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Proceedings of the 2023 ADSA Annual Meeting
2023 Academic Data Science Alliance Annual Meeting
October 24-27, 2023
University of Texas at San Antonio
The Proceedings of the ADSA Annual Meeting contain papers, posters, conference session summaries, and other materials presented at or associated with the ADSA Annual Meeting.
About the ADSA Annual Meeting
The ADSA Annual Meeting convenes data science practitioners from all disciplines and career stages to share state-of-the-art approaches in data science research and education, with a strong emphasis on responsible data science. We encourage new, untested ideas to promote brainstorming for innovation,collaborative feedback, and engaging discussions. One focus of this meeting is building new collaborations, which we facilitate through networking and sessions that focus on data types.
Each year, we aim to leverage local strengths to focus the meeting on specific domains. For the 2023 meeting at University of Texas at San Antonio, we are highlighting the strong presence of biosciences/healthcare and the arts (especially cultural and public) in San Antonio for a special theme day: "Health, Well-being, and the Arts".
Published: Oct 12, 2023
Introduction to the ADSA Annual Meeting along with a downloadable program book.
Published: Oct 12, 2023
Information about the keynote speakers at the 2023 ADSA Annual Meeting
ET
RC
DP
Published: Nov 21, 2023
Presented at the Data Science for Social Good panel
DD
MM
Published: Nov 15, 2023
Clinical trials generate a wealth of data. To maximize the utility of this data, it is critical that data be made FAIR (Findable, Accessible, Interoperable and Reusable) and that we have to tools necessary to properly analyze this data.
JJ
Published: Nov 16, 2023
Despite the expanding educational and employment opportunities in developed countries, many young adults aged 16-24 are neither enrolled in school nor employed—opportunity youth—in the U.S. This study explores some of the health implications of not addressing this disengagement.
SS
Published: Nov 16, 2023
The Data Science by Design collective has self-published two anthologies of creative, data-inspired, and data-informed art and written work. The goals of these anthologies are to broaden the idea of what data is and what “doing” data science means.
Published: Nov 28, 2023
This study analyzes the effectiveness of Neural-ODEs in pharmacokinetics (PK) modeling by benchmarking ODEs against other state-of-the-art approaches for time-series modeling. The study also evaluates ODEs in noisy and missing data simulations to mimic real-world settings.
TK
DH
JJ
JL
DW
Published: Nov 16, 2023
The Center for TAIMing AI is a pilot center at the University of North Carolina at Charlotte
RS
IT
JN
AM
SF
SH
Published: Nov 16, 2023
RS
SS
IT
Published: Nov 16, 2023
AD
Published: Nov 17, 2023
Pearls in vision health research with special data science implications, as part of ADSA 2023 "Learning from data in complex and heterogeneous biological systems" session
HG
JL
MB
HR
Published: Nov 17, 2023
This abstract describes a birds-of-a-feather session which focused on the development of accelerated pathways to good jobs in data science and artificial intelligence at community colleges.
Published: Jan 10, 2024
This is the story of the author's first introduction into technology for research in 1961 and then across the decades as she learns to compile data first in Pro-Cite (now defunct) and presently Endnote, with misadventures along the way.
RM
PS
KB
BV
LH
Published: Nov 21, 2023
LINflow is designed to automate LIN assignments to genomes using their data, i.e., nucleotide content, by considering one or more organism comparison measurements.
TJ
ML
Published: Nov 21, 2023
We investigate the value of information through a randomized controlled trial on market design in the market for sanitation services in Burkina Faso.
MW
Published: Nov 29, 2023
DD
Published: Dec 06, 2023
In this work, we demonstrate OrgaTuring, an end-to-end vision AI approach that can locate, quantify, and classify human colon organoids with an accuracy of 90%.
LA
Published: Dec 06, 2023
We will discuss why this is a fundamental question in Data Science and how we connected the concept to educational experience of the next generation of Data Scientists.
CV
Published: Dec 06, 2023
Making use of exploratory graph analysis (EGA) framework, we will summarize the changes over time in three key indicators: science identity, research self-efficacy, and academic self-concept.
SP
Published: Dec 06, 2023
I will discuss our research (currently ongoing) into the impact of GenAI on legal education and the profession.
MB
Published: Dec 06, 2023
SB
RL
DS
ZZ
Published: Dec 06, 2023
MB
EG
Published: Dec 06, 2023
