Team Leader
Pravin Subrahmaniyan
Texas A&M University
Chemical Engineering
pravinhks_1507@tamu.edu
Project Type
Research
Who Can Join
Graduate Students, Masters Students, Undergraduate Students
Project Description
Integrating microscopy and microfluidics, we aim to develop a portable, AI based high throughput and effective tool to detect pathogens from any environmental sample. This machine vision, automated system uses morphological analysis and image segmentation for comprehensive cell characterization. With an evolving database, we plan to extend detection capabilities to process over a million bacterial species.
Team Needs
1 undergraduate student from Computer Science and Engineering – must know coding in python, have knowledge in NumPy, Matplotlib, Pandas (optional) libraries.
1 graduate level student from CSE – must have skills in ML/AI and related libraries (PyTorch or any similar deep learning library, Matplotlib, NumPy) in Python, fundamental knowledge in Neural Networks
1 graduate level student from Instrumentation/ ECEN – must be skilled in hardware control for Arduino boards and Raspberry Pi
1 undergraduate student from Instrumentation/ECEN – fundamental skillset in hardware-software integration
1 or 2 undergraduate students from CHEN
Students recruited are expected to work 5 hours a week and participate in team meetings regularly.
Students from Texas A&M University – College Station campus are preferred
Special Opportunities
Upon assessment of performance, graduate students will be paid. Undergraduate/ graduate students can also register for credits while they are enrolled (however this option may not be available for the first semester). And, significant contributions will be recognized by authorship in publications pertaining to the work.