Among them was Kaiyi Ji, a student of machine/deep learning and member of TDAI affiliate Yingbin Liang’s group who was selected for their outstanding achievements to date. The award provides students with one year of full-time financial support as they complete their dissertations. All three winners have earned glowing praise from their professors over the years for their work at Ohio State.
The primary goal of Ji’s research is to develop fast, principled and scalable optimization algorithms for modern large-scale machine learning and deep learning.
“In the era of big data, deep learning has become a powerful tool for various artificial intelligence and machine learning applications, with a broad impact on various areas including computer vision, pattern recognition, robotics, natural language processing, and online advertising,” he said.
When Ji came to Ohio State, his first research actually focused on cache networking. He also learned some cutting-edge techniques in both machine learning and deep learning.
“I discovered I was willing and very interested to try some projects related to deep learning,” he said.
Ji chose to contact Professor Yingbin Liang’s group, which he said is very active and successful in this field.
“Considering my strength in math, and with some advice from Prof. Liang, I started to work on deep learning from two perspectives,” he said.
He researches algorithm acceleration for large-scale deep learning applications, and theoretical justification of widely-used deep learning frameworks.
“During this process, I was continuously motived by the results of my projects and positive feedback from other researchers along this direction. I am very grateful to my advisor Prof. Liang for finding me such a suitable research direction,” Ji said.
Congratulations to students Daniel Lepkowski, Kaiyi Ji and Towhidur Razzak, as well as TDAI affiliate Yingbin Liang for this exceptional achievement!
For the full article originally written by Ryan Horns, ECE/IMR Communications Specialist, click here
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