Posts tagged with 'datascience'
Nov. 7, 2017
By Hana Maeda
Working in teams can bring many unexpected challenges, but one professor is looking into making that process a little easier. As part of an ongoing research project, School of Information Studies (iSchool) Associate Professor Jeffrey Saltz is continuing experiments on how teams can best work together on data science projects. Saltz is testing these experiments in his data science course, Applied Data Science, where he has teams work on different process methodologies each semester. This semester, Saltz is working on applying the Kanban methodology, a type of agile technique, to analyze how well teams work in a data science environment. And Saltz’s initial experiments suggests that Kanban “is one of the better project methodologies for data science teams.”
Saltz was inspired to take on this project from his own experiences working in data science teams for 20 years. He said that teams “would always struggle with getting all the different stakeholders on the same page and communicating and coordinating a large, diverse group of people.” For Saltz, coming to Syracuse University was the opportunity to address this challenge.
This project, Saltz said, is important because up until recently, most data scientists have worked individually. Being a ...
Sept. 17, 2016
By Jerry Robinson
As one of the iSchool's newest data science hires, Daniel Acuna has an affiliation with the Center for Computational and Data Science (CCDS). Acuna is an Assistant Professor at the Syracuse University School of Information Studies. He earned his Ph.D. in Computer Science from the University of Minnesota, Twin Cities, and completed a postdoc at the Rehabilitation Institute of Chicago and Northwestern University before joining the iSchool this fall.
Acuna's work crosses multiple disciplines including cognitive science, computer science, machine learning, and neuroscience. Currently, he most identifies with the relatively new but growing field of Science of Science.
Acuna research and tools help scientists and funding agencies to make high-quality decisions around hiring, promotion, literature search, and expertise matching. He believes his work is possible because of data science: "Data science is a fundamental area that allows me to enter a number of fields and use data to answer critical questions in those fields."
Acuna regularly relies on his background knowledge to design useful computational tools that help scientists and funders make sense of data and answer important questions in their specific domain. For instance, cognitive science helps him to understand how uncertainty factors ...
June 6, 2016
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 ...