I am an assistant professor in the Department of Biostatistics at Harvard T.H. Chan School of Public Health. I obtained my Ph.D. in Operations Research and Financial Engineering at Princeton University.

Preprints

Contextual Online Uncertainty-Aware Preference Learning for Human Feedback Nan Lu, E. X. Fang, J. Lu [arXiv]

Ranking of Large Language Model with Nonparametric Prompts Z. Wang, Y. Han, E. X. Fang, L. Wang, J. Lu [arXiv]

The Wreaths of KHAN: Uniform Graph Feature Selection with False Discovery Rate Control J. Liang, Y. Liu, D. Zhou, S. Zhang, J. Lu [arXiv] [Package]

Scalable Gaussian Process Regression Via Median Posterior Inference for Estimating Multi-Pollutant Mixture Health Effects A. Sonabend, J. Zhang, J. Schwartz, B. A. Coull, J. Lu [arXiv] [Package]

Inference of Dependency Knowledge Graph for Electronic Health Records Z. Xu, Z. Gan, D. Zhou, S. Shen, J. Lu, T. Cai [arXiv]

FADI: Fast Distributed Principal Component Analysis With High Accuracy for Large-Scale Federated Data S. Shen, J. Lu, X. Lin [arXiv] [Package] ASA Statistical Learning and Data Science Paper Award

Publications [by Topic]

ARCH: Large-scale Knowledge Graph via Aggregated Narrative Codified Health Records Analysis Z. Gan, D. Zhou, E. Rush, V. Panickan, Y. Ho, G. Ostrouchov, Z. Xu, S. Shen, X. Xiong, K. Greco, C. Hong, C. Bonzel, J. Wen, L. Costa, T. Cai, E. Begoli, Z. Xia, M G, K. Liao, K. Cho, T. Cai, J. Lu Journal of Biomedical Informatics, 2025+ [Package]

DOME: Directional Medical Embedding Vectors from Electronic Health Records. J. Wen, H. Xue, E. Rush, V. A. Panickan, T. Cai, D. Zhou, Y. Ho, L. Costa, E. Begoli, C. Hong, J. M. Gaziano, K. Cho, K. Liao, J. Lu, T. Cai Journal of Biomedical Informatics, 162, 104768, 2025 [Journal]

StarTrek: Combinatorial Variable Selection with False Discovery Rate Control L. Zhang and J. Lu The Annals of Statistics 52.1: 78-102. 2024 [Journal] [Package]

Federated Offline Reinforcement Learning D. Zhou, Y. Zhang, A. Sonabend, Z. Wang, J. Lu, T. Cai Journal of the American Statistical Association, 2024. [Journal] [Package]

Nonparametric Additive Value Functions: Interpretable Reinforcement Learning with an Application to Surgical Recovery P. Emedom-Nnamdi, T. Smith, J-P. Onnela, J. Lu Annals of Applied Statistics, 19(2): 1448-147. 2025 [arXiv] [Journal]

LATTE: Label-efficient incident phenotyping from longitudinal electronic health records J. Wen, J, Hou, CL Bonzel, ..., J. Lu, K. Cho, T. Cai Patterns, 5(1), 2024. [Journal] [Package]

Multi-source Learning via Completion of Block-wise Overlapping Noisy Matrices D. Zhou, T. Cai, J. Lu Journal of Machine Learning Research. 24(221), 1-43, 2023. [Journal] [Package] ASA Statistical Learning and Data Science Paper Award

Prompt Discriminative Language Models for Domain Adaptation K. Lu, P. Potash, X. Lin, Y. Sun, Z. Qian, Z. Yuan, T. Naumann, T. Cai, J. Lu Proceedings of the 5th Clinical Natural Language Processing Workshop, pp. 247-258. 2023. [Journal]

Inferring Differential Hub Nodes on Differential Gaussian Graphical Models. X. Zhou, K.M. Tan, J. Lu Statistica Sinica. 35(4), 2023. [Journal]

Combinatorial-Probabilistic Trade-Off: Community Properties Test in the Stochastic Block Models S. Shen, J. Lu Conference version: International Conference on Learning Representations (spotlight paper). [Video] Journal version: IEEE Transactions on Information Theory, 2023. [Journal] WNAR Best Paper Award

Inference on the optimal assortment in the multinomial logit model X. Chen S. Shen, E. Fang, J. Lu ACM Conference on Economics and Computation, 2023. [arXiv] [Journal]

Graph over-parameterization: Why the graph helps the training of deep graph convolutional network Y Lin, S Li, J Xu, J Xu, D Huang, W Zheng, Y Cao, J. Lu Neurocomputing, 534, 77-85. 2023. [Journal]

Multimodal representation learning for predicting molecule–disease relations J Wen, X Zhang, E Rush, V A Panickan, X Li, T Cai, D Zhou, Y Ho, L Costa, E Begoli, C Hong, J Gaziano, K Cho, J. Lu, K Liao, M Zitnik, T Cai Bioinformatics, 39(2), btad085. 2023. [Journal]

Lagrangian Inference for Ranking Problems Y. Liu, E.X. Fang, J. Lu Operations Research 71.1: 202-223. 2023 [arXiv] [Journal] [Package]

Penalized estimation of frailty-based illness–death models for semi-competing risks H.T. Reeder, J. Lu, S.Haneuse Biometrics, 79(3), 1657-1669, 2023 [Journal]

Multiview Incomplete Knowledge Graph Integration with Application to Cross-institutional EHR Data Harmonization D. Zhou, Z. Gan, X. Shi, A. Patwari, E. Rush, CL. Bonzel, V. A. Panickan, C. Hong, YL. Ho, T. Cai, L. Costa, X. Li, V.M. Castro, S.N. Murphy, G. Brat, G. Weber, P. Avillach, J.M. Gaziano, K. Cho, K. Liao, J. Lu*, T. Cai* (*: co-senior author) Journal of Biomedical Informatics 133: 104147. 2022. [Journal]

Clinical Knowledge Extraction via Sparse Embedding Regression (KESER) with Multi-Center Large Scale Electronic Health Record Data. C. Hong, E. Rush, M. Liu, D. Zhou , J. Sun, A. Sonabend, V. M. Castro, P. Schubert, V. Panickan, T. Cai, L. Costa, Z. He, N. Link, R. Hauser, J.M. Gaziano, S. Murphy, G. Ostrouchov, Y. Ho, E. Begoli, J. Lu, K. Cho, K. Liao, T. Cai NPJ digital medicine 4, no. 1, 151. 2021 [Journal] [Package]

Heteroskedastic and imbalanced deep learning with adaptive regularization. K. Cao, Y. Chen, J. Lu, N. Arechiga, A. Gaidon, T. Ma International Conference on Learning Representations. 2021 [arXiv]

Progression of traction bronchiectasis/bronchiolectasis in interstitial lung abnormalities is associated with increased all-cause mortality: Age Gene/Environment Susceptibility-Reykjavik Study. H. Takuya, T. Hida, M. Nishino, J. Lu, R. Putman, E.F. Gudmundsson, A. Hata European journal of radiology open 8 100334, 2021 [Journal]

Interstitial lung abnormalities in patients with stage I non-small cell lung cancer are associated with shorter overall survival: the Boston lung cancer study. H. Tomoyuki, A. Hata, J. Lu, V. Valtchinov, T. Hino, M. Nishino, H. Honda, N. Tomiyama, D. C. Christiani, H. Hatabu. Cancer Imaging 21, no. 1 1-7, 2021 [Journal]

Inter-Subject Analysis: Inferring Sparse Interactions with Dense Intra-Graphs C. Ma, J. Lu, H. Liu Journal of the American Statistical Association, 116(534), 746-755, 2021 [arXiv][Journal] ICSA 2017 Student Paper Award

Robust Scatter Matrix Estimation for High Dimensional Distributions with Heavy Tails J. Lu, Fan Han, and Han Liu IEEE Transactions on Information Theory. vol. 67, no. 8, pp. 5283-5304, 2021. [paper][Journal]

Estimating and inferring the maximum degree of stimulus-locked time-varying brain connectivity networks. KM Tan, J. Lu, T. Zhang, H. Liu Biometrics. Jun;77(2):379-390, 2020 [Journal]

Computational and Statistical Tradeoffs in Inferring Combinatorial Structures of Ising Model J. Ying, Z. Wang, J. Lu International Conference on Machine Learning, pp. 4901-4910. PMLR, 2020. [Journal]

Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation A. Sonabend W., J. Lu, L.A. Celi, T. Cai, P. Szolovits Advances in Neural Information Processing Systems 33: 18967-18977, 2020. [Journal]

Kernel Meets Sieve: Post-Regularization Confidence Bands for Sparse Additive Model J. Lu, M. Kolar, H. Liu. Journal of the American Statistical Association, 92:4, pages 875-893, 2020. [arXiv] [Journal] ASA Best Student Paper in Nonparametric Statistics Finalist

Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization X. Li, Z. Wang, J. Lu, R. Arora, J. Haupt, H. Liu, T. Zhao. IEEE Transactions on Information Theory, 65(6):3489-3514, 2019. [arXiv][Journal]

Combinatorial Inference for Graphical Models M. Neykov*, J. Lu*, H. Liu. (*: equal contribution) Annals of Statistics, 47(2), pp.795-827, 2018 [arXiv] [Journal]

Sketching Method for Large Scale Combinatorial Inference W. Sun, J. Lu, H. Liu. Advances in Neural Information Processing Systems 31, 10598-0607, 2018 [Journal]

Distributed Testing and Estimation under Sparse High Dimensional Models H. Battey, J. Fan, H. Liu, J. Lu, Z. Zhu. (alphabetical order) Annals of Statistics, 46(3), 1352-1382, 2018 [arXiv][Journal]

Post-Regularization Inference for Dynamic Nonparanormal Graphical Models J. Lu, M. Kolar, H. Liu. Journal of Machine Learning Research, 18, 1-78, 2018 [arXiv][Journal]

The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference H. Lu, Y. Cao, Z. Yang, J. Lu, H. Liu, Z. Wang. Proceedings of the 35th International Conference on Machine Learning, 80:3247-3256, 2018 [Journal]

Provable Sparse Tensor Decomposition W. Sun, J. Lu, H. Liu, G. Cheng. Journal of the Royal Statistical Society: Series B, 79(3), 899-916, 2017 [arXiv][Journal]

Application of the Strictly Contractive Peaceman-Rachford Splitting Method to Multi-block Separable Convex Programming B. He, H. Liu, J. Lu, X. Yuan (alphabetical order) Splitting Methods in Communication, Imaging, Science, and Engineering (In Roland Glowinski, Stanley J. Osher, Wotao Yin (Eds.)), Springer, 2017 [Journal]