Call for Abstracts is now closed!
Thank you to those who have made abstract submissions. You will be notified of the status of your submission by September 21st.
If you do not see the 2020 lists of tracks once signing into EasyChair, please click on this link again to see the abstract submission page.
Scroll to bottom for template and additional instructions.
Invitation to prepare an abstract to be considered for presentation at the Virtual 4th Annual 2020 Ken Kennedy Institute Data Science Conference.
Innovation and ideas are often generated at the interface of different disciplines and industry verticals. The conference will be a research, development, and innovation (RD&I) gathering, bringing together researchers from universities, national laboratories (technology developers), industry verticals (technology consumers and deployment), mixed in with a vibrant IT industry (technology providers). This year’s virtual conference will have an online venue for networking, collaborating, and building partnerships focused around data science, machine learning, and data engineering problems and opportunities.
The Ken Kennedy Institute Data Science Conference is interested in exposing how data science can be used to address interesting challenges for translating data to knowledge through advances in data engineering, analytics, machine learning, deep learning, reinforcement learning, and more broadly, artificial intelligence (AI). The conference program will feature a mix of invited talks by leading experts, complemented by thematically organized sessions with talks selected from submitted abstracts.
We invite prospective speakers to submit extended abstracts and presentation proposals that highlight technology, use-cases, and solutions that support data-driven discovery and decision making. We encourage the broadest possible set of use-cases ranging from health care, energy, finance, insurance, transportation, urban planning, and other industries.
Accepted abstracts will be asked to deliver a 14-minute presentation, including Q&A, as part of the conference program. For the virtual conference, presentations will be live through the app portal. You will need access to Wi-Fi and a computer with microphone and camera. Following the conference, the presentation will be posted on Ken Kennedy Institute’s YouTube channel, and a PDF copy of the slides will be shared on the conference web page. Please note, the extended abstract guidelines have changed this year.
Please use the following guidelines when preparing your extended abstract submission:
- One page (not including graphics, bio, and references as needed)
- Extended abstracts should contain: title; list of all author(s) with identifying and contact information; short abstract (not to exceed 350 words); up to 5 keywords; followed by short sections covering:
- Extended abstracts must be uploaded as PDF in EasyChair. The short abstract and the keywords from your extended abstract must also be pasted into the appropriate text box in the web submission form.
- This year we are asking authors to categorize abstracts into one of four different tracks:
- 1) COVID-19,
- 2) Healthcare,
- 3) Business Impact/Industry, and
- 4) Algorithms, Visualizations, and Foundations
- To submit presentation proposals, go to http://dsconference.rice.edu.
- NOTE: We are also accepting posters from academic researchers, such as students and post-docs.
Note 1: This conference will consider and can accept abstracts for work that has previously been presented.
Note 2: Presentation proposals that appear to the program committee as “marketing” will be rejected. Abstracts with a strong and compelling customer use-case with the focus on the innovation knowledge discovery enabled by the solution more than the product can be considered. Vendors interested in engaging are also encouraged to explore sponsorship.
Please share the call for participation with anyone that you think might be interested in submitting an extended abstract and/or attending the 4th Annual Ken Kennedy Institute Data Science Conference at Rice University.