Shashank Pritam

You can find my research work here:

• GitHub

• Google Scholar

• Orcid

• LinkedIn

OBJECTIVE

Hello! I am a Ph.D. student at North Dakota State University (NDSU), enrolled in the Department of Biological Sciences. My academic journey has been quite enriching for me so far. Computational Biology has been my focus as a research area, mainly because it is quite interdisciplinary. I truly enjoy studying the breadth of the research area, as it gives me opportunities to focus on deep, specific problems while still acquiring new skills and utilizing old ones.

The way I approach a problem is from a software engineer’s perspective—to build on skeletal structures. But at the same time, I error-proof my model, code, and project as a mathematician would. Biology is a domain that not only provides me with intellectual satisfaction but also enables me to help society in a way that I can. In terms of skills and knowledge, I have completed excellent courses ranging from Undergrad Real Analysis to Graduate-level Statistical Machine Learning. Within the domain of computational science, I keep sharpening my Python and R skills, albeit with a narrow focus on data analysis and visualization. In my spare time, I devour great programming articles, books, and podcasts to continue learning. I have also been learning Rust and Go languages.

With my acquired skills and knowledge, I would like to work on projects that are fulfilling to me, such as working on problems that bridge scientific research and industry solutions.

EDUCATION

Projects

Small RNA’s Role in Megachile Rotundata Diapause

• Duration: August 2023 - Present
• Description: Investigating the role of small RNAs in the diapause of Megachile rotundata using computational methods in bioinformatics.

Examining the High Insertion Bias of P-Elements into X-TAS

• Duration: March 2023 - July 2024
• Description: Analyzing the high insertion bias of P-elements into X-TAS using computational methods in bioinformatics.

Relevant Courses

Graduate

• Computational Methods in Bioinformatics
• Quantitative Biology
• Statistical Machine Learning

Undergraduate

Publications & Presentations

• Examining the High Insertion Bias of P-Elements into X-TAS. [Poster]. Presented at the TAGC, Washington DC, March 2024.
• Investigating the Elevated Insertion Bias of P-elements into X-TAS. [Poster]. Presented at the Northern Plains Biological Symposium, Grand Forks ND, March 2024.

Awards & Recognitions

• Best Poster Presentation, PhD Category. Northern Plains Biological Symposium 2024, University of North Dakota, Grand Forks ND.

Professional Development

Workshops

1. Leadership and Entrepreneurship Workshop. Conducted by the NDSU Research Foundation and NDSU Office of Innovation and Economic Development, January 25, 2024.
2. Poster Preparation and Abstract Writing Workshop. Center for Writers, NDSU, February 29, 2024.

Skills

1. Programming Languages: Python and R for bioinformatics pipelines; familiar with Go and Rust for tool development. Exploring Crystal for specific computational tasks (e.g., scripting).

2. Data Analysis & Visualization: I have been using DuckDB and Polars for efficient in-memory data querying and manipulation. Also, I am experienced with Pandas and NumPy for data analysis, proficient in creating visualizations with Matplotlib, Seaborn, ggplot2, and gnuplot.

3. Machine Learning/Deep Learning: I have used TensorFlow and PyTorch to develop predictive models in genomics and proteomics. I have been using Scikit-learn and JAX for machine learning research.

4. Workflow Management: I have been creating bioinformatics workflows using Just, Snakemake, or Bash for my projects. Experienced in job scheduling with PBS and Slurm for HPC systems.

5. Documentation, and Version Control: LaTeX, Quarto, and Markdown. Also, Git for version control.