Jason Wiese is an Assistant Professor in the School of Computing at the University of Utah where he leads the Personal Data and Empowerment Lab (PeDEL). His research takes a user-centric perspective of personal data, everyday computing experiences, and end-user empowerment. His work spans personal informatics, accessibility, privacy, user-centered design, and real-world deployments. Dr. Wiese’s research excellence has been recognized by paper awards at DIS, CHI, and EICS, and through individual awards, including: recognition as a Yahoo Fellow in 2014, the Stu Card Fellowship in 2012, and the Yahoo! Key Scientific Challenges Award in 2011. He publishes work in top Computer Science and HCI venues including CHI, DIS, CSCW, and UbiComp/IMWUT. He received his Ph.D. in Human-Computer Interaction from Carnegie Mellon University in 2015.
Dr Eric Mercer was the 2021 Amazon Research Awards recipient in AUTOMATED REASONING.
Monday September 13th at 2pm
Advisor: Mark Clement
Friday July 30 at 10am
Advisor: Mark Clement
David is a recent graduate of the University of California Santa Barbara in the Electrical and Computer Engineering Department. His research interests are centered on multiagent systems, game theory, distributed optimization, mechanism design, and security, however, he’s genuinely open to new domains of thinking which may challenge his assumptions or deepen his appreciation of current understanding. Alongside his academic pursuits, he has been able to work in industry for Applied Invention and MIT Lincoln Laboratories, allowing him to apply theory to several industries, including agriculture, national defense, travel, security, and aerospace. He has also been a leading member of Achilles Heel Technologies, a startup company applying systems theory to the security of critical infrastructures.
Thursday, July 8th at 11:00am, 3350 TMCB
Advisor: Kevin Seppi
Wednesday, June 23 at 11:00am
Advisor: Jonathan Sillito
Wednesday, June 9th at 4:00pm
Advisor: Daniel Zappala
Watch Ryan Gabriel's devotional, Healing Racism Through Jesus Christ, and learn more about how we can "work hard to heal the painful legacies of racism that we inherited."
Tuesday, May 25th at 1:00pm
Advisor: David Wingate
The web application "Relative Finder", developed by BYU CS students now has 1 Million Users. This is a major milestone for the Family History Technology Laboratory
Porter is extremely excited to be joining the faculty at BYU. His main area of research is Artificial Intelligence, where he tries to help machines learn a little bit more like humans. He received a PhD from Penn State studying machine learning and data mining, and BS in Statistics from BYU.
Friday, March 26th at 11am
Advisor: Casey Deccio
Wednesday, March 31st at 3:00pm
Advisor: Parris Egbert
The month of February is Black History Month. It's an annual celebration of recognizing the achievements and the role of African Americans in U.S. History. For Black History Month, the BYU Student Service Association PEN Talks with collaboration with the Kennedy Center, Global Women's Studies, and clubs including BYU Women of Color, and BYU Black Student Union are hosting a panel discussion on the topic "Black Women Throughout Social Movements."
Welcome to the CS Department's second edition of Threads, a student-driven publication of "thread" papers describing the evolution of various ideas in computer science. The topics for these papers were chosen by the students in CS 611, the only required course for our Ph.D. students, who then researched and wrote the papers making up the publication. Our hope in sharing them with you is that they will give you a glimpse of the kinds of ideas these advanced students are engaging, expose you to the stories behind the evolution of a number of great ideas in computer science, and inspire rich technical conversations throughout the department. Enjoy!
February 10-March 13
For more educational resources from CS Inclusion, Diversity, & Equity (CSIDE), please visit inclusion.cs.byu.edu.
AI-driven user profiling based on user data is a key component of providing a personalized experience on Facebook. However, public concern has grown around social media platforms profiling users to infer fine-grained interests and characteristics such as race, religion, or socioeconomic status, which can be used for secondary purposes such as targeted advertising. In fact, there have been recent public outcries over how such micro profiling has been used to sway political views, as well as concern over how people’s emotional and psychological well-being can be negatively affected. This project investigates how to leverage one of the most popular medium for engaging viewers, Youtube videos, to increase digital literacy and help users limit such profiling. This is an interdisciplinary effort drawing from Media and Film studies, Applied Artificial Intelligence, and Human-Computer Interaction.
Ten Computer Science students, including Stanley Fujimoto and Eric Burdett, have been instrumental in using handwriting recognition to find which people died in the 1918 pandemic in the United States. To create the dataset, students identified and retrieved hundreds of thousands of relevant images from FamilySearch.
“That’s been quite a process because their collections are just massive,” said Burdett, who wrote computer code to interface with FamilySearch’s system. “We have access to millions and millions of records from FamilySearch, resources a lot of researchers haven’t had before.”
To teach the computer to extract relevant entries from certificates with varying layouts, Fujimoto modified and trained object detection algorithms typically used to identify people or cars in images. The students in the lab transcribe causes of death using a state-of-the-art handwriting recognition algorithm created by former BYU graduate student Curtis Wigington. Once they obtain the transcriptions, students assign a diagnosis code to the certificates to standardize differing ways coroners described the same cause of death. The automated process has allowed them to transcribe over 100,000 death records in under 2 hours, compared with the weeks or months of labor that human-generated transcriptions require.
For many, involvement in the project will shape their professional futures.
“This project is giving us the skills to be able to function in jobs in big fields in computer science like machine learning and artificial intelligence,” Burdett said.
As for Fujimoto—despite his past indifference to genealogy—seeing cutting-edge computer science and machine learning applied to family history has inspired him to take a full-time position as a data scientist with Ancestry.com.
September is National Suicide Prevention Month. For information and resources, check out http://cswomen.byu.edu/help-for-students-in-crisis/.
The following policy will help employees and students to remain safe as we deal with the COVID-19 pandemic. Infectious diseases, such as COVID-19, can have a huge impact on you and on those that work and study around you. In an effort to reduce that impact we will be strictly following the guidance and policies of the university and of the government. University and government (both State and County) policies are continually being updated, and those policies and requirements will always supersede the department policy outlined below. We will do our best to keep this document current, but intentionally do not exhaustively repeat the university/government policies here.
Computer Science Department
Brigham Young University
3361 TMCB PO Box 26576
Provo, Utah 84602