I build production ML systems that bridge research and real-world impact; from voice classification serving millions of users to uncertainty-aware medical imaging models. I'm passionate about deploying AI that actually works in the wild, especially in healthcare.
- 🎓 Graduating December 2026 from Northeastern University (MS in Artificial Intelligence)
- 🏥 Currently researching speech-based depression detection using the DAIC-WOZ dataset
- 🔬 Published researcher in blockchain consensus mechanisms for healthcare data management
- 🖥️ Building RewardSense — a credit card recommendation system with full MLOps pipeline
- 💼 Graduate TA for CS5100: Foundations of AI, previous TA for CS1800: Discrete Structures
- 📫 Reach me at akhilkas2001@gmail.com
- 👻 Looking to collaborate on open-source ML/AI projects
Reliance Jio — Built voice classification systems across multiple Indian regional languages, generating $150K+ revenue in production.
CognitiveHealth Technologies — Developed healthcare AI solutions including fraud detection and multimodal medical document analysis.
Deep Vision Analytics — Worked on autonomous systems development with production-grade ML pipelines.
| Project | Description |
|---|---|
| RewardSense | Credit card recommendation system with synthetic data generation, anomaly detection, bias mitigation & CI/CD |
| Patient Communication Assistant | RAG application transforming complex medical documents into patient-friendly explanations |
| XAI Healthcare Dashboard | Orthopedic motion assessment using IMU sensors with explainable AI principles |
| CheXpert Medical Imaging | Uncertainty-aware chest X-ray classification achieving 0.87 AUC on weak labels |
| Speech Depression Detection | Multimodal depression detection research using the DAIC-WOZ dataset |