Thesis topic: Machine lerning models and mobile applications
Research:
- Developed a color-based machine learning model and mobile application to predict the amount of substances from pictures of solution
- Developed an image processing application using Flask and OpenCV to detect ArUco markers and accurately warp images for perspective adjustment.
- Designed a color match card to compute and correct color values, mapping these to specific chemical concentrations based on environmental corrections. Integrated the system with the developed mobile application to facilitate real-time analysis and results display.
Awards and Honors:
Publications:
Conferences:
Oral presentations:
-
Poster presentations:
- ACS Spring National Meeting, San Diego, CA, March 23-27, 2025