College of Science presents the Faculty Research Awards

02-23-2023

The College of science held the faculty Research awards on Thursday March 9 from 3-4:30 p.m. in STEW 214 A,B,C,D. The awards honored three outstanding researchers that are a part of the College of Science and each honoree was given the opportunity for individuals to hear them share about their research in a twenty-minute presentation. The honorees and their research include:

 

• Elisa Bertino, Samuel D. Conte Professor of Computer Science-The Security of Cellular Networks: As the world moves to 5G cellular networks and next-generation is being envisioned, security of cellular networks is increasingly critical. To that end LTEInspector, a model-based systematic testing approach for cellular network protocols combines a symbolic model checker and a cryptographic protocol verifier in the symbolic attacker model. Using it, 10 new attacks have been discovered along with 9 prior attacks, categorized into three abstract classes (i.e., security, user privacy, and disruption of service), in three procedures of 4G LTE.
• Julia Laskin, William F. and Patty J. Miller Professor - Analytical Chemistry-Mass Spectrometry: From Materials Science to Biology: Mass spectrometry is a powerful analytical technique with applications ranging from forensics and environmental sciences to drug discovery and biological research. New experiments are developing approaches for preparing uniform layers of well-defined active species on surfaces using soft-landing of mass-selected ions. These experiments harness the potential of mass spectrometry as a preparative tool that enables the precise control of ion composition, charge state, kinetic energy, and coverage.
• Guang Lin, Professor of Mathematics and Mechanical Engineering-Machine Learning for Applications in Science and Engineering: Machine learning can be used to develop interpretable, robust trustworthy data-driven models, and physics-informed neural networks with emphasis on discovering physical laws from noisy data in diverse applications. Examples include, developing an integer-order COVID-19 epidemic model and a fractional-order COVID-19 epidemic model to forecast the transmission dynamics of COVID-19 in New York City and introducing an innovative data-driven modeling approach for causal model discovery, and personalized prediction in Alzheimer’s disease.