{"id":1691,"date":"2024-09-25T19:24:11","date_gmt":"2024-09-25T19:24:11","guid":{"rendered":"https:\/\/research.uga.edu\/team-research\/?post_type=projects&p=1691"},"modified":"2024-09-25T19:26:28","modified_gmt":"2024-09-25T19:26:28","slug":"harvard-uga-collaborations-on-foundations-of-data-science","status":"publish","type":"projects","link":"https:\/\/research.uga.edu\/team-research\/projects\/harvard-uga-collaborations-on-foundations-of-data-science\/","title":{"rendered":"Harvard-UGA Collaborations on Foundations of Data Science"},"content":{"rendered":"

[vc_row][vc_column][vc_column_text css=”.vc_custom_1727292249573{margin-top: 0px !important;margin-left: 0px !important;padding-top: 0px !important;padding-left: 0px !important;}”]<\/p>\n

Teaming for Interdisciplinary Research Pre-Seed Program<\/span><\/h1>\n

[\/vc_column_text][\/vc_column][\/vc_row][vc_row bg_type=”bg_color” css=”.vc_custom_1578672371568{margin-right: 0px !important;padding-right: 0px !important;background-color: #004e60 !important;}”][vc_column width=”2\/3″][vc_column_text css=”.vc_custom_1578679527679{margin-left: 10px !important;}”]<\/p>\n

Harvard-UGA Collaborations on Foundations of Data Science<\/span><\/h3>\n

[\/vc_column_text][\/vc_column][vc_column width=”1\/3″ css=”.vc_custom_1578679376146{margin-right: 0px !important;padding-right: 0px !important;background-color: #ffffff !important;}”][vc_single_image image=”161″ img_size=”full” alignment=”right” onclick=”link_image” css=”.vc_custom_1578679545623{margin-bottom: 0px !important;padding-bottom: 0px !important;}”][\/vc_column][\/vc_row][vc_row css=”.vc_custom_1578666495607{margin-top: 10px !important;}”][vc_column][vc_row_inner][vc_column_inner width=”2\/3″][vc_empty_space][vc_column_text]The demand for employees with data science expertise has risen sharply across all sectors of the U.S.\u00a0economy. Yet, despite the best efforts of universities, industry, and government, the development of data science research and education programs faces significant challenges, including the lack of 1) deep understanding of the theoretical foundation of data science methods and techniques, 2) effective data science instruction and mentoring, and 3) a community and ecosystem for support and development. To surmount these challenges, we propose to develop the Harvard-UGA Collaborations on the Foundations of Data Science (HGCFODAS). The HGCFODAS fosters and supports: 1) interdisciplinary research and collaboration among mathematics, statistics, computer science, and electrical engineering as well as other arts, science, engineering fields to propel research development in data science; 2) interdisciplinary education and training efforts to provide a high quality workforce in data science; and 3) out-reach and partnership building between academia, government and industry to foster sustainable development in data science.<\/p>\n

The foundations of data science lie at the intersection of four research fields: theoretical computer science, statistics, mathematics, and electrical engineering. A major challenge is that each of these largely-distinct disciplines has been built based on different cultures in the use of data science to reach conclusions from data. In this project, we will borrow strengths from all four distinct cultures, adopt a diverse set of tools, and develop a coherent foundation of data science to tackle the grand challenges.[\/vc_column_text][\/vc_column_inner][vc_column_inner width=”1\/3″][vc_column_text]<\/p>\n

Team Lead<\/h4>\n

Ping Ma<\/strong>
\nDepartment of Statistics
\npingma@uga.edu<\/a><\/p>\n

Team Members<\/h4>\n

Wenxuan Zhong<\/strong>
\nDepartment of Statistics<\/p>\n

Tianming Liu<\/strong>
\nDepartment of Computer Science<\/p>\n

TN Sriram<\/strong>
\nDepartment of Statistics<\/p>\n

Yuan Ke<\/strong>
\nDepartment of Statistics<\/p>\n

WenZhan Song<\/strong>
\nSchool of Electrical and Computer Engineering<\/p>\n

Jin Ye<\/strong>
\nSchool of Electrical and Computer Engineering<\/p>\n

Qian Xiao<\/strong>
\nDepartment of Statistics<\/p>\n

Pengsheng Ji<\/strong>
\nDepartment of Statistics<\/p>\n

Ray Bai<\/strong>
\nDepartment of Statistics[\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"featured_media":0,"menu_order":0,"template":"","format":"standard","meta":{"_links_to":"","_links_to_target":""},"categories":[],"class_list":["post-1691","projects","type-projects","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/research.uga.edu\/team-research\/wp-json\/wp\/v2\/projects\/1691"}],"collection":[{"href":"https:\/\/research.uga.edu\/team-research\/wp-json\/wp\/v2\/projects"}],"about":[{"href":"https:\/\/research.uga.edu\/team-research\/wp-json\/wp\/v2\/types\/projects"}],"version-history":[{"count":0,"href":"https:\/\/research.uga.edu\/team-research\/wp-json\/wp\/v2\/projects\/1691\/revisions"}],"wp:attachment":[{"href":"https:\/\/research.uga.edu\/team-research\/wp-json\/wp\/v2\/media?parent=1691"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/research.uga.edu\/team-research\/wp-json\/wp\/v2\/categories?post=1691"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}