Team

Principal Investigator

Sifat Muin, PhD

Research Assistant Professor

Sonny Astani Department of Civil & Environmental Engineering

University of Southern California

email: muin@usc.edu

Dr. Muin earned her PhD in Civil and Environmental Engineering at UC Berkeley in 2018. She finished her BS and MS in Civil Engineering from Bangladesh University of Engineering and Technology and UC Berkeley, respectively. Before joining USC she was a postdoctoral researcher at the Pacific Earthquake Engineering Research (PEER) Center. Dr. Muin is an active member of Structural Extreme Events Reconnaissance (StEER) network and Earthquake Engineering Research Institute (EERI). 

Dr. Muin’s expertise is in structural health monitoring(SHM). She is currently working in areas of response-based damage detection using machine learning, SHM sensor development, and disaster resiliency modeling.  Dr Muin’s research interest lies in structural health monitoring, earthquake engineering, response of long period structures, machine learning, data-driven community resilience, disaster reconnaissance, feasible SHM sensors. 

Graduate Students

Zijie Li

email: zijieli@usc.edu

Zijie completed his master's degree in materials engineering at the University of Southern California. He is interested in wearable electronics and flexible electronics. At MRG, his work focuses on the fabrication and testing of a new kind of structural health monitoring sensor working on the pipe.

Md Farhad Hossain

email: mdfarhad@usc.edu 

Md Farhad Hassan is a graduate student at Ming Hsieh Department of Electrical and Computer Engineering, USC. His research focus is flexible electronics and wearable medical devices for precision health and psychiatry. At MRG he is developing flexible and low-cost continuous structural health monitoring sensors-systems with the capability to localize sensing across large areas. To learn more about Farhad and his research, please visit: www.farhadhassan.com

Ankit Tripathi

email: ankittri@usc.edu

Ankit is pursuing his MS degree in Applied Data Science at USC. He is interested in natural language processing and machine learning. At MRG, his work focuses on community sentiment analysis for identifying vulnerability following earthquakes. He helped create the methodology and the NLP  model required for the research as well as created visualizations. 

Undergraduate Students

Kathryne Keenan

email:kakeenan@usc.edu

Kathryne is pursuing her BS degree in Mechanical and Aerospace Engineering and will be starting her MS program in the spring 2024. At MRG, she was part of the group that is developing the printed strain sensor. She helped with the NX modeling and simulations to model the bending and compressing of the pipe. She also participated in writing a conference paper on this project.

Cevina Manzano

email:crmanzan@usc.edu

Cavina is pursuing her BS degree in Mechanical and Aerospace Engineering. At MRG, she was part of the group that is developing the printed strain sensor. She helped fabricate the printed flexible strain sensors by screen printing. In addition to fabrication, she worked on a research paper submitted to the IEEE conference and conducted literature review for the research project's review paper.

Summer Research Students

Md. Sultanur Ashikin

email: mdsultanurashikin@gmail.com 

Ashikin received his BS in Civil Engineering from Bangladesh University of Engineering and Technology in 2022. He has done his undergraduate thesis on predicting creep-fatigue based design life of a steam generator tube-sheet of a sodium fast reactor where the component undergoes cyclic loading due to sodium flow. He is now preparing himself to get enrolled in a graduate program where he wants to explore the research opportunities in the response based structural health monitoring arena. At MRG@USC, Ashikin is working on a project where the main objective is to identify the best feature using machine learning algorithm to monitor wooden structures' structural health. Later, using this feature the aim of the study is to monitor the structural health of the wood buildings due to different levels of ground motions.


Sanjay Acharjee

email: sanjayacharjee07@gmail.com 

Sanjay is pursuing his BS in Civil Engineering from Bangladesh University of Engineering and Technology. His research interest is at the intersection of Deep Learning and Civil Engineering. At MRG, he is currently working on a method to measure Earthquake Resiliency with Natural Language Processing and Social Media data.