Accepted into NCI-funded Computational Biology Summer Program (CBSP).Developing toolkit using Pytorch and Pyro for time series analysis using probabilistic graphical models.Modeling tumor growth in patient-derived xenografts for forecasting and prediction of drug responses.

Researching semi-supervised learning using variational autoencoders, improving image classification tasks with sparse labels.Gained expertise in PyTorch, experimental design, integrating diverse machine learning models and code bases.

Guided and tutored students in computer science courses, including CS5 (introductory Python), CS60 (functional programming in Racket, OOP in Java), and CS70 (data structures and algorithms in C++).Selected by professors for biology Academic Excellence Program, mentoring students in data analysis and visualization with R.Invested 5+ weekly hours tutoring and grading, promoting student success and academic excellence.

Developing bioinformatics pipelines to investigate Plasmodium life cycle regulation using RNA-seq and CHIP-seq data.Performed and analyzed data from PCR, gel electrophoresis, flow cytometry, Western blot and TA cloning experiments.

Developing production-quality source code to automate switching of 3D printer heads and optimize filament usageCollaborating with company representatives and intern team to write Python and C++ code, Klipper firmwarePreparing code for deployment by testing on company-manufactured devices

Developing PyTorch-based models to identify cell types, specifically macrophages, from single-cell RNA sequencing data.Comparing performance with various neural network architectures and logistic regression.Fine-tuning models from academic papers for lab-specific tasks.Creating computational pipelines for neutrophil cell count estimation from blood mRNA data, manuscript under preparation.Mentoring 4 students and creating comprehensive software training resources and Jupyter notebooks.

Developed improved Boolean algorithm for single cell RNA-seq analysis under the guidance of Dr Debashis Sahoo. Described new retinal cell type markers from retinal organoid data. Manuscript published in BMC Bioinformatics.

Utilized R for statistical analysis on RNA sequencing datasets (healthy and tuberculosis samples)Applied K-S test to assess broad distributional variations and differential expression analysis to quantify specific differences.