Creagh Briercliffe Email & Phone Number

Vancouver, BC, CA

Vancouver, British Columbia, Canada

San Francisco, California, United States

• Led the design of a machine learning system that utilized retailer and customer data to learn product attributes.
• Lead Inventor on U.S. Patent Application (No. 17/935,916), titled “Item Attribute Determination Using a Co‑Engagement Graph.”
• Developed a prototype using a human‑in‑the‑loop model with semi‑supervised learning, leveraging both text and graph data.

Vancouver, British Columbia, Canada

• Researched change‑point detection on multivariate event sequences, with applications in detecting financial market shifts.
• Constructed a novel deep learning architecture: Transformers for sequence embedding, stacked with a MLP for change‑point detection.
• Executed experiments that demonstrated superior performance and efficiency compared to the state‑of‑the‑art based on Hawkes processes.
• Developed models in PyTorch; trained, validated, and tested on a GPU cluster.

My main research focus is towards constructing Bayesian models to discover hidden structure in complex network data.

DSCI 563: Unsupervised LearningDSCI 553: Statistical Inference & Computation IISTAT 300: Intermediate Statistics for ApplicationsSTAT 203: Statistical MethodsSTAT 201: Statistical Inference for Data ScienceSTAT 200: Elementary Statistics for Applications

Vancouver, British Columbia, Canada

• Mentored researchers from various fields, resulting in successful publication of their research.
• Designed, executed and interpreted statistical analyses for clients, utilizing methods such as mixed‑effects & generalized linear models.
• Developed and presented training on statistical methods to clients with little or no statistical background.

Developed Bayesian stochastic models for analyzing the batting performance of cricket players. Research led to journal publication.Research supervisors: Prof. Saman Muthukumarana & Dr. Theo Koulis

Managed medical databases; performed error analysis and quality control on patient records.

Studied consistency properties of estimators in linear error-in-variables models.Research supervisor: Prof. Yuliya Martsynyuk

Doctor Of Philosophy (Ph.D.), Statistics

Dissertation: "Bayesian Models for Hierarchical Clustering of Network Data" Supervisors: Alexandre Bouchard-Côté & Paul Gustafson Funding.

Master Of Science (M.Sc.), Statistics

Thesis: "Poisson Process Infinite Relational Model : a Bayesian nonparametric model for transactional data." Funding: NSERC Canada.

Bachelor Of Science (B.Sc.) Joint Honours, Computer Science & Statistics, First Class Honours

CS specialization in Artificial Intelligence