Lee Falin

Curriculm Vitae

PhD Genetics, Bioinformatics, and Computational Biology Virginia Tech: 2011
Bachelor of Science in Computer Science University of Illinois Springfield: 2005

Adjunct Faculty of Computer Science University of the Cumberlands: 2023 – Present
Faculty of Computer Science BYU-Idaho: 2020 – 2021
Assistant Professor of Computer Science Southern Virginia University: 2017 – 2018
Visiting Faculty of Computer Science BYU-Idaho: 2015 – 2017
CS/EE Adjunct BYU-Idaho: 2014 – 2015
Bioinformatician EMBL–European Bioinformatics Institute: 2012 – 2014
Research Assistant, Tyler Lab Virginia Bioinformatics Institute: 2006 – 2011

Ensembl Genomes 2016: more genomes, more complexity. Kersey, Paul; et al. – Nucl. Acids Res. (04 January 2016) 44 (D1): D574-D580
Ensembl Genomes 2013: Scaling up access to genome-wide data. Kersey, Paul; et al. – Nucl. Acids Res. (1 January 2014) 42 (D1): D546-D552
Using Interpolation to Estimate System Uncertainty in Gene Expression Experiments. Falin LJ, Tyler BM (2011) – PLoS ONE 6(7): e22071.
Systems Uncertainty in Systems Biology & Gene Function Prediction Falin LJ (2011) – PhD Dissertation
Adapting Teaching to the Needs of the Learner VT Hokie Stone Commemoration – 2010
System Uncertainty in Gene Expression Data VT Graduate Research Symposium – 2010
Microarray Data Inference ACC Interdisciplinary Forum for Discovery in the Life Sciences – 2010
Microarray Data Inference ISCB Intelligent Systems for Molecular Biology – 2010
OpenCL – Now everyone has a super computer (almost) Virginia Bioinformatics Institute – 2009
Inference of Functional Modules in Regulatory Networks Virginia Bioinformatics Institute – 2007

Jul 2008 – Present

Used the CRISP-DM process model to develop custom heuristic algorithms and statistical methods to help clients solve data analysis, data visualization, and other machine learning problems, using a mix of custom algorithms and off-the-shelf libraries, including pandas, NumPy, matplotlib, scikit-learn, TensorFlow, and keras.
Used Python to create a custom data processing and machine learning pipeline for a CAD software company to allow for enhanced metadata recognition and textual analysis.

Sep 2022 – Mar 2023

Led a team of data scientists working to develop analytics and machine learning solutions targeted at the detection and prevention of financial crime and fraud for a variety of financial institutions.
Coordinated a variety of process improvement initiatives across various regions of our analytics division, including documentation and process improvement initiatives, and programs to shorten on-boarding time for new data scientists.
Led team in adopting best practices for GitLab use, issue documentation, and project management processes.
Coordinated and assisted senior developers with code reviews.
Worked with other team leads to design and pilot a cross-training program across our departments to help increase billable utilization of our consultancy team.

Jan 2019 – Jan 2020

Built an AI-powered small business scheduling assistant SaaS app.
Designed and implemented UI components using React, React Hooks, Redux, and React Router.
Created API and backend data stores using Node and Firebase

Jul 2012 – May 2014

Worked with international collaborators to help add over 30,000 genomic datasets to a bioinformatics SaaS research tool accessed by tens of thousands of users.
Developed analytics pipelines in Perl and Python to pull data from Oracle, MySQL, MongoDB, and Neo4J databases for analysis.
Developed parallelized map-reduce algorithms using IBM’s Platform LSF.
Built Rest APIs and web interfaces for genomic analysis using JavaScript, Perl CGI, and Python

Jan 2005 – Mar 2008

Designed and built flagship commercial software product using OpenGL and Objective-C.
Oversaw marketing, sales campaigns, and SEO strategies which led to $5k in sales the first year, and a 17x increase in sales revenue over the next 2 years.
Negotiated acquisition of company in 2008.