Incoming First-Year Student is First Author of Published Paper

*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************

Recent high school graduate Rohan Datta published his Georgia Tech research in the Journal of Chemical Physics

Contact

Jason Maderer
College of Engineering
maderer@gatech.edu

Sidebar Content
No sidebar content submitted.
Summaries

Summary Sentence:

Recent high school graduate Rohan Datta published his Georgia Tech research in the Journal of Chemical Physics.

Full Summary:

Recent high school graduate Rohan Datta published his Georgia Tech research in the Journal of Chemical Physics. After working virtually in a Georgia Tech lab the last two years, he'll enter Georgia Tech as a freshman this coming fall. 

Media
  • Rohan Datta Rohan Datta
    (image/jpeg)

Undergraduate engineering students interested in research typically enroll at Georgia Tech with an eye on joining a lab within its eight schools. Their long-term goal is to write and submit a study, hoping for an eventual publication in a peer-reviewed journal.

Rohan Datta, however, reversed the usual timeline. The 18-year-old recently graduated from The Galloway School in Atlanta. By the time he attends his first classes on campus this fall as a Stamps Scholar, Datta will already have a published paper on his resume.

With guidance from and collaboration with both a professor and an alumna of the School of Materials Science and Engineering (MSE), Datta is the first author on a recently published study in the Journal of Chemical Physics. In the paper, “Conductivity prediction model for ionic liquids using machine learning,” Datta describes his construction of a deep neural network capable of making rapid and accurate predictions of the conductivity of ionic liquids.

Datta’s publication marks a fitting conclusion to high school while serving as the next phase of his Georgia Tech experience.

Read the entire story

Additional Information

Groups

College of Engineering, School of Materials Science and Engineering, School of Chemical and Biomolecular Engineering, Research Horizons

Categories
No categories were selected.
Related Core Research Areas
Materials
Newsroom Topics
Science and Technology
Keywords
go-researchnews
Status
  • Created By: Jason Maderer
  • Workflow Status: Published
  • Created On: Jul 6, 2022 - 11:45am
  • Last Updated: Jul 7, 2022 - 3:25pm