This spring the Machine Learning Center at Georgia Tech (ML@GT) will honor its first graduating class. The three graduates – Cyrille Combettes, Harsh Shrivistava, and Haoming Jiang – will be the first students awarded a doctorate degree in machine learning from Georgia Tech.
“We are thrilled to celebrate our first graduating class from ML@GT. Each of these students has contributed significantly to the machine learning community and I am sure will continue to do so for many years to come. Congratulations to all on this incredible achievement,” said Irfan Essa, ML@GT executive director.
Combettes was advised by former David M. McKenney Family Associate Professor in the School of Industrial and Systems Engineering (ISyE) Sebastian Pokutta and his research focused on constrained optimization.
For others working to complete a Ph.D. in machine learning, Combettes advises them to work on time management, saying “get work done when you work, but also fulfill other interests in life. This will help you bounce back better when needed.”
After graduation, Combettes will be moving to Toulouse in Southern France to work as a post-doctorate with Jérôme Bolte, a professor at the Toulouse School of Economics.
Shrivistava completed his Ph.D. degree in Fall 2020 and will officially graduate this semester. He was advised by Srinivas Aluru, a professor in the School of Computational Science and Engineering. Shrivastava’s thesis research introduced two novel and generic techniques to design deep learning architectures that exist in natural language processing, healthcare, and computational biology. He has already begun working as a senior applied scientist at Microsoft Redmond.
Reflecting back on his experience at Georgia Tech, Shrivistava said, “The course structure of the ML Ph.D. program is very well designed to provide a good balance between the breadth and depth of knowledge required to pursue ML and related research. I really enjoyed meeting fellow grad students from various departments in our ML seminars and in the Coda workspace. The program helps foster a collaborative research environment at Georgia Tech.”
Jiang’s research focused on reducing human labor cost in deep learning for natural language processing and he was advised by Tuo Zhao, an assistant professor in ISyE. He opted to pursue his Ph.D. at Georgia Tech because of ISyE’s high ranking (number one for best graduate school) and his advisor.
“The overall experience at Georgia Tech is excellent. The academic environment is active, flexible, encouraging, and collaborative. The best part of my experience were my amazing collaborators,” said Jiang. Post-graduation, Jiang will work on improving search service for Amazon as an applied scientist.
Though earning their degrees came with a lot of hard work and sacrifice, all three are grateful for their ability to travel the world as a part of their Ph.D. experience.
“I was able to travel to Tokyo, Vancouver, Toronto, and Berlin to participate in conferences and workshops. It’s an incredible feature of life as a Ph.D. student,” said Combettes.
Jiang agrees with Combettes saying, “My favorite Georgia Tech memory is when I was able to attend my first academic conference, the International Conference on Learning Representations (ICLR) in New Orleans. I’m also a foodie, so I really enjoyed trying the oysters in New Orleans.”
About ML@GT
ML@GT was founded in 2016 with the center beginning to administer the doctorate in machine learning in 2017. As of Spring 2021, the center has 94 Ph.D. students and more than 200 faculty members from all six colleges. The center aims to research and develop innovative and sustainable technologies using machine learning and artificial intelligence (AI) that serve our community in socially and ethically responsible ways.
Story by Allie McFadden, Communications Officer, allie.mcfadden@cc.gatech.edu
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