About Me

(Github) (Google Scholar) (Linkedin)

My name is Chengze Shen (CV) and I am a fifth-year (started 2020) PhD student @ UIUC Computer Science program. My advisor is Tandy Warnow.

QUAL: PASSED
PRELIM: PASSED
I expect to graduate by Summer 2025 and I am looking for job opportunities in industry. Seeking a role in software engineering/machine learning/algorithmic design to apply extensive research and technical expertise in developing high-performance, scalable solutions.

My Research

I am a computer scientist with strong programming skills and a broad background in bioinformatics and machine learning techniques.
I develop scalable solutions and software for challenging problems with ultra-large data in biology, sometimes using techniques in machine learning and deep learning.

My research interests include

• Machine learning
• Bioinformatics
• Multiple sequence alignment
• Microbiome analysis
• Metagenomics

Talks and Presentations

1. [November 11, 2024] PPoSS Meeting, Clusterings and Multiple Sequence Alignments.
2. [September 4, 2023] ACM-BCB/WABI 2023, EMMA: accepted paper presentation. Link
3. [September 1, 2022] Sandia National Lab Presentation on Scalable Alignment and Tree Estimation. Link

News

1. [March 2, 2025] TIPP3 has beeen accepted for publication at PLOS Computational Biology!
2. [Decemeber 7, 2023] EMMA has been formally published on Algorithms for Molecular Biology. DOI link
3. [November 19, 2023] "EMMA: A New Method for Computing Multiple Sequence Alignments Given a Constraint Subset Alignment" has been accepted for publication in Algorithms for Molecular Biology!
4. [September 3-6, 2023] Attended ACM-BCB/WABI 2023 for presentation and poster session for new multiple sequence alignment research results - EMMA. See Publications for the EMMA paper.
5. [April 2023] Currently collaborating with Kelly P. Williams from Sandia National Lab on developing alignment methods that deal with missing clade in input data.

Teaching Assistantship

• Fall 2020: CS125 (An Introduction to Computer Science)
• Spring 2021: CS125

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2025

1. Chengze Shen, Eleanor Wedell, Mihai Pop, and Tandy Warnow. TIPP3 and TIPP3-fast: Improved Abundance Profiling in Metagenomics. Accepted for publication at PLOS Computational Biology. (Link TBD)

2023

1. Chengze Shen, Baqiao Liu, Kelly P. Williams, and Tandy Warnow. EMMA: A New Method for Computing Multiple Sequence Alignments Given a Constraint Subset Alignment. Algorithms for Molecular Biology 18, no. 1 (December 7, 2023): 21. (Link)
2. Eleanor Wedell, Chengze Shen, and Tandy Warnow. BATCH-SCAMPP: Scaling phylogenetic placement methods to place many sequences. Under review at IEEE Transaction Computational Biology and Bioinformatics. An early version was published in Workshop in Algorithms for Bioinformatics 2023. (Link)
3. Mihir Mongia*, Chengze Shen*, Arash Gholami Davoodi, Guillaume Marcais, and Hosein Mohimani. Large Scale Sequence Alignment via Efficient Inference in Generative Models. Scientific Reports 13, no. 1 (May 4, 2023): 7285. (Link)
4. Minhyuk Park, Stefan Ivanovic, Gillian Chu, Chengze Shen, and Tandy Warnow. UPP2: Fast and Accurate Alignment of Datasets with Fragmentary Sequences.” Bioinformatics 39, no. 1 (January 1, 2023): btad007. (Link)

2022

1. Chengze Shen, Minhyuk Park, and Tandy Warnow. WITCH: Improved Multiple Sequence Alignment Through Weighted Consensus Hidden Markov Model Alignment. Journal of Computational Biology, May 17, 2022. (Link) (pdf)
2. Chengze Shen, Paul Zaharias, and Tandy Warnow, MAGUS+eHMMs: improved multiple sequence alignment accuracy for fragmentary sequences, Bioinformatics, Volume 38, Issue 4, 15 February 2022, Pages 918-924. (Link) (pdf)