CV

Education

• Ph.D. candidate in Biomedical Engineering, University of Michigan, USA

  August 2022 - Present

• M.S. in Biomedical Engineering, University of Michigan, USA

  August 2020 - May 2022

• B.S. in Computer Engineering, Chiang Mai University, Thailand

  August 2015 - May 2019

Research experience

• November 2020 - Present: Graduate student research assistant @ Lana Garmire Group

  University of Michigan, Ann Arbor, MI, USA

  • Using machine learning and deep learning approaches for biomarker discovery and predictive analysis
  • Performing single-cell RNA sequencing data analysis
  • Performing spatial transcriptomics data analysis
  • Contributing to proposals, reports, and manuscripts. Carrying out literature reviews of bioinformatics, cancer, and placental biology
  • My current research interests include, but are not limited to, single-cell and spatial transcriptomic analysis of cancer and placenta tissues, integrating spatial transcriptomics with graph neural network models for cell-cell communication inference, and drug repurposing using spatial transcriptomic data.

• January 2020 - June 2020: Undergraduate student research assistance @ Computational Intelligence Laboratory

  Chiang Mai University, Chiang Mai, Thailand

  • Collaborated with a multi-disciplinary team to identify variants in patients with hereditary gingival fibromatosis

• June 2018 - July 2018: Undergraduate student research assistance @ SHIMODA Laboratory

  Kyoto University, Kyoto, Japan

  • Contributed to the development of the haptic feedback device for a realistic experience of grinder accidents

• June 2017 - August 2017: Undergraduate student research assistance @ OASYS Research Group

  Chiang Mai University, Chiang Mai, Thailand

  • Responsible for general hardware tasks
  • Contributed to the optimization of the device for measuring the depth of the riverbed

Presentations

• Lahiri, S., Unjitwattana, T., Dong, K., Du, Y., Girard, S., & Garmire, L. (2024, May 18). Building a rigorous placenta atlas to enable pregnancy research [Poster presentation]. DahShu 2024 Data Science Symposium, Michigan State University, Michigan.
• Unjitwattana, T., Huang, Q., Du, Y., Yang, Y., Zhou, M., & Garmire, L. (2023, October 6). Cell origin deconvolution pipeline for scRNA-seq data [Poster presentation]. MidAtlantic Bioinformatics Conference 2023, University of Pennsylvania, Pennsylvania.
• Unjitwattana T., Yadav S., He B., & Garmire, L. (2022, July 10). Single Cell Pathway Embedding Neural Network (scPENN) for Single Cell RNA-Seq Analysis [Poster presentation]. Intelligent Systems for Molecular Biology (ISMB) 2022.

Publications

[Preprint] Linking Spatial Omics to Patient Phenotypes at Population Scale Using BSNMani

Single-cell RNA-seq data have prevalent blood contamination but can be rescued by Originator, a computational tool separating single-cell RNA-seq by genetic and contextual information

Honors & awards

• Thai Government Science and Technology Scholarship
  • Issued by The Ministry of Higher Education, Science, Research Innovation; The Royal Thai Government · Dec 2019

Skills

• Bioinformatics
  • single cell RNA (scRNA)-seq analysis
  • Spatial transcriptomic analysis
• Machine learning
• Deep learning
• Electronics & hardware design
• Hardware development
  • Arduino IDE