About Me

PhD student exploring how the brain processes musical rhythm, using computational cognitive models and probabilistic machine learning. Additionally, an amateur drummer, building a new kind of electronic snare drum. Studying at Queen Mary University of London (QMUL), supervised by Marcus Pearce and Lorenzo Jamone, in the Music Cognition Lab and CRISP groups. Respectively, these are part of the CogSci and ARQ Research Groups. Studentship supported by MAT.




Google Scholar.

  1. Thomas Kaplan, Lorenzo Jamone, Marcus Pearce. Probabilistic modelling of microtiming perception. PsyArXiv. (2022) {url}.
  2. Thomas Kaplan, Jonathan Cannon, Lorenzo Jamone, Marcus Pearce. Modelling enculturated bias in entrainment to rhythmic patterns. PLoS Comput. Biol. 18(9): e1010579.(2022) {url, doi, pdf}.
  3. Thomas Kaplan, Elaine Chew. Detecting low frequency oscillations in cardiovascular signals using Gradient Frequency Neural Networks. IEEE Computing in Cardiology (CinC) (2019) {doi, url}.
  4. James Arram, Thomas Kaplan, Wayne Luk, Peiyong Jiang: Leveraging FPGAs for Accelerating Short Read Alignment. IEEE/ACM Trans. Comput. Biology Bioinform. 14(3): 668-677 (2017) {url, doi}
  5. James Arram, Moritz Pflanzer, Thomas Kaplan, Wayne Luk: FPGA acceleration of reference-based compression for genomic data. {url, doi}
  6. Thomas Kaplan, Optimising Bisulfite Sequencing Analysis, 2015. {pdf}

Conferences & Seminars


Demonstrator in the School of Electronic Engineering & Computer Science (EECS), QMUL:


✉️ Email: thomas•m•kaplan✉gmail•com


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