• Developed and deployed an XGBoost regression model in production to predict year-over-year high-cost Medicare Advantage patients, concentrating ~93% of realized high costs in the top patient decile.
• Developed and deployed an XGBoost classification model (AUC 0.95) in production to predict one-year mortality risk, supporting timely transition to palliative care.
• Developed and open-sourced the kfre Python library and kfre R package, implementing Tangri et al.’s kidney failure risk equations for clinical use (SoftwareX, 2026).
• Co-developed the open-source Python libraries model_tuner (ML workflow optimization, hyperparameter tuning, and pipeline automation) and equiboots (bias and fairness auditing for equitable model evaluation).
• First author of two American Society of Nephrology Kidney Week abstracts on kidney failure risk prediction using internal EHR data, both achieving AUCs in the 80th percentile: one reproducing gold-standard risk equations, and a second extending prediction across CKD stages 1–4.
  

• Co-founded a boutique data science consultancy delivering machine learning, predictive modeling, and analytics solutions to research and industry clients.Website.
  
  

• Built a model predicting post-terminal extubation mortality in the pediatric ICU (AUC 0.88); co-authored the resulting paper in Pediatric Critical Care Medicine.
  

• Automated sales reports in Excel using VBA and built SQL queries for revenue aggregation and KPI analysis.
  

• Automated financial reporting in CPM software with VBA macros, cutting 20 staff hours per month.
  

In this this hands-on, exercise-driven course, students will learn the role of data science in decision-making, basic statistics, entry-level Python programming, and data analysis, using tools such as Excel, SPSS, and Python. Designed for absolute beginners, business analysts, and non-technical managers, the curriculum includes problem-solving exercises for assignments during and outside of the class.

Responsibilities:

• Teach data science, statistics, and machine learning (Excel & Python).
  

An examination of the role of data science within business and society. The goal is to identify a problem, collect and analyze data, select the most appropriate analytical methodology based on the context of the business problem, build a model, and understand the feedback after model deployment. Emphasis is on the process of acquiring, cleaning, exploring, analyzing, and communicating data obtained from variety of sources. Assignments require working with data in programming languages such as Python, wrangling data programmatically and preparing data for analysis, using libraries like NumPy and Pandas.

Responsibilities:

• Teach undergraduate data science and statistics courses in Python.
  

This course is an introduction to relational database management systems. You will use a relational database management system to create, maintain, and secure a database in order to analyze data. You will create filters, sorts, queries, forms, and reports. The course emphasizes the skills you need to meet user requirements.

Responsibilities:

• Instructed database fundamentals, entity relationship diagrams, tables, and SQL in Access.
  

Probability and Statistics for Artificial Intelligence Course Description

• M.S. Applied Artificial Intelligence Program Biography

• Faculty Directory Biography

Responsibilities:

• Co-design & teach graduate data science & stats course in the M.S. in Applied Artificial Intelligence program.
  

Responsibilities:

• Facilitated data analytics and statistics certificate courses.
• Completed certificates in Data Science, Data Analytics, and related areas.
  

This signature program has been designed to help UCLA undergraduate students practice their team building, public speaking, and presentation skills – all vital for their professional development.

Guest Lecturer (Volunteer):

• Taught a summer workshop on Financial Modeling in Excel - 2018
• Guest Lecturer in ECON 104 (Data Science for Economists
  
  

Panel Judge (Volunteer):

• Evaluate student presentations and provides specific feedback on students' presentation skills.
• Identify strengths and areas of improvement on students' presentation style and method.
  

Reviews:

1. European Journal of Medical Research (Springer Nature) [Certificate]
2. BMC Medical Education (Springer Nature) [Certificate]
3. Discover Medicine (Springer Nature) [Certificate]
4. BMC Medical Imaging (Springer Nature) [Certificate]
5. Critical Care (Springer Nature) [Certificate]
6. Scientific Reports (Nature) [Certificate]
7. JAMIA Open (Journal of the American Medical Informatics Association)
   

worked with Litewallet software development, design, support, and marketing teams.

Responsibilities:

• Led a GitHub project for cryptocurrency price forecasting
• Built Google Data Studio (Looker) dashboard to track daily event-specific platform (Android and iOS) activity by country.
• Conducted research and formulated time-series models in R and Python to forecast price trajectory.