Aidan P. LaBella

Brown University

CIT Building, Brown University

115 Waterman St,

Providence, RI 02906

I am currently a Ph.D. student at Brown University in the Department of Computer Science where I am advised by Steve Bach in the BATS research group and AI ‘superlab’. I am primarily interested in developing novel solutions for mining and learning from large, real-world datasets while also exploiting new methods for harvesting and labeling data.

Before starting my graduate studies at Brown, I graduated with my B.Sc. in Computer Science from Rochester Institute of Technology. I was advised by Travis Desell and worked as an Undergraduate Reseach Assistant in the Distributed Data Science Systems (D2S2) lab.


Sep 1, 2023 Started my Ph.D. at Brown!
May 13, 2023 Graduated from RIT with my B.Sc. (cum laude) in Computer Science! So thankful to my family, friends, lab-mates and advisors for helping me get to this point!
Mar 18, 2023 I’m super excited to announce that upon completion of my BSc at RIT, I will be joining the BATS research group at Brown University for my Ph.D. in Computer Science, where I will be advised by Stephen Bach!
Dec 15, 2021 Our paper “Optimized Flight Safety Event Detection in the National General Aviation Flight Information Database” was accepted to ACM’s Symposium on Applied Computing (SAC ‘22)!
Nov 12, 2021 Our paper “Predictive Maintenance for General Aviation Using Convolutional Transformers”, has been accepted for presentation as an Emerging Application of AI paper at the Thirty-Fourth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-22)!

selected publications

  1. IAAI 2022
    Predictive Maintenance for General Aviation Using Convolutional Transformers
    Hong Yang, Aidan LaBella, and Travis Desell
    In Proceedings of the AAAI Conference on Artificial Intelligence 2022
  2. ACM SAC ’22
    Optimized flight safety event detection in the national general aviation flight information database
    Aidan P LaBella, Joshua A Karns, Farhad Akhbardeh, Travis Desell, Andrew J Walton, Zechariah Morgan, Brandon Wild, and Mark Dusenbury
    In Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing 2022