Headshot of Samuel Veer Singh

Samuel Veer Singh

PhD Student, Trinity College Dublin • Machine Learning, Functional Data & Clustering

Clustering Functional Data Time Series Health Tech

About

I’m interested in unsupervised learning for multivariate and manifold functional data. My current work explores clustering methods and representation learning to make sense of long-horizon physiological signals.

Highlighted Projects

  • Cluster Analysis of Multi-Variate Functional Data via Non-linear Representations — methods for grouping long-form sensor signals (e.g., heart rate, activity) modeled as continuous functions of time.
  • Wearable Data Pipelines — cleaning, windowing, and feature extraction for noisy on-body sensors.

Publication

  • S. Singh, S. Coyle, and M. Zhang. Shape-informed clustering of multi-dimensional functional data via deep functional autoencoders. In Advances in Neural Information Processing Systems (NeurIPS), Curran Associates, Inc., 2025. [CORE A*]

Curriculum Vitae

Work Experience

  • Master's Thesis Researcher · Empa — Transport at Nanoscale Interfaces
    Mar 2021 – Mar 2022 · Dübendorf, Switzerland
    • Cluster analysis of datasets acquired on quantum devices.
    • PROMOS (DAAD) stipend for the research stay; thesis graded 1.3.
  • Graduate Research Assistant · RWTH — Institut für Werkstoffe der Elektrotechnik II
    May 2020 – Mar 2021 · Aachen, Germany
    • Project on Kinetic Monte‑Carlo simulation of electrochemical metallisation (ECM) cells.
    • Developed a 1‑D compact physical model and a MATLAB App Designer GUI for ECM simulations.

Academia

  • Ph.D. (Statistics) — School of Computer Science & Statistics · Trinity College Dublin
    Sep 2023 – Present · Dublin, Ireland
    • Research focus: Machine Learning, Functional Data, and Clustering; funded by Research Ireland via the d‑real project.
    • Thesis: Cluster Analysis of Multi‑Variate Functional Data through Non‑linear Representation Learning.
  • M.Sc. Physics · RWTH Aachen University
    Oct 2019 – Jul 2022 · Aachen, Germany · Final grade: 1.8
    • Thesis: An unsupervised model to classify univariate datasets acquired on nanoscale devices.
    • Specialisation in computational physics and deep learning for physics research.
  • B.Sc. Physics (Hons) · St. Stephen's College
    Jul 2016 – May 2019 · Delhi, India · Final grade: 1.7
    • Focus on implementing physical models via computational methods.
  • Indian School Certificate (ISC) · La Martiniere College
    Completed May 2015 · Lucknow, India ·