Congratulations to Dr. Sarah Chen on Her PhD Defense

We are delighted to announce that Sarah Chen has successfully defended her PhD dissertation titled “Machine Learning Approaches for Automated Urban Water Quality Monitoring and Contamination Source Identification.” Her defense, held on June 28, 2023, marks the culmination of four years of dedicated research and innovation in our lab.

Research Contributions

Sarah’s dissertation makes several significant contributions to the field:

1. Novel Algorithm Development: Created a new deep learning architecture that can detect water contaminants with 95% accuracy using low-cost sensor data

2. Field Implementation: Deployed and validated her system across three urban watersheds, demonstrating real-world applicability

3. Source Tracking: Developed a reverse-modeling approach that can identify pollution sources with unprecedented spatial precision

4. Open-Source Tools: Released a comprehensive software package for water quality monitoring agencies to implement similar systems

Committee Praise

The dissertation committee, consisting of experts from hydrology, computer science, and environmental engineering, unanimously praised Sarah’s work for its interdisciplinary approach and practical applications.

Committee chair Dr. Rodriguez noted:

“Sarah’s research represents exactly the kind of work we need in this field - technically sophisticated but designed with real-world implementation in mind. Her algorithms are already being adopted by two municipal water authorities.”

Publications

Sarah’s PhD research has resulted in four peer-reviewed publications:

• Chen, S., Johnson, S., & Rodriguez, L. (2023). “Deep Learning for Real-Time Water Quality Anomaly Detection.” Water Research, 215, 118249.

• Chen, S., & Rodriguez, L. (2022). “Contaminant Source Identification Using Bayesian Networks and Sensor Arrays.” Environmental Science & Technology, 56(9), 5621-5633.

• Chen, S., Taylor, J., & Rodriguez, L. (2021). “Low-Cost Sensor Networks for Urban Water Monitoring: A Comparative Analysis.” Journal of Environmental Management, 287, 112348.

• Chen, S., Wang, Y., & Rodriguez, L. (2021). “Machine Learning Approaches for Water Quality Prediction: A Review.” Science of the Total Environment, 782, 146574.

Next Steps

We’re proud to announce that Dr. Chen has accepted a tenure-track assistant professor position at Pacific Coast University’s Department of Environmental Engineering, where she will continue her research on smart water systems. She will also maintain a research affiliation with our lab as we continue collaborative projects.

Lab Impact

Sarah’s contributions to our lab have been immeasurable. Beyond her research, she:

• Mentored 6 undergraduate researchers
• Co-developed our lab’s water quality monitoring curriculum
• Led community science initiatives with local high schools
• Secured two small grants to support her research extensions

Celebration

The lab hosted a celebration for Dr. Chen on June 30th, attended by faculty, students, and family members. We presented her with a commemorative award recognizing her outstanding contributions to our research community.

Dr. Chen (center) with lab members at her graduation celebration

Please join us in congratulating Dr. Sarah Chen on this significant achievement and wishing her continued success in her academic career!