Institute for Data Science
The Institute for Data Science works with faculty, students, and the community and promotes the advance of data science and machine learning.
Email:
ids@olemiss.eduOffice Location:
Office of Research and Sponsored Programs, 313 LyceumPhone:
662-915-7583Office Hours
8:00 - 5:00, Monday - Friday
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Goals
For faculty: provide opportunities for existing and future faculty to engage in, collaborate on, and compete for sponsored research projects that advance data science and machine learning methods or apply them to solve problems of importance to society, by giving support in grant writing and data analysis.
For students: provide opportunities for students in existing programs to develop analytics skills through new courses, workshops, summer internships, and faculty-mentored research experiences.
For external connections: provide a unified interface to large and small companies and non-governmental organizations looking to engage data science experts in the ethical use of data to create new enterprise, solve business problems, and improve society.
Mission
Fostering interdisciplinary research and education in multidisciplinary grand-challenge areas;
Strengthening and expanding the University network by enhancing relationships with world-class researchers and establishing links and creative partnerships with industry leaders, community, and government stakeholders;
Supporting current graduate and undergraduate degree offerings involving data science and analytical skills.
Institute Faculty and Staff
Panduka Nagahawatte
- Director of the Institute for Data Science
Lori Nichols
- Data Scientist
Hong Xiao
- Assistant Professor of Computer and Information Science
Affiliated Faculty and Staff
Our research faculty look forward to collaboration across campus. Don't hesitate to reach to find out how you can contribute.
Richard Balkin
- Chair and Distinguished Professor of Counselor Education
John Bentley
- Professor of Pharmacy Administration and Marketing and Research Professor in the Research Institute of Pharmaceutical Sciences and Director of the Center for Pharmaceutical Marketing and Management Pharmacy Administration
Yunhee Chang
- Professor of Nutrition and Hospitality Management
Yixin Chen
- Chair and Professor of Computer and Information Science
Amar Chittiboyina
- Principal Scientist and Associate Director of the National Center for Natural Products Research and Research Professor in BioMolecular Sciences
Jiayu Fang
- Research Scientist
Matthew Jessee
- Interim Chair and Associate Professor of Health, Exercise Science, and Recreation Management
Minsoo Kang
- Professor of Health, Exercise Science, and Recreation Management
Jing Li
- Assistant Professor of Medicinal Chemistry and Research Assistant Professor in the Research Institute of Pharmaceutical Sciences
Ryan Parsons
- Assistant Professor of Sociology and Southern Studies
Joseph Wellman
- Associate Professor of Psychology and Director of Experimental Training
Partnerships
You’re welcome to partner with us! Please contact ids@olemiss.edu for more details.
Please fill out this form if you want to tell us more about yourself.
Resources
See our recommended data science resources, both free and paid.
Free software
R: good for statistical modeling and bio-informatics analysis. Rstudio is a premium IDE for R and home for R Shiny web applications. Find Cheat sheets for R here.
Python: good for machine learning.Deep learning packages include Pytorch, Tensorflow and Keras. Find cheat sheets for Python here.
Orange: complete workflow package for data mining.
Free software for university users
Mathematica: Go here, find the “Mathematica” and download.
Matlab: Go here, find the “Matlab” and download.
Tableau: Go here. Viewers can just sign in using their webID. Producers in the university need to send request using this form. Students can get a free desktop version here.
Paid software
Prism: easy to use for those who have fewer knowledge on statistics and coding, with user interface and a lot of help and tutorials.
SAS: is a commercial statistics software that has been widely used in health care and social science.