Columbia Electrical Engineering Student Jingping Nie was selected to participate in EECS Rising Stars 2023, which is an intensive workshop for graduate students and postdocs of historically marginalized or underrepresented genders who are interested in pursuing academic careers in electrical engineering and computer science.
Nie is a 5th-year PhD candidate in the Department of Electrical Engineering at Columbia University advised by Professor Xiaofan (Fred) Jiang and Professor Matthias Preindl. She is a member of the Columbia Intelligent and Connected Systems Lab (ICSL) and Motor Drives and Power Electronics Lab (MPLab). She received her Master of Science degree (Honor Student) in Electrical Engineering from Columbia University (2018) and her Bachelor of Science degree (Magna cum Laude with High Honors) in Engineering Science from Smith College (2017). Her research focuses on hardware-software co-design of next-generation human-centric intelligent and privacy-aware wearable devices in AIoT systems. Her recent projects include creating wearable devices for health and wellness, AIoT systems for mental health, as well as human-in-the-loop EV charging optimizations. Her works have been published in various top-tier journals and conferences and received multiple awards, including best demo award at ACM/IEEE IPSN, best demo runner-up award at ACM SenSys, and best paper award at IEEE ITEC. Nie is the recipient of the Apple Scholars in AI/ML PhD fellowship and the Columbia University Jacob Millman Award. She was a machine learning research intern at Apple.
In addition to excellence in research, Nie is passionate about education. She has led various mentorship and outreach activities, including mentoring summer high school interns, developing workshops for female students interested in STEM, and participating in Women in Science at Columbia (WISC) undergraduate mentoring program. Nie served on the organizing committee for ACM SenSys 2023, ACM e-Energy, IEEE/AIAA ITEC+EATS 2022, and ACM BuildSys 2021.
