Hi, I'm Dipit Vasdev. I am an aspiring Data Scientist, Research Enthusiast, and Software Developer set to graduate from New York University in May 2024 with a degree in Computer Engineering. I excel in Python, JavaScript, React, and TensorFlow to create innovative digital solutions.
About Me
After earning a Bachelor's degree in Computer Science and Engineering from Guru Gobind Singh Indraprastha University, my fascination with neural networks drove me to pursue a Master's in Computer Engineering at New York University. What excites me most about technology is the challenge of unraveling complex problems. I thrive on finding innovative solutions in the fields of data science, machine learning, and generative AI. My technical toolkit includes Python, Java, TensorFlow, and React, alongside advanced competencies in full-stack development. I am continuously honing these skills through dynamic projects and professional engagements. Presently, I am eager to secure a full-time role where I can contribute to impactful tech solutions.
Beyond the screen, I balance my tech pursuits with personal interests. I am a chess enthusiast, relishing the strategic depth of each game. I am currently absorbed in "Quiet: The Power of Introverts in a World That Can't Stop Talking" by Susan Cain, which has given me profound insights into personality dynamics. As a gamer, I find relaxation in virtual worlds, and I explore culinary arts as a cooking aficionado, experimenting with new recipes.
My projects
Check out all my projects at my project cabinet Click here
Project Cabinet: My Coding Projects Showcase
Project Cabinet is an interactive portfolio showcasing my coding projects through visually engaging cards. Featuring responsive design, advanced filtering, and sorting, highlighting my technical skills and project expertise in a user-friendly format. Visit: https://project-cabinet.vercel.app/
- React
- Tailwind CSS
- Next.js
- Typescript
- Javascript
Predictive Analysis and Insights on NBA Playoff Outcomes
Conducted data preprocessing and analysis on NBA datasets (2014-2023) using R (tidyverse, dplyr), generating visualizations with ggplot2 and plotly. Developed logistic and linear regression models to predict NBA playoff outcomes, achieving 75% accuracy in forecasting series winners and the number of games.
- R
- tidyverse
- ggplot2
- caret
- plotly
AI-Driven GitHub Issue Classification System
Built a machine learning model with 85% accuracy for classifying GitHub issues using Logistic Regression and PySpark on Databricks (GCP Compute). Developed a React-based frontend for a user-friendly interface, enabling real-time issue classification and predictions.
- PySpark
- MLlib
- Databricks
- GCP
My Skills
- Python
- C++
- Kotlin
- Java
- SQL
- TypeScript
- JavaScript
- TensorFlow
- Flask
- Scikit-learn
- Git
- Node.js
- Express.js
- MongoDB
- Mongoose
- PyTorch
- React
- Pandas
- NumPy
- Matplotlib
- Power BI
- Tableau
- Microsoft Excel
- Machine Learning
- Deep Learning
- Data Science
- Natural Language Processing
- Computer Vision
- Big Data
- Relational Database
- Generative AI
- Hadoop
- Spark
- Dash
My experience
Software Engineer @ Hack for LA
California (Remote)
Contributed to the development of the TDM Calculator using React and Node.js, streamlining Los Angeles' Transportation Demand Management (TDM) regulations.
August 2024 - PresentResearch Assistant @ DICE Lab - NYU Tandon School of Engineering
New York, NY
Led a project on vision-language models for radiology report generation using Python, contributing to a vision transformer for medical image understanding, and lead-authored a paper with top cancer researchers at MSK.
December 2023 - May 2024Graduate Course Assistant @ NYU
New York, NY
Collaborated with other TAs to facilitate all aspects of graduate-level Deep Learning course for 100+ students, including grading, assignments, and doubt resolution.
September 2023 - May 2024Software Engineer Intern @ Alten Capital
New York, NY
Developed and deployed highly scalable backend systems using leading technologies, enabling CRUD operations across a variety of data models, leading to a 17% reduction in redundant code.
May - August 2021Software Engineer Intern @ S&P Global
Gurgaon, India
Reduced infrastructure costs by 23% by leveraging AWS Lambda and CloudWatch APIs to streamline data extraction,
May - July 2021Contact Me
Feel free to reach out to me through email at dipit.vasdev@nyu.edu or send me a message using the form below.