Chieh-Ting (Jimmy), Ph.D. Hsu

• Genomic and proteomic analysis for vaccine development for different viruses. Enhanced the development speed of various vaccines by 80 percent by automating fetching and filtering virus sequences directly from the National Center for Biotechnology Information gene database and processing through the automated pipeline. • Designed DNA/RNA sequence analysis pipeline. Constructed a robust statistical algorithm for more than 50,000 sequences, boosting the accuracy of virus DNA sequence analysis by 50%. • Automated processing pipeline for spatial mapping of scRNA-seq data by directly interacting with online analysis package through self-build algorithms, processing more than 1000 genes and outputting corresponding levels in different cell types • Led the development of drug discovery applications for utility and flexibility by building and creating pipelines to handle a diverse range of molecules with different ML algorithms and combining multiple programs (PyMOL, AutoDock)

• Led interviews with clients to create a precise scope of the project following the client’s statement of work • Create a skeleton and storyboard for precise value delivery to the clients, keep track of individual subsection timelines for all consultants, and ensure the quality of their work with detailed feedback

• Determined the cause for the loss of 60% of revenue for the clients by tracking 5 consecutive years of financial statements • Created short and medium-term executable blueprints for the clients to diversify their revenue streams

• Increased accuracy of data analysis pipeline to 100% by building a new automating algorithm • Decreased data storage by 33% by optimizing the data frame and data structure of the analysis pipeline • Automated analysis of big flow cytometry data. • Study the techniques involved in bioinformatics and develop software tools to support relevant databases and applications. • Aid the development of a Machine Learning algorithm for cell population identification and the analysis of Project Discovery data to aid in developing an algorithm for population labeling.

• Co-founder and Chief Operation Officer • Incorporated the startup by receiving 1st place in healthcare stream of District 3 incubator validation program with external judges and a venture capital panel • Built Minimum Viable Product using business strategies from interviewing 100+ patients and physicians • Calculated profitable business model (within 3 years) by obtaining social survey data and confirming the accuracy with local primary care physicians

• General manager in charge of both bar and restaurant's day-to-day front of house operations. • Reduced inventory by 50% and labor costs by 33% by analyzing sales data and removing low-sales items • Generated peak weekly revenue of >$20K by designing and building new floor plans • Managed 15+ and trained 20+ employees by building a training program and writing an employee manual

• Ran 8 hours of weekly practice sessions by developing and executing warm-ups and drills • Trained three levels of players (beginners to high school varsity athletes) by customizing training sessions

• Tested individual experiments before each lab session and assisted students during lab period. • Evaluated lab reports and provided written feedback to students.

• Modelled kink formation dynamics of collagen fibrils using the Gillespie algorithm with tension dependent kink formation rate to compare with experimental stress strain curve. • Derived mean field solutions for model for comparison to simulations.

• Improved the Bayesian partition function method program to fit the stochastic decay of Green Fluorescent Protein (GFP) that outputs the distribution of brightness of GFP, distribution of lifetime of GFP, and the joint distribution for both. • Derived analytic solutions using statistical model for distribution for simple cases of stochastic decay of GFP and compare them with simulation to ensure convergence.

• Analyzed data taken from the atmospheric mass spectrometer from the Arctic observatory. • Compared simulated results from WRF atmospheric transport model with real measurements in the domain of north-eastern North America.

• One of the only two undergraduate TAs in the department. • Assisted first year students during lab sessions through responding to inquiries, fixing simple apparatus, and explaining derivations to equations. • Evaluated lab reports and provided feedback to assist students with scientific report writing.

• Updated ‘Monte Carlo Maximum Likelihood’ with Bayesian partition function method using C to perform curve fitting on stochastic decay of GFP. • Derived convergence criteria and tested on different likelihoods • Produced Micron size droplets with fluorescein using modified technique of Premixed Membrane Emulsification. • Image analysis of image taken from Phase Contrast microscope.

• Developed Monte Carlo Maximum Likelihood method and tested the algorithm with simulated probability distributions. • Used Monte Carlo Maximum Likelihood method to fit experimental data of stochastic decay of GFP.

• First Author publication in a top 15% journal by developing a new computational tool that ranks the importance of each component in any computational model, simplifying the complexity of a problem • Supported publication of 2 articles in a top 7% journal by leading mathematical simulations of systems in different biological organisms • Won poster presentation award out of 30 posters at the 3rd Canadian Society of Biophysics conference

Completed course work as part of the course based Master's program in medical physics before switching back to more research focus program in physics.

• National NSERC Undergraduate Research Scholarship (0.6% Acceptance rate), 6 times Dean’s lists • Presented at nine Canada-wide conferences, covering multiple areas of undergraduate research