About Me
I am a Senior Engineer and Team Manager with 8 years of experience at HydroTech, specializing in IoT sensor development, hardware engineering, and cloud-based data analytics. I lead cross-functional teams in designing and deploying high-performance sensor systems, developing end-to-end solutions from hardware prototyping to AWS cloud infrastructure deployment.
My core expertise includes sensor hardware development, IoT system architecture, cloud data pipelines on AWS, and data analytics using machine learning. I build scalable ML systems that process sensor data in real-time, enabling predictive maintenance, anomaly detection, and intelligent monitoring for industrial IoT applications.
In parallel, I am pursuing a Ph.D. in Biomedical Engineering at the University at Buffalo, focusing on AI infrastructure for medical imaging and LLM-based clinical applications. This research complements my industry work by advancing scalable AI systems and data processing frameworks.
Education
- Ph.D., Biomedical Engineering — University at Buffalo, 2021–2025 (expected)
- M.Eng., Biomedical Engineering — Cornell University, 2020–2021
- Visiting Research — Chinese Academy of Sciences, 2018–2020
- Undergraduate Research — University of Kentucky, 2018–2019
Research Interests
- IoT & Sensor Systems - Hardware development, embedded systems, and sensor data processing
- Cloud Infrastructure (AWS) - Scalable data pipelines, real-time analytics, and ML deployment
- Machine Learning & Data Analytics - Time-series analysis, anomaly detection, and predictive modeling
- Computer Vision - Medical imaging, image processing, and visual analytics
- LLM & AI Infrastructure - Large language models for clinical applications and automated systems