Mechanical Engineering and NSF-CREST supported PhD candidate Marzieh Savadkhoohi won the overall First Prize at the “ Emerging Researchers Network (ERN) Conference in Science, Technology, Engineering, and Mathematics hosted by the American Association for the Advancement of Science (AAAS), Inclusive STEM Ecosystems for Equity & Diversity (ISEED) Programs and the National Science Foundation (NSF) Division of Human Resource Development (HRD). The objective of the conference is to help undergraduate and graduate students to enhance their science communication skills and to better understand how to prepare for science careers in a global workforce. Marzieh will be graduating by summer ‘23 as the first PhD student in Mechanical Engineering from UDC. Her faculty advisor is Dr. Pawan Tyagi. Marzieh has several journal papers already under her belt, including papers in collaboration with NIST.
Marzieh Savadkoohi is a Ph.D. candidate in the Engineering & Computer Science doctoral program at the University of the District of Columbia (UDC) and works in the NSF-CREST center of Nanotechnology, Research, and Education (CNRE) under the supervision of Prof. Tyagi. She is also a research associate at the National Institute of Standards and Technology (NIST) since the Summer of 2021. She holds a bachelor’s degree in Applied Physics and a master’s degree in Atomic and Molecular Physics. Her main research focus is nanotechnology and the fabrication of molecular-based magnetic tunnel junctions for computer memory devices. She is seeking an unprecedented magnetoresistance ratio in such elements to advance the magnetic tunnel junction field. In her research collaboration with NIST she is studying another type of memory device called Spin-transfer torque Random Access Memories (STT-RAMs). She is an expert in device fabrication and characterization using photolithography, thin film deposition, and various microscopy techniques (i.e., AFM, MFM, SEM, etc). She also holds keen interests in the area of data analytics and Artificial Intelligence to discover insights, find new patterns, and discover relationships in quantitative and qualitative data.