Machine Learning Engineer

👨‍🎓 Education

• Arizona State University
  MS in Software Engineering (2023 - 2025)
  Current GPA: 3.78

• LNM Institute of Information Technology
  B. Tech. Communication and Computer Engineering (2017 - 2021)
  GPA: 7.42

💼 Work Experience

Optum Health & Technology (United Health Group)

Associate Data Scientist (Jan 2021 - July 2023)

• Led a team of 4 data scientists in projects focused on machine learning, AI, and automation, improving company-wide processes and operational efficiency.
• Spearheaded end-to-end development of machine learning algorithms and big data analytics using Spark and Snowflake, applying insights to optimize business processes.
• Designed and implemented scalable automation solutions using AWS, including data integration pipelines and Slack-based notifications, significantly enhancing workflow and team productivity.
• Collaborated cross-functionally with performance excellence teams and senior management to drive high-impact projects, from requirement gathering to delivery and post-launch maintenance.
• Led initiatives to automate data mining and agent scheduling systems, improving decision-making processes by leveraging data trends and predictive algorithms.
• Drove innovation in data handling, reducing operational inefficiencies by optimizing processes and introducing custom AI-driven solutions.

Reliance Industries

Intern (May 2020 - July 2020)

• Developed a YOLO-based Intruder Detection System using the Kaplan algorithm, improving tracking accuracy in diverse conditions for enhanced security.

🛠️ Technical Skills

• Programming Languages: Python, Java
• Frameworks: TensorFlow, PyTorch, Hugging Face Transformers
• Big Data Tools: Spark, Hadoop
• Cloud Platforms: AWS, Google Cloud
• Other Tools: Docker, Kubernetes, Git/GitHub

🚀 Projects

Text-to-Image Generation (2023)

Developed custom text-to-image models using Stable Diffusion, focusing on zero-shot generation for creative and commercial applications.

Scrum Simulator (2023)

Created a Java-based Scrum simulator for immersive learning in Agile methodologies, enhancing project management skills.

Predicting Motor Imagery Tasks (2022)

Conducted experiments with EEG data, developing an optimized model for predicting motor imagery tasks using deep learning techniques.

Cancer Detection by Mitosis Identification (2021)

Developed a classification model using the MLP-mixer architecture to identify mitosis in CT scans, contributing to early cancer detection efforts.

📚 Publications

COVID-19 Disease Identification from Chest CT Images (2021)

Published in Biomedical Signal Processing and Control, 2021. Proposed a novel preprocessing technique for CT scans, achieving significant improvements in COVID-19 detection accuracy.

An Optimal Model Selection for COVID-19 Disease Classification (2021)

Published in Biomedical Signal and Image Processing with Artificial Intelligence, 2021. Conducted a comparative analysis of deep learning architectures, achieving high F1 scores and AUC in disease classification.

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Feel free to connect with me on LinkedIn or explore more of my work on GitHub.