Pallavi Gupta

Pallavi's Research

Highlight Summary

Leveraging this data collected from older adults apartments in the past few years (as explained in background above), Pallavi is developing a semi-supervised machine learning application to unobtrusively detect abnormal patterns specific to respiratory disorders like Chronic Obstructive Pulmonary Disorder (COPD) during onset or early stages of COPD. As a graduate research data scientist she works with cross-functional teams to gather the clinical knowledge to understand the intricacies of the disease. Further, her work involves translating the clinical knowledge into the right set of signal processing techniques, robust feature engineering, machine learning and advanced analytics approaches to achieve the goal.

Open Access Paper: TBD

PhD Candidate, Informatics

Research Focus:

  • Machine Learning

  • Informatics

  • Sensor Data Analytics

  • Multi-modal modeling

Education

Graduate Certificate: Data Science and Analytics, University of Missouri (2021)

Master of Science: Bioinformatics and Computational Biology, Saint Louis University (2019)

Bachelors: Biotech Engineering

  • Lovely Professional University, Punjab, India (2010).

Publications

  1. Gupta, Pallavi, Omar Ibrahim, Marjorie Skubic, and Grant J. Scott. "Leveraging Unsupervised Machine Learning to Discover Patterns in Linguistic Health Summaries for Eldercare." In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 2180-2185. IEEE, 2021.

  2. Hammond, Pallavi Gupta, Parth Patel, Blake C. Meyers. "miRador: a fast and precise tool for the prediction of plant miRNAs." Accepted (November 2022) in Plant Physiology.

  3. Baldrich, P., Bélanger, S., Kong, S., Pokhrel, S., Tamim, S., Teng, C., Schiebout, C., Gurazada, S.G.R., Gupta, P., Patel, P. and Razifard, H., 2022. The evolutionary history of small RNAs in Solanaceae. Plant Physiology, 189(2), pp.644-665. 3. Reza K.

  4. Yang, Yongil, Cory Gardner, Pallavi Gupta, Yanhui Peng, Cristiano Piasecki, Reginald J. Millwood, Tae-Hyuk Ahn, and C. Neal Stewart Jr. "Novel Candidate Genes Differentially Expressed in Glyphosate-Treated Horseweed (Conyza canadensis)." Genes 12, no. 10 (2021): 1616.