Nazia Aslam is a Ph.D. student in the Chemical and Biomolecular Engineering Department at the University of Connecticut, advised by Dr. George Bollas. Her research lies at the intersection of machine learning and process systems engineering.

In the first two years of her Ph.D., Nazia contributed to comparative studies involving physics-informed neural networks (PINNs) and symbolic regression to identify governing partial differential equations from sparse and noisy data. This work was presented at several venues, including the Data-Driven Physical Simulations (DDPS) seminar organized by Lawrence Livermore National Laboratory, a webinar for the CRUNCH group at Brown University, and the 2023 INFORMS Annual Meeting. During her second year, she contributed to a collaborative project funded by the National Alliance for Water Innovation (NAWI). In this role, she integrated accurate, open-source, explainable, and customizable models with system-level simulations of water treatment processes for high-concentration brine. Specifically, she used customized modeling steps to incorporate different thermodynamic models and evaluated both refined and conventional thermodynamic models in her simulations, demonstrating significant energy savings that support the water-energy nexus. Additionally, she created the necessary configuration and test files, developed a new property package, and compiled comprehensive documentation for public use, resulting in software packages that are publicly available through the open-source WaterTAP GitHub repository. This work was presented at the AIChE Annual Meeting in San Diego and the International Conference on Water, Energy, Food and Sustainability (ICoWEFS) in Portugal. Nazia was also among the 36% of applicants selected to present their work at UConn’s first Graduate Student Research Symposium. Currently, she is developing continuous, predictive, and interpretable machine learning models to forecast membrane fouling trends in real time during membrane-based water treatment processes.

Beyond her research, Nazia is passionate about STEM outreach. She is a member of the Graduate Society of Women Engineers and has volunteered as a judge and mentor for the Connecticut Invention Convention State Finals and in SPARK, a summer camp that encourages middle school girls to explore STEM careers.

Before joining the University of Connecticut, Nazia earned her bachelor’s degree in chemical engineering from the Illinois Institute of Technology in 2019. After graduation, she worked at ExxonMobil in Kuala Lumpur, Malaysia, and Texas, USA, as a Process Monitoring and Analysis Engineer for several refinery units. She then joined a startup petrochemical company, where she spent a few years taking on key roles ranging from engineering design to commissioning and startup of process units.

Her interest in the John Lof Leadership Academy (JLLA) stems from a desire to strengthen her leadership skills, particularly as she aspires to grow into corporate leadership roles post-graduation. Her advice to fellow students: develop grit, view challenges as opportunities to grow, and remain humble—because humility is essential for continuous personal and professional growth.