I lead a talented team of data scientists, developing tools for clinical research. We specialize in generative AI and Waveform Analysis (high-resolution time series data). So far, we've developed 10+ generative AI tools for clinical research and administration and have multiple publications in high-resolution data analysis.

Corporate Risk; Balance Sheet ModelingThe focus of my work was development and remediation of stress-test models for trading, credit, treasury management, wholesale revenue, and wealth investment management portfolios. These projects employed time series modeling, regularized regression, cluster analysis, cross-validation, panel data methods, and generalized linear modeling implemented in R, Python, and SAS along with data warehouse queries via SQL. These projects were collaborative in nature, working with both other modelers and line-of-business partners. This was a data science position to develop forecast models for financial data.

At Humane League Labs, I created models based on survey data, conveying to stakeholders what the most successful campaign strategies are. Additionally, I have worked on a data collection project involving web scraping, database management, and data cleaning with the goal of suggesting target demographics and geographic regions for an upcoming outreach campaign. This was a remote intern position where I have worked on a variety of web scraping, data cleaning, model creation and model validation projects. All projects have had as the final deliverable of a report proposing concrete, actionable steps for outreach campaigns. My responsibilities included• Creating and validating statistical models predicting the behavior of individuals in response to outreach campaigns.• Web scraping, data cleaning, and data management for the purpose of creating a database of potential geographic locations to target for the greatest impact.• Preparing technical and non-technical reports recommending concrete actions for outreach campaigns.

In my statistics research, I worked on a team that developed a novel clustering technique for multi-partite networks. I am also the primary author of an upcoming manuscript on a technique for uncovering the underlying structures of networks (e.g., social networks or communication networks).I was involved in the creation of a novel clustering technique for multi-partite networks and a method for uncovering the underlying structure of networks (e.g., social networks and communication networks). My responsibilities included• Developing a novel clustering technique for arbitrary subsets of nodes on a network.• Designing and implementing a technique for analyzing the underlying structures of networks.

Throughout my graduate career, I worked extensively on finding the underlying patterns in large data sets through the use of Markov Chains, hierarchical and non-hierarchical clustering, principal component analysis, statistical modeling, decisions trees and neural networks. Aside from implementing such analysis techniques, I designed and implemented novel data visualization methods in the field of biophysics. In addressing the issues of large data sets in this field, I also proposed and implemented novel algorithms for event detection and pattern recognition. My Ph.D. research projects covered data analysis, molecular modeling, and computer-aided drug discovery. My responsibilities included• Performing GPU-enabled molecular dynamics simulations of proteins and nucleic acids• Implementing existing and developing novel data analysis techniques (e.g. Bayesian Markov state modeling, network analysis, clustering, and data visualization) to investigate drug candidates• Implementing machine learning techniques for analyzing large biophysics (~terabyte sized) data sets.• Proposing and validating models for explaining the pharmacological properties of drug candidates.

Applied teaching skills and physics content knowledge to more than triple the percentage of students scoring “Advanced or Proficient” on California High School physics standards. Taught the school's first AP science course -- AP Physics -- as a flipped classroom. Videos made for the class are linked below.Other responsibilities:•Instructional Leadership Team member - A team of teachers and administrators who analyze student achievement data, identify areas of need and increase student achievement by influencing the behavior of adults on campus.•Curriculum Design – Summer 2012, I spent approximately 120 hours (at the request of our network curriculum coordinators) creating and packaging daily lesson materials, unit plans, quizzes and unit exams for distribution to and use by all other physics teachers in the charter network. •Course facilitator – Responsible for coordinating network-wide physics testing, updating the network’s common physics curriculum as needed and coordinating meetings among network physics teachers as needed.•11th grade lead – Facilitated eight professional development sessions during the 2011-2012 school year on common teaching strategies and student intervention plans.

Selected from more than 47,000 applicants nationwide to join national teacher corps who commit two years to teach in under-resourced public schools. Participated in intensive training program to develop the skills and knowledge needed to achieve significant gains in student achievement.

Researched and tested (using MATLAB) boundary conditions for numerical evolution of wave equations over time. Also Tested methods for numerical integration and interpolation.