Thanks for stopping by. I'm excited to share a bit about who I am, what I've done, and what I'm passionate about. Feel free to explore and reach out if you want to chat or collaborate!

I'm a Computer Science grad student at Binghamton University - SUNY, currently diving deep into data structures, machine learning, and social media data science. Before that, I completed my Bachelor's in Computer Engineering at University of Mumbai, where I built a strong foundation in everything from cloud computing to data mining.

I love working with a variety of technologies. Here's a quick rundown:

• Programming Languages: Python 🐍, R, Mulesoft, Java ☕, JavaScript, Node.js, React.js, REST APIs, Rust, MongoDB, SQL
• Frameworks & Libraries: LangChain, PySpark, Hadoop, FastAPI, Flask, PyTorch, TensorFlow, NumPy, Pandas, Scikit-learn, Spring
• Tools & Platforms: Azure, AWS, GCP, Spark, Hive, Sqoop, Power Automate, Git, Maven, Postman, Docker, Messaging Queues, CI/CD, Tableau
• Certifications: Microsoft AZ-900, AWS Technical Accreditation, Machine Learning A-Z™: Python & R in Data Science

Research Assistant – Data Science & Analytics
Sep 2024 – Present
I'm working on some pretty cool projects:

• Fine-tuning large language models (think BERT and GPT-3.5) on hundreds of multimodal patient records to boost cancer imaging diagnosis accuracy by 12% 🎯.
• Engineering features using PCA and optimizing SVM classifiers to hit high accuracy rates while reducing false positives 📈.
• Using PySpark to process hundreds of thousands of genomic samples, making data harmonization a breeze for clinical research 🔄.
• Running statistical analyses to unearth key biomarkers that could shape future treatments 🔍.

Senior Software Engineer – Data Engineering
Nov 2021 – Jan 2024
I dove deep into data engineering and machine learning:

• Developed text summaries using Hugging Face models, speeding up issue prioritization by 50% ⚡.
• Scaled AWS EMR workflows to process over 10M records daily and significantly cut runtimes ⏱️.
• Built a serverless ML monitoring system that slashed manual reporting from 8 hours a week to just half an hour 📊.
• Enhanced data pipelines with Spark to boost throughput and feature engineering capabilities 🚀.

Graduate Engineer Trainee
Jul 2021 – Nov 2021

• Developed Python-based ML microservices on Azure Functions, reducing deployment costs by 40% 💡.
• Integrated Azure tools to enhance scaling and security within CI/CD pipelines 🔒.

Web Development Intern
Jun 2019 – Aug 2019
I got my start by:

• Building a timesheet application with React, Flask, and SQL that saved managers time and streamlined billing ⏳.
• Training an NLP-powered chatbot to answer FAQs with impressive accuracy 🤖.
• Assisting with third-party API integrations to boost website functionality and user engagement 🌐.

I love taking on projects that challenge me and help me grow. Here are a few highlights:

• Employee Timesheet and Billing Cost Calculator:
  A handy web app using React JS and Python Flask that helps employees log work, managers approve submissions, and clients review project costs.

• Group Chat and Large-File Transfer Application:
  Built with Python's Socket and GUI libraries, this app supports real-time chatting and file transfers up to 2GB 💬📁.

• Facial Image Generation for Suspect Identification:
  Trained a TensorFlow-based DCGAN on over 200K images to generate high-resolution facial images, achieving an impressive Fréchet Inception Distance score and published in Springer ICSES 2021 🖼️✨.

• Comprehensive Study of Failed Machine Learning Applications:
  A research project employing a 3C (Consolidation, Classification, Case Studies) approach, culminating in a co-authored chapter in a Taylor & Francis ML journal 📚.

• Forest Cover Classification and Clustering:
  Leveraged PCA and SVM (with GridSearchCV) to classify forest cover data with high accuracy, and applied K-Means clustering to validate the results 🌲📊.

• Gene Mutation and RNAseq Data Analysis:
  Processed and analyzed data from over 500 NSCLC patient records to study gene expression and survival outcomes 🧬.

• Social Media Sentiment Analysis - Reddit and 4chan:
  Developed a sentiment scoring pipeline with Spark NLP and Logistic Regression, deployed on AWS EMR to analyze over 100K stock market-related posts 📈💬.

• Virtual Chemistry Lab:
  A web-based simulation of 25 chemistry experiments that even led to a published paper in an international journal (IRJET) 🔬.

I believe in sharing knowledge and building community:

• Editorial Head, ACM Student Chapter:
  Led the publication of our annual technical magazine in 2021 📰.
• Co-Technical Head, ICACTA-2020:
  Helped organize and manage the technical aspects of an international conference 🌐.

If you're curious about my work, have a question, or just want to chat about tech and innovation, feel free to reach out:

• Phone: (607) 313-8194
• Email: [email protected]
• LinkedIn: Prem Bhajaj
• GitHub: prembhajaj

Looking forward to connecting and collaborating!

Cheers,
Prem