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BE Doctoral Dissertation: “Using Machine Learning and Natural Language Processing to Improve Scientific Processes”
June 8, 2021 at 10:30 AM - 12:30 PM
The Department of Bioengineering at the University of Pennsylvania and Dr. Konrad Kording are pleased to announce the Doctoral Dissertation Defense of Titipat Achakulvisut.
Using Machine Learning and Natural Language Processing to improve scientific processes
Scientific information has been growing exponentially over the past decades. Arguably, traditional processes of doing science cannot keep up with this growth. This expansion has a scaling impact on scientific activities such as funding, the review process, conferences, and exploring the literature. To improve on the traditional scientific processes, useful tools and understanding of these processes are crucial. This dissertation advances the scientific processes by incorporating knowledge and tools from natural language processing (NLP) and machine learning (ML). We discuss the applications in three applications of scientific endeavors including (1) extracting scientific claims for scientific literature, (2) improving on traditional conferences with data-driven approaches, and (3) understanding the funding process using the content of applications. To complement our findings, we provided open-source software, tools, and real-world implementation for other researchers. In sum, this thesis serves as both a conceptual point of view and proof-of-concept implementations of how we can improve science through the use of ML and NLP.
Scientific information has been growing exponentially over the past decades. Arguably, traditional processes of doing science cannot keep up with this growth. This expansion has a scaling impact on scientific activities such as funding, the review process, conferences, and exploring the literature. To improve on the traditional scientific processes, useful tools and understanding of these processes are crucial. This dissertation advances the scientific processes by incorporating knowledge and tools from natural language processing (NLP) and machine learning (ML). We discuss the applications in three applications of scientific endeavors including (1) extracting scientific claims for scientific literature, (2) improving on traditional conferences with data-driven approaches, and (3) understanding the funding process using the content of applications. To complement our findings, we provided open-source software, tools, and real-world implementation for other researchers. In sum, this thesis serves as both a conceptual point of view and proof-of-concept implementations of how we can improve science through the use of ML and NLP.
The public is welcome to attend.
Please join Zoom Meeting
https://upenn.zoom.us/j/
Meeting ID: 937 5024 9969
Passcode: 224865
https://upenn.zoom.us/j/
Meeting ID: 937 5024 9969
Passcode: 224865
Titipat Achakulvisut
PhD Candidate
More information can also be found on Titipat’s personal page: