Yang Lu's Homepage

Postdoctoral Fellow

Department of Genome Sciences
University of Washington

Biography

I am on the job market. If you have any openings related to ML and CompBio, please get in touch with me!

I am a postdoctoral fellow at the Noble Research Lab in University of Washington. Previously, I earned my Ph.D. in Computational Biology and Bioinformatics from University of Southern California. Before that, I received my M.S. and B.S. degrees in Computer Science and Engineering from Shanghai Jiao Tong University.

My research aims to formulate the biological problems in genomics and proteomics as interesting computational problems and to develop novel machine learning to solve these problems. I am particularly interested in developing interpretability methods to make sense of complex machine learning models to analyze complex biological data. I am also interested in finding both scientifically interesting and statistically confident hypotheses by interpreting these models. I have published papers in prestigious conferences and journals from computational biology and machine learning, such as Bioinformatics, Nucleic Acids Research, ISMB, NeurIPS, ICML, etc.

Research Interests

Computational Biology:

Single-cell genomics
Mass spectrometry-based proteomics
Metagenomics

Machine Learning:

Interpretable machine learning
Reproducible (error-controlled) machine learning
Heterogeneous data integration

Education

Ph.D. in Computational Biology and Bioinformatics, 2017
University of Southern California
M.S. in Computer Science and Engineering, 2013
Shanghai Jiao Tong University
B.S. in Computer and Software Engineering, 2010
Shanghai Jiao Tong University

Publications as leading author

YY Lu and WS Noble. A wider field of view to predict expression.
Nature Methods, 18:1155-1156, 2021.
[Article]
YY Lu*, W Guo*, X Xing, WS Noble. DANCE: Enhancing saliency maps using decoys.
Proceedings of the 38th International Conference on Machine Learning (ICML), 2021.
[Paper] [Slides] [Poster] [Code]
YY Lu, T Yu, G Bonora, WS Noble. ACE: Explaining cluster from an adversarial perspective.
Proceedings of the 38th International Conference on Machine Learning (ICML), 2021.
[Paper] [Slides] [Poster] [Code] [Datasets]
YY Lu, J Bilmes, RA Rodriguez-Mias, J Villen, WS Noble. DIAmeter: Matching peptides to data-independent acquisition mass spectrometry data.
Proceedings of the 29th International Conference on Intelligent Systems for Molecular Biology (ISMB), 2021.
Bioinformatics, in press, 2021.
[Paper] [Slides] [Poster] [Code]
YY Lu*, J Bai*, Y Wang, Y Wang, F Sun. CRAFT: Compact genome Representation towards large-scale Alignment-Free daTabase.
Bioinformatics, 37(2):155-161, 2021.
[Paper] [Code]
J Schreiber*, YY Lu*, WS Noble. Ledidi: Designing genomic edits that induce functional activity.
ICML Workshop on Computational Biology, 2020.
[Paper] [Slides] [Tutorial] [Code]
YY Lu*, Y Fan*, J Lv, WS Noble. DeepPINK: reproducible feature selection in deep neural networks.
Proceedings of the 32nd International Conference on Neural Information Processing Systems (NeurIPS), 2018.
[Paper] [Video] [Poster] [Code] [Datasets]
YY Lu. Big Data Analytics in Metagenomics: Integration, Representation, Management, and Visualization.
Doctoral thesis, University of Southern California, 2017.
[Thesis] [Slides]
YY Lu, J Lv, JA Fuhrman, F Sun. Towards enhanced and interpretable clustering/classification in integrative genomics.
Nucleic Acids Research, 45(20):e169, 2017.
[Paper] [Slides] [Code]
YY Lu, K Tang, J Ren, JA Fuhrman, MS Waterman, F Sun. CAFE: aCcelerated Alignment-FrEe sequence analysis.
Nucleic Acids Research, 45(W1):W554-W559, 2017.
[Paper] [Code] [Executable]
YY Lu, T Chen, JA Fuhrman, F Sun. COCACOLA: binning metagenomic contigs using sequence COmposition, read CoverAge, CO-alignment and paired-end read LinkAge.
Bioinformatics, 33(6):791-798, 2017.
[Paper] [Slides] [Poster] [Code]

*= co-first author

Full publication list

Experiences

2018/01 -- Present. Postdoctoral Fellow. University of Washington
Advisor: Prof. William Stafford Noble
2015/08 -- 2017/07. Research Assistant. University of Southern California
Advisor: Prof. Fengzhu Sun
2011/06 -- 2011/11. Research Intern. Microsoft Research Asia, Beijing, China
Mentor: Dr. Qingwei Lin
2010/11 -- 2011/05. Software Engineer Intern. Microsoft Bing, Shanghai, China
2010/04 -- 2011/08. Software Engineer Intern. Tencent, Shanghai, China
2009/08 -- 2009/11. Software Engineer Intern. Ericsson, Shanghai, China

Academic Services

Program Committee Member: CompMS@ISMB/ECCB 2021, SC@ACM-BCB 2021, MLCB 2021
Journal Reviewer: Nature Methods, Nature Communications, Nature Machine Intelligence, Genome Biology, Nucleic Acids Research, Bioinformatics, Briefings in Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics, BMC Bioinformatics, Frontiers in Genetics, Journal of Proteome Research
Conference Reviewer: NeurIPS, ICML, ICLR, AISTATS, AAAI, RECOMB, ISMB, APBC

Awards & Scholarships

2021/08. Most Innovative Presentation Award. Machine-learning Methods for Single-cell Analysis Workshop, ACM-BCB 2021
2013 -- 2015. Provost's Fellowship. University of Southern California
2010 -- 2013. Graduate Fellowship. Shanghai Jiao Tong University

Teaching Assistant

2015. Statistics for the Biological Sciences.
Department of Biological Science, University of Southern California.
2012. Introduction to Artificial Intelligence.
Department of Computer Science and Engineering, Shanghai Jiao Tong University.
2011. Introduction to Bioinformatics.
Department of Computer Science and Engineering, Shanghai Jiao Tong University.

Department of Genome Sciences University of Washington

Research Interests

Education

Department of Genome Sciences
University of Washington