About Me

(Github) (Google Scholar) (Linkedin)

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

QUAL: PASSED
PRELIM: PASSED
I expect to graduate in Summer/Spring 2024 and I am looking for job opportunities in the bioinformatics industry. I am also interested in solving optimization problems in general and fiddling with large data (Data Scientist and other research positions)!

My Research

I am a computer scientist with strong programming skills and a broad background in bioinformatics.
I want to develop scalable solutions and software for challenging problems with ultra-large data in biology where advanced computer science is needed.

My research interests include

• Bioinformatics
• Multiple sequence alignment
• Microbiome analysis
• Metagenomics
• GPU computing

News

1. [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.
2. [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

Publications

1. 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)
2. 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)
3. 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)
4. Chengze Shen, Baqiao Liu, Kelly P. Williams, and Tandy Warnow. EMMA: Adding Sequences into a Constraint Alignment with High Accuracy and Scalability. WABI 2023, Houston TX. (Link)
5. 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)

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