on Google Scholar. 

Methodologies:

1. Li, Sijia, Peter B. Gilbert, Rui Duan, and Alex Luedtke. "Data fusion using weakly aligned sources." Journal of the American Statistical Association (2025): 1-11.

2. Li, Sijia, and Alex Luedtke. "Efficient estimation under data fusion." Biometrika 110, no. 4 (2023): 1041-1054.

3. Li, Xiudi, Sijia Li, and Alex Luedtke. "Estimating the efficiency gain of covariate-adjusted analyses in future clinical trials using external data." Journal of the Royal Statistical Society Series B: Statistical Methodology 85, no. 2 (2023): 356-377.

4. Stein-O’Brien, Genevieve*, Luciane T. Kagohara*, Sijia Li*, Manjusha Thakar, Ruchira Ranaweera, Hiroyuki Ozawa, Haixia Cheng et al. "Integrated time course omics analysis distinguishes immediate therapeutic response from acquired resistance." Genome medicine 10 (2018): 1-22.

Commentary:

1. Li, Sijia*, Xiudi Li*, and Alex Luedtke. "Discussion of Kallus (2020) and Mo, Qi, and Liu (2020): New Objectives for Policy Learning." Journal of the American Statistical Association 116, no. 534 (2021): 680-689.

Applications:

1. Puia-Dumitrescu, M., B. A. Comstock, S. Li, P. J. Heagerty, K. M. Perez, J. B. Law, T. R. Wood, S. Gogcu, D. E. Mayock, and S. E. Juul. "Assessment of 2-Year Neurodevelopmental Outcomes in Extremely Preterm Infants Receiving Opioids and Benzodiazepines. JAMA Network Open, 4 (7), 1–14." (2021).

2. Weiss, E. M., A. E. Olszewski, K. F. Guttmann, B. E. Magnus, S. Li, and A. R. Shah. "Parental factors associated with the decision to participate in a neonatal clinical trial. JAMA network open. 2021; 4 (1): e2032106–e2032106."

3. Weiss, Elliott Mark, Katherine F. Guttmann, Aleksandra E. Olszewski, Brooke E. Magnus, Sijia Li, Scott YH Kim, Anita R. Shah et al. "Parental enrollment decision-making for a neonatal clinical trial." The Journal of pediatrics 239 (2021): 143-149.

4. Turley, Christine B., LaKesha Tables, Trevon Fuller, Lisa J. Sanders, Hyman Scott, Amaran Moodley, Amanda Woodward Davis et al. "Modifiers of COVID-19 vaccine efficacy: results from four COVID-19 prevention network efficacy trials." Vaccine 41, no. 33 (2023): 4899-4906.

5. Juul, Sandra E., Thomas R. Wood, Kendell German, Janessa B. Law, Sarah E. Kolnik, Mihai Puia-Dumitrescu, Ulrike Mietzsch et al. "Predicting 2-year neurodevelopmental outcomes in extremely preterm infants using graphical network and machine learning approaches." EClinicalMedicine 56 (2023).

Preprints:

1. Li, Sijia, and Rui Duan. "Efficient collaborative learning of the average treatment effect under data sharing constraints." arXiv preprint arXiv:2410.02941 (2024). Invited revision at Biometrics.

2. Li, Xiudi*, and Sijia Li*. "Efficient Inference for Covariate-adjusted Bradley-Terry Model with Covariate Shift." arXiv preprint arXiv:2503.18256 (2025). Submitted.

3. Gu, Tian, Sijia Li and Rui Duan. "On the connections among three transfer learning paradigms." Accepted at Stat.

4. Li, Xiudi*, and Sijia Li*. "Efficient Inference for Time-to-Event Outcomes by Integrating Right-Censored and Current Status Data." arXiv preprint arXiv:2503.18256 (2025). 

Lastly, if you are interested in my undergraduate work in pore-forming peptides:

Li, Sijia, Sarah Y. Kim, Anna E. Pittman, Gavin M. King, William C. Wimley, and Kalina Hristova. "Potent macromolecule-sized poration of lipid bilayers by the macrolittins, a synthetically evolved family of pore-forming peptides." Journal of the American Chemical Society 140, no. 20 (2018): 6441-6447.

*: contributed equally