Jessica Kim

Ann Arbor, MI · (734) 249-0544 · jessjkim@umich.edu

Data analyst with 3 years of experience in data mining, data analysis and management in clinical research and 1 year of experience in applied machine learning and natural language processing in healthcare

Experience

Graduate Student Research Assistant

NLP4Health | University of Michigan
  • Designed list of computable phenotypes that can be used to build algorithm to analyze EHR data and help detect dementia & Alzheimer’s Disease in potential patients
  • Developed rule-based pattern-matching system to extract definitions and contexts from scholarly manuscripts using Python regular expressions to design knowledge maps that would facilitate researchers in making full use of knowledge in the field
May 2021 - Present

Neuroimaging Data Analyst

fNIRS Laboratory | University of Michigan
  • Facilitated in developing methodology and application for fNIRS (optical brain imaging technique), including signal preprocessing and analysis, by exploring methods in minimizing noise and eliminating outliers in data
  • Analyzed neuroimaging data using MATLAB and implemented visualizations for researchers
  • Streamlined data collection, management & analysis pipeline and improved data quality by 50%
  • Trained & supervised research assistants, PhD students, and research teams in neuroimaging data collection & data analysis
September 2017 - May 2020

Education

University of Michigan, Ann Arbor

Master of Health Informatics
Big Data Analytics Track

GPA: 4.00

Relevant Coursework: Data Analysis & Manipulation, SQL & Databases, Natural Language Processing for Health, Data Mining, Applied Machine Learning

August 2020 - Present

University of Michigan, Ann Arbor

Bachelor of Science in Information

GPA: 3.74

September 2013 - April 2017

Skills

Programming Languages & Tools
  • python Python
  • numpy Numpy
  • pandas pandas
  • mysql mySQL
  • scikit_learn scikit-learn
  • pytorch Pytorch
  • tensorflow Tensorflow
  • nltk NLTK
  • matplotlib Matplotlib
  • seaborn seaborn
  • rstudio R
  • Jupyter Jupyter Notebook
  • matlab MATLAB
  • Applied Machine Learning
  • Applied Statistics
  • Applied Machine Learning
  • Data Mining
  • Natural Language Processing (NLP)
Workflow
  • Data Preparation & Cleaning
  • Data Exploration
  • Data Analytics
  • Data Visualization

Certifications

Natural Language Processing Specialization - DeepLearning.AI (Coursera)
May 2021
Applied Machine Learning in Python - University of Michigan (Coursera)
January 2021

Featured Publications

Memmini, A. K., Sun, X., Hu, X., Kim, J., Herzog, N.K., Islam, M.N., Weissman, D.H., Rogers, A.J., Kovelman, I., Broglio, S.P. (2020). Persistent alterations of cortical hemodynamic response in asymptomatic concussed patients. Concussion. https://doi.org/10.2217/cnc-2020-0014

Zhai, T., Ash‐Rafzadeh, A., Hu, X., Kim, J., San Juan, J., Filipiak, C., Guo, K., Islam, M.N., Kovelman, I., Basura, G.J. (2020). Tinnitus and auditory cortex; Using adapted functional near‐infrared‐spectroscopy to expand brain imaging in humans. Laryngoscope Investigative Otolaryngology. https://doi.org/10.1002/lio2.510

San Juan, J. D., Zhai, T., Ash-Rafzadeh, A., Hu, X. S., Kim, J., Filipak, C., Guo, K., Islam, M. N., Kovelman, I., & Basura, G. J. (2021). Tinnitus and auditory cortex: using adapted functional near-infrared spectroscopy to measure resting-state functional connectivity. Neuroreport, 32(1), 66–75. https://doi.org/10.1097/WNR.0000000000001561

Islam, M., Guo, K., Zhai, T., Meah, M., Hu, X., Memmini, A.K., Beard, D., Martinez, R., Meah, S., Kovelman, I., Weissman, D., Hu, X., Kim, J., Broglio, S., Beard, D., Van Den Bergh, F., Alam, H., Russo, R. (in press). Brain metabolism monitoring through CCO measurements using all-fiber-integrated super-continuum source. BIOS/Photonics West Conference Proceedings Journal. https://doi.org/10.1117/12.2550137

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