About
I work on research that examines how data, sensing technologies and intelligent systems perform in real, non-ideal environments. I'm especially interested in using multimodal data to study safety, performance and well-being in physically and cognitively demanding work.
Much of my work is about translating research ideas into methods that hold up outside the lab, where noise, variability and human factors matter. I enjoy the space where sensing, data analysis and applied engineering meet, and thinking carefully about what can be measured reliably and used meaningfully in practice.
Before moving into construction engineering, I trained as a computer scientist, building natural-language systems for smart homes. That background shapes how I approach biosignals today: as a machine learning problem that has to serve real people.
Education
- Ph.D., Civil, Environmental and Construction EngineeringThe University of Texas at El Paso, 2025–present
- M.S., Computer ScienceMissouri State University, 2024
- Graduate Certificate, Software EngineeringMissouri State University, 2024
- B.Sc., Computer Science and EngineeringChittagong University of Engineering and Technology, 2019
Skills
- Machine learning
- Deep learning, GANs, transformers and SBERT, attention models, LSTM, zero-shot classification, transfer learning
- Sensing and signals
- EEG, EMG and PPG data collection and processing, experimental protocol design, human-subjects research (CITI certified)
- Programming
- Python, MATLAB, C, C++, Java, SQL, JavaScript, Node.js, PHP
- Tools
- OpenCV, MediaPipe, JupyterLab, VS Code, Weka, MongoDB, MySQL
- Process improvement
- Lean Six Sigma (Green Belt), NSF I-Corps customer discovery