Expanded Resume/CV

Education

• Northeastern University - Industry Ph.D. (2024 - Present)
  • Pfizer Advisors: Ajit Jadhav and Stephen Watt
  • NEU Advisor: Professor Melanie Tory

• Johns Hopkins University - ScM in Biostatistics (2021 - 2023)

• University of Nevada, Reno - Honors BS in Mathematics (Statistics Emphasis), Minor in Big Data (2017 - 2021)

Skills and Interests

• Programming Languages: R, Python, SQL, C++, C, MATLAB
• Software: Amazon AWS, Dataiku, Docker, Singularity, SLURM, Markdown, Shiny, LaTeX, Linux Shell, Office Suite, Git, and GitHub
• Modeling and Computing: Classification, Regression, Predictive Analytics, Feature Engineering, Variable Selection, Exploratory Data Analysis, High-Performance/Cluster Computing, Containerization, Database Design and Implementation, Web-Application Development

Work

• Pfizer Digital Client Partners – Ajit Jadhav - Data Scientist - DRP Associate (Jun. 2024 - Present)

• Pfizer AI/ML/Analytics Enterprise Architecture and L&D Analytics – Randy Duncan and Leonidas Petridis - Software/Solution Engineer - DRP Associate (Jun. 2023 - Jun. 2024)

• Pfizer Machine Learning and Computational Science Group – Dr. Liang Xue - Data Scientist Intern (Jun. 2022 - Aug. 2022)
  • Cooperated with Chemical Biology Group scientists to incrementally develop a MySQL database to store and query experiment, protein, and meta-data, thus also providing a deliverable that functioned as a proof of concept for other Pfizer groups with lacking proteomics data infrastructure.
  • Programmed an accessible R Shiny-based UI to set up experiments/rawfiles/samplesheets, load in raw/processed data, modify data with excel-like interactivity, create a drag-and-drop tool to map omics files and data, store mapped data in a SQL database, and query stored data based on user needs.
  • Wrote markdown-based usage instructions and recorded tutorial videos to guide future database and UI users.
  • Created and tested scripts/methods to extend the Pfizer R Statistical Tool for Quantitative Mass Spectrometry-Based Proteomics (MSstats) package to process and standardize data from multiple proteomics data sources.
• Pfizer Simulation and Modeling Science Group – Dr. Liang Xue - Software Development Intern (Jun. 2021 - Aug. 2021)
  • Implemented an automated data pipeline in R, providing standardized computational proteomics cloud (SevenBridges) task execution and management capabilities.
  • Optimized the functionality and speed of core pipeline elements, using API’s for virtual private cloud interfacing and MySQL database task logging.
  • Developed an R Shiny-based General User Interface, using reactivity, datatable, and dashboard layout elements to provide user-friendly access to pipeline tools.
  • Wrote Markdown-based documentation to provide software feature and usage instructions.
• UNR Visual Perception Lab – Dr. Daniel Joyce - Student Researcher (HURA Award Funded) (Jan. 2021 - May. 2021)
  • Ported sleep classification algorithms from R to MATLAB and validated models with real-world sensor data.
  • Pre-processed light-intensity/movement sensor data and programmed a graphical user interface for data visualization with MATLAB.
  • Built, programmed, and calibrated a low-cost Arduino-based wrist-wearable for circadian rhythm measurement using C/C++.
• Nevada IDeA Network of Biomedical Research Excellence – Dr. Mihye Ahn - Student Researcher (INBRE UROP Award Funded) (Jan. 2020 - Jan. 2021)
  • Developed a user-friendly R Shiny web-application to deploy the best-performing prediction model.
  • Containerized parallelized R-based analyses in Docker and Singularity to minimize model training times on local high-performance computing clusters.
  • Minimized class imbalance effects of models using case-weighted models, subsampling techniques, and robust performance evaluation metrics.
  • Utilized both supervised machine learning and traditional statistical methods for pediatric patient traumatic brain injury predictive modeling.
• UNR Department of Mathematics - Dr. Grant Schissler - Statistics Research Assistant (Aug. 2019 - Jan. 2020)
  • Recommended future medical student outcome data collection and data evaluation strategies.
  • Conducted R-based frequentist and bayesian regression analyses to assess the difference of the new UNR medical school curriculum.
  • Performed data cleaning, numerical/visual exploratory data analysis, and assumption checking on medical school datasets in R.
• Swiss Armed Forces Nuclear, Biological, Chemical Defense School - Biology Laboratory Specialist (Jul. 2016 - Dec. 2016)
  • Identified microbiological hazards using multiple bacterial identification approaches.
  • Performed bacterial contamination analyses in a Biosafety Level 3 laboratory.
  • Worked as team coordinator to summarize, deliver, and present daily analysis results in an clear, concise, and timely manner.

Teaching and Tutoring

• JHU Bloomberg School of Public Health - Teaching Assistant (Aug. 2022 - May. 2023)
  • Teaching multiple discussion sections to help guide pre-medical and public health undergraduate students through a weekly problem set on topics related to the fundamentals of applied statistics and epidemiology.
  • Grading quizzes and discussion problem sets.
• UNR Honors College - Honors Peer Coach and Teaching Assistant (Aug. 2019 - May. 2021)
  • Taught, held office hours, and graded for an introductory honors course on academic integrity, undergraduate research, and professional networking.
  • Provided individual academic and professional mentorship and guidance to cohorts of 5-8 honors students in computer science and mathematics.
• UNR Department of Mathematics - Statistics Grader (Jan. 2020 - May 2020)
  • Graded homework, quizzes, and exams related to the statistical theory and R-implementation of linear models.
• UNR Department of Computer Science - Computer Science Teaching Fellow (Jan. 2018 - Apr. 2019)
  • Taught, tutored, and graded for the C language programming course.
  • Held weekly reviews and workshops on best practices to optimize and format C code.

Posters, Presentations, and Projects

• “Enhancing DataTrail Data Science Education: The BaltimoreTrails R Package and Dashboard”
  • ScM Thesis Web-App used and presented in the context of the DataTrail project (2023)
• “Proteomics Input and Output Tool (ProtIOT)”
  • Pfizer Machine Learning and Computational Science (MLCS) group talk regarding functionality and usage for the developed database access/querying and pipeline tools (2022)
• “Standardized Proteomics Pipeline Software Development”
  • Pfizer Simulation and Modeling Science (SMS) and Molecular Informatics (MI) group demonstrations regarding functionality and usage for the developed pipeline tools (2021)
• “A Low-Cost Arduino-Based Wearable for Circadian Rhythm Measurement and Light Exposure Classification”
  • UNR Undergraduate Research Symposium Presentation (2021)
• “Pediatric Traumatic Brain Injury Survival Prediction”
  • Research poster presented at the IEEE International Conference on Bioinformatics and Biomedicine (doi: 10.1109/BIBM49941.2020.9313568) and Fall UNLV Undergraduate Research Symposium (2020)
• “An Intuitive Introduction to Metropolis-Hastings Algorithm Sampling and Diagnostics”
  • Personal (R-based) Project (2020)
• “Personal Website and Project Portfolio”
  • Personal (R-based) Project (2020)
• “Bayesian Regression Model analyzing the UNR medical School Curriculum Change”
  • Research poster presented at the UNR Fall 2019 Statistical Computing Capstone Competition (2019)
• “Comparing Regularization Techniques on Simulated Data”
  • Personal (R-based) Project (2019)

Awards

• Honors Undergraduate Research Award (HURA)
  • 1,500 dollar undergraduate research funding and 500 dollar mentor stipend (2021)
• Nevada 2020 IDeA Network of Biomedical Research Excellence (INBRE) Undergraduate Research Opportunity (UROP)
  • 6,000 dollar undergraduate research funding, 1000 dollar mentor stipend, and weekly seminars on bioethics, medical grant writing, current biomedical practices, and preparation for a career in biomedical research (2020)
• 1st Place, 2019 Capstone Statistical Computing Project Competition
  • For undergraduate research results and poster presentation regarding the bayesian modeling of medical student outcomes (2019)