Kunal Deb

Recently graduated a semester early with a 3.75 GPA while consistently on the dean's list. With the foundation of computational knowledge in python and machine learning I've built with my time as an undergrad, I hope to further develop my expertise in extracting meaningful insights from relevant datasets while serving potential employers to the best of my ability.

Link: linkedin.com/in/kunal-deb-255361206 

Dean's List 2020-2023

• Developed a predictive model for whether a tumor would be benign or malevolent in python based on multiple measurements of the tumor. This involved cleaning the csv data that contained the training data, normalizing the data, utilizing both PCA and Logistic Regression through python, splitting the data into training and testing data with K-folds, and graphing a confusion matrix to display accuracy.
• Utilized bank data to develop a predictive model for how likely a customer was to sign up for a checking account. Used OneHotEncoder to categorize the data based on state and used PCA to determine the best predictors. Developed multiple predictive models using both Random Forest Classifiers and Logistic Regression.
• Categorized wheat fields based on their characteristics using both a predictive model based on linear support vector machines as well as xgBoost.
• Developed a python script to pipe relevant gene data from relevant databases into excel to determine potential genes of interest for fly circadian rhythm as part of a research project.

• Competent in multitasking, time management, communicating, analytical reasoning and coordinating with others
• Excellent self-learner
• Proficient at public presentations

• Playing the clarinet
• Caligraphy
• Reading philosophy