AI/ML Engineer | Gen AI Specialist | Building tools for real-world impact

🎓 MS in Artificial Intelligence, Khoury College of Computer Sciences, Northeastern University

Passionate about building intelligent systems that solve real-world problems, with expertise in computer vision and generative AI.

I turn complex AI concepts into practical applications and enjoy teaching computers to see the world (while occasionally apologizing to my GPU).

• 💡 Currently developing GrantWell at The Burnes Center for Social Change, helping underserved communities access federal grants
• 🧠 Published researcher in healthcare AI, focusing on radiation safety and personalized dosimetry in CT imaging
• 🤖 Experience with generative AI, RAG techniques, and deploying AI solutions at scale
• 🌐 Built end-to-end MLOps pipelines and production-ready AI systems using AWS and GCP

I'm passionate about AI for social impact and creating technology that makes a meaningful difference.

Languages
Python • Java • C++ • TypeScript • React • HTML/CSS

Machine Learning & Data Science
TensorFlow • PyTorch • OpenCV • HuggingFace • Transformers • NLTK • MLFlow

Cloud & MLOps
AWS (Lambda, Bedrock, DynamoDB) • GCP (Vertex AI) • Docker • Git

AI-powered platform helping underserved communities in Massachusetts pursue federal grants.
Tech: React • AWS (Lambda, Bedrock, DynamoDB) • RAG

• Co-developed a public-facing AI tool with the Massachusetts Federal Funds Office
• Designed an AI-powered grant recommendation system using Claude 4 via Amazon Bedrock
• Built a guided grant writer interface with real-time AI assistance and document processing
• Conducted user demos across Massachusetts to gather feedback and improve features

Real-time music recommender using facial emotion analysis and mood-based clustering.
Tech: Python • Docker • Airflow • DVC • MLflow • Vertex AI

• Built a system that detects user emotions via facial analysis and maps them to song clusters
• Designed a complete MLOps pipeline with Docker, Airflow, and DVC
• Deployed models using Vertex AI and tracked performance with MLflow
• Optimized data workflows with parallel processing and CI/CD implementation

Transformer-based sign language recognition system for Indian Sign Language.
Tech: PyTorch • Transformers • Computer Vision

• Built system using heatmap-guided pretraining and binary masking
• Improved recognition accuracy by 85%
• Supported future deployment for UMANG services as part of C20 India 2023 Digital Education initiative

Jun 2024 - Aug 2024

• Conducted research on AI applications in radiation safety and personalized dosimetry in CT imaging
• Co-authored two peer-reviewed journal articles on AI-driven methods for medical imaging
• Synthesized findings from over 100 academic studies on CNN-based segmentation and deep learning denoising

• Peer Reviewer, European Journal of Radiology Artificial Intelligence, 2025
• "Enhancing Radiation Safety in CT Imaging through Artificial Intelligence," Physica Medica – European Journal of Medical Physics, 2025 (under review)
• "Real-time patient-specific-dose in CT through use of artificial intelligence," Journal of Radiological Protection, 2024

I'm always interested in collaborating on AI research, MLOps, and computer vision projects.

• 📧 Email: chathankandy.a@northeastern.edu
• 💼 LinkedIn: linkedin.com/in/anjithprakash
• 💻 GitHub: github.com/Anuttan
• 🏙️ Location: Boston, MA

"Teaching computers to see the world and occasionally apologizing to my GPU."