my profile

About Me

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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 Jan/May 2025 and I am looking for job opportunities in industry. Seeking a role in software engineering/data science/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.
I develop scalable solutions and software for challenging problems with ultra-large data in biology where advanced computer science is needed.

My research interests include

News

  1. [Decemeber 7, 2023] EMMA has been formally published on Algorithms for Molecular Biology. DOI link
  2. [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!
  3. [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.
  4. [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

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: A New Method for Computing Multiple Sequence Alignments Given a Constraint Subset Alignment. Accepted for publication in Algorithms for Molecular Biology. (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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