{"id":558,"date":"2019-08-06T22:11:25","date_gmt":"2019-08-06T22:11:25","guid":{"rendered":"http:\/\/sites.rutgers.edu\/idsla\/?page_id=558"},"modified":"2019-08-08T17:31:47","modified_gmt":"2019-08-08T17:31:47","slug":"past-events-2","status":"publish","type":"page","link":"https:\/\/sites.rutgers.edu\/idsla\/past-events-2\/","title":{"rendered":"PAST EVENTS"},"content":{"rendered":"

Women in Data Science (WiDS) Conference, 2017<\/strong><\/h3>\n

Fri, Feb 3, 2017<\/p>\n

Rutgers University-Newark<\/p>\n

\"\"<\/p>\n

Women in Data Science (WiDS) Conference promotes and motivates women in the field of Data Science, providing a platform to present their cutting-edge research. It also aims to strengthen the academe- industrial ties.The one-day technical conference will provide opportunity to hear about the latest data science related research in a number of domains, learn how leading-edge companies are leveraging data science for success, and connect with potential mentors, collaborators, and others in the field.<\/p>\n

More Info :https:\/\/sites.google.com\/site\/womenindatasciencerutgers\/home<\/a><\/p>\n

 <\/p>\n

<\/h3>\n

CHMPR Technical and IAB 2017 Semi-Annual Meeting<\/strong><\/h3>\n

Wed, May 31, 2017<\/p>\n

Rutgers University-Newark<\/p>\n

\"\"<\/p>\n

Semi-annual Industrial Advisory Board (IAB) Meetings are an opportunity for face-to-face collaborations among CHMPR members. Industry members, research faculty, and students review the progress of current projects and the potential of proposed projects; discuss the performance of CHMPR relating to research areas, test beds, education, and technology transfer; and investigate prospective research topics to address current and future industry needs.<\/p>\n

More Info:\u00a0https:\/\/sites.google.com\/view\/rutgers-chmpr-iab-meeting\/home<\/a><\/p>\n

 <\/p>\n

<\/h2>\n

Rutgers University-Newark Research Computing Fair<\/strong><\/h3>\n
\n
\n
Mon, Nov 6, 2017<\/span><\/div>\n
<\/div>\n
Rutgers University-Newark\u00a0<\/span><\/div>\n<\/div>\n<\/div>\n

\"\"<\/p>\n

11:30AM – 11:45AM A word with Dr.Nabil Adam<\/p>\n

11:45AM – 12:00PM Discussion with Rutgers CIO Michele Norin<\/p>\n

12:00PM – 01:30PM Lunch,poster session, tour of Data center (Englehard Hall)<\/p>\n

01:30PM – 02:00PM Hackathon by John Cain & Amarel Experts<\/p>\n

More Info:\u00a0http:\/\/cimic.rutgers.edu\/HighPerformanceComputing\/idsla-hpc.html<\/a><\/p>\n

 <\/p>\n

NSF Conference on Practice and Science of Public Participation in STEM Research on Data Enabled Science and Engineering<\/strong><\/h3>\n

Thu, Feb 8, 2018<\/p>\n

Rutgers University-Newark<\/p>\n

More Info\u00a0http:\/\/cimic.rutgers.edu\/NSF-PPSR-Abstract-final.pdf<\/a><\/p>\n

 <\/p>\n

ACM\/IEEE JCDL 2016<\/strong><\/h3>\n

Sun, Jun 19, 2016 to Thu, Jun 23, 2016<\/p>\n

Rutgers University, Newark<\/p>\n

\u201cBig Libraries, Big Data, Big Innovation\u201d.<\/h4>\n

\"\"<\/p>\n

The Joint Conference on Digital Libraries (JCDL) is a major international forum focusing on digital libraries and associated technical, practical, and social issues. Participation is sought from all parts of the world and from the full range of disciplines and professions involved in digital library research and practice, including computer science, information science, librarianship, archival science and practice, museum studies and practice, technology, medicine, social sciences, and humanities. All domains – academics, government, industry, and others – are encouraged to participate as presenters or attendees.<\/p>\n

CO-SPONSORED BY: ACM, IEEE, Rutgers I-DSLA, More Info\u00a0http:\/\/www.jcdl2016.org<\/a><\/p>\n

 <\/p>\n

This is Data Science! Speaker series<\/strong><\/h3>\n

Fri, Feb 19, 2016 – 9:52pm to Fri, May 6, 2016 – 9:52pm<\/p>\n

Aidekman Research Center (CMBN)<\/p>\n

\"\"<\/p>\n

Rutgers is happy to announce the Data Science speaker series and line-up for the spring 2016. As you will see, the speakers span education, text analysis, computational neuroscience and from rising stars to established leaders in their fields. The goal is to show off the many ways in which data science is affecting diverse areas of scholarship. Talks are all scheduled for Fridays at 2:30 in Aidekman’s first floor auditorium. I look forward to seeing you there!<\/p>\n

 <\/p>\n

 <\/p>\n

2\/5\/2016 – Ryan Baker, Associate Professor of Cognitive Studies in Education, Columbia University Teachers College. Research area: Educational data mining. 371A Smith Hall<\/p>\n

2\/19\/2016 – Eugene Wu, Assistant Professor of Computer Science, Columbia University. Research area: Visualization and databases<\/p>\n

3\/25\/2016 – Brenden Lake, Moore-Sloan Data Science Fellow Center for Data Science, NYU, Research area: Computational models of human and machine cognition<\/p>\n

4\/8\/2016 – Stephan Mandt, Postdoctoral Researcher in the Institute for Data Sciences and Engineering, Columbia University. Research area: Statistical machine learning<\/p>\n

4\/15\/2016 – Barbara Engelhardt, Assistant Professor Department of Computer Science, Princeton University. Research area: Statistical models and methods for analysis of high-dimensional data and biological mechanisms of complex phenotypes and human diseases.<\/p>\n

4\/22\/2016 – Mark Finlayson, Assistant Professor of Computer and Information Sciences, Florida International University. Research area: Computational models of narrative<\/p>\n

5\/6\/2016 – Nathaniel Daw, Professor of Princeton Neuroscience Institute and Department of Psychology, Princeton University. Research area: Reinforcement learning from computational, neural, and behavioral perspectives<\/p>\n

 <\/p>\n

NSF Workshop 2016<\/strong><\/h3>\n

Thu, Jan 7, 2016 to Fri, Jan 8, 2016<\/p>\n

NY Academy of Sciences<\/p>\n

\"\"<\/h5>\n

“Data Science, Learning, and Applications to Biomedical & Health Sciences (DSLA-BHS2016)”
\nSPONSORED BY: Rutgers I-DSLA, the NSF Smart and Connected Health Program, the NSF North East Big Data Innovation Hub and in Partnership with the NYAS<\/p>\n

More info :\u00a0https:\/\/sites.google.com\/site\/dslabhs2016\/\u00a0<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

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