About Me

AI Researcher, Centre for Clinical Pharmacology and Precision Medicine at the William Harvery Research Institute (WHRI), Queen Mary University of London (QMUL). PhD in probabilistic machine learning, applied to how the brain processes musical rhythm, using computational cognitive models and probabilistic machine learning; studied at QMUL, supervised by Marcus Pearce and Lorenzo Jamone, in the Music Cognition Lab and CRISP groups (CogSci and ARQ groups); studentship supported by MAT.

Experience

Previously: Fidelity Intl. (2015), BAML (2014) & Splunk (2013)

Education

Publications

Google Scholar.

  1. Thomas Kaplan. Probabilistic Models of Rhythmic Expectation & Synchronisation. PhD Thesis, Queen Mary University of London, School of Electronic Engineering and Computer Science. (2024) {url}.
  2. Ana Clemente, Thomas Kaplan, Marcus Pearce. Perceptual representations mediate effects of stimulus properties on liking for music. Annals of the New York Academy of Sciences. (2024) {doi,url}.
  3. Jonathan Cannon, Thomas Kaplan. Inferred representations behave like oscillators in dynamic Bayesian models of beat perception. Journal of Mathematical Psychology. 122, e102869. (2024) {doi,url}.
  4. Thomas Kaplan, Lorenzo Jamone, Marcus Pearce. Probabilistic modelling of microtiming perception. Cognition. 239, e105532. (2023) {doi,url}.
  5. 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}.
  6. Thomas Kaplan, Elaine Chew. Detecting low frequency oscillations in cardiovascular signals using Gradient Frequency Neural Networks. IEEE Computing in Cardiology (CinC) (2019) {doi, url}.
  7. 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}
  8. James Arram, Moritz Pflanzer, Thomas Kaplan, Wayne Luk: FPGA acceleration of reference-based compression for genomic data. {url, doi}
  9. Thomas Kaplan, Optimising Bisulfite Sequencing Analysis, 2015. {pdf}

Conferences & Seminars

Teaching

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

Contact

✉️ Email: thomas•m•kaplan✉gmail•com

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