Yatish Hedge: CCDS Researcher Discusses Illuminating 2016 and other Center Projects
Hedge is a research staff member at the Center for Computational and Data Science (CCDS). He reflects on how his education and experience as a software engineer at Alcatel Lucent have given him the chance to better understand, engage and analyze different datasets and projects.
By Amanda Quick
Yatish Hedge is no stranger to working with large datasets. Since his first day on the job four years ago, Hegde has had the opportunity to work on various data-related projects while engaging with faculty from both the NLP and data science departments in the iSchool.
“One of the main opportunities is working with data,” said Hegde of his experience so far at the CCDS. “Students learn how to correct, analyze and collect data. The data is already here and they can work with all real datasets.”
Hegde graduated from the iSchool at Syracuse University with a master’s degree in Information Management in 2010. He also holds an undergraduate degree in Computer Science from R.V College of Engineering, according to his bio. Hegde’s education and work experience as a software engineer have prepared him to become a key research member of the CCDS.
“My role in the Center is to help researchers achieve their goals and system needs and help grad students and PhD students,” said Hegde.
Prior to working full-time at the CCDS, Hegde was a member of the Center for Natural Language Processing (CNLP). He brought his interests in natural language processing, data science and machine learning to the CCDS to continue to work on projects that encompassed his expertise.
“There is something interesting new to learn everyday,” said Hegde of his favorite part about working at the CCDS. “It’s a very good opportunity to work with different students and faculty and work on different projects.”
More About Hegde and CCDS Projects
Since Hegde joined the Center for Computational Data Science, he has worked on projects such as Illuminating 2016, Field Data Repository (FDR) and Citation Opinion Retrival and Analysis (CORA).
With the Presidential Election just around the corner, one of the Center’s biggest projects is called Illuminating 2016.
“We are analyzing the 2016 Presidential Election and social media data,” said Hegde. “We are preserving the data and using it in a manner that gives good visualizations.”
Hegde is also working with Bei Yu, an iSchool Professor, on the CORA project, which received a grant for more than $380,000 to fund masters and Ph.D. students who can help build an automated tool for citation analysis.
“It can extract opinions, answer sentiment analysis and predict citations,” said Hegde of the tool. “The main thing the tools does is identify citations and if the tone is used in a positive, negative or neutral tone.”
One of the other projects that Hegde has extensive experience with is the FDR project, which encourages researchers to deposit, store and share their data.
“FDR helps researchers deposit their data,” said Hegde. “The main purpose is to archive the data that researchers have deposited. Data is lost if you don’t deposit and preserve it in an archival fashion.”
As the data science field continues to become more popular, Hegde recommends that students become familiar with database technologies such as SQL.
“You should also know a programming language like Java or Python,” said Hegde of a key skill needed for the field. “Knowing R is also very good so that you can visualize the data and quickly understand the data.”