My name is Kayla Frisoli, and I am a Ph.D. student in the Department of Statistics at Carnegie Mellon University. I graduated with a Bachelor of Science from the Department of Statistics at UCLA in 2015. My current research interests lie in statistical methodology for social science applications including: record linkage, clustering, topic modeling, and active learning. In my free time, you may find me cooking, watching/playing sports, or listening to live music.
News and upcoming events
- I was awarded the 2018 Gertrude M. Cox Scholarship Honorable Mention
- I received the CMU ProSEED/Crosswalk grant for work with Women in Statistics at CMU
- I helped organize WiDS Pittsburgh @CMU
- August 2018 – Joint Statistical Meetings – Vancouver, BC, Canada
- July 2018 – Working Group on Model-based Clustering – University of Michigan, Ann Arbor, USA
- June 2018 – Classification Society Annual Meeting – Stony Brook University, New York, USA
- May 2018 – Electronic Conference On Teaching Statistics (eCOTS)
I work with Dr. Rebecca Nugent on problems in record linkage. Record linkage is the process of identifying records corresponding to unique entities across datasets.
We are currently working on linking historical Irish census data. We propose extending a typical linkage framework to include familial network structure and to allow for expected field changes. Our application (Ireland census records from 1901 and 1911) provides challenges including: limited, non-standardized fields, errors due to formatting and the digitization of hand-written records, and high frequencies of common names. We recently traveled to Dublin, Ireland to work with collaborators Dr. Brendan Murphy and Dr. Michael Fop on this problem.
My previous record linkage project was at the U.S. Census Bureau, where I was advised by Dr. John Abowd, Dr. Steve Fienberg, Dr. Samuel Ventura, and Dr. Jared Murray. We developed a semi-supervised approach to record linkage at the U.S. Census Bureau and utililized active learning to extend current unsupervised methods in order to capitalize on the benefits of supervised learning (NSF grant: SES1130706).
2017-2018 PhD TA Excellence Award 2015-2016 PhD TA Excellence Award
- Summer 2018: 36-315, Statistical Graphics and Visualization, Syllabus
- Manage and coordinate the conversion of 36-202 to R Studio:
Spring 2018: 36-202, Statistics & Data Science Methods, Syllabus
- Spring 2018: 36-202, Statistics & Data Science Methods, Syllabus
- Fall 2017: 36-661, Statistical Methods in Epidemiology, Syllabus
- Spring 2017: 36-200, Reasoning with Data, Syllabus
- Spring 2016: 36-315, Statistical Graphics and Visualization, Syllabus
- Fall 2015: 46-923, Introduction to Statistical Inference, Syllabus
- Fall 2015: 46-921, Introduction to Probability, Syllabus
- Courses: Algebra, Geometry, Pre-Calculus, Calculus, AP Statistics, Introductory Probability
In the Pittsburgh community, I am the Organizer for the Pittsburgh userR Meetup and a judge for the Pittsburgh Data Jam. I also serve as the American Statistical Association Pittsburgh Chapter Student Representative.
At Carnegie Mellon University, I am the Community Outreach Chair for the CMU Women in Statistics group and an ambassador for Women in Data Science (WiDS). I also act as a member of the CMU Graduate Student Assembly Social Committee. Within the CMU Statistics and Data Science Department, I serve as the president of the Student Advisory Committee, am an official mentor to younger students, and organize events for our Ph.D. admissions committee.
At UCLA, I was the President of the Statistics Club and helped organize UCLA DataFest. I was the Assistant Financial Vice President and Greek Relations chair of my sorority, Gamma Phi Beta. I was chosen as the commencement speaker for the Department of Statistics graduation ceremony in 2015. I give back to UCLA by hosting alumni dinners in Pittsburgh and acting as a mentor for the UCLA Alumni Mentor Program.