CV

Independent Researcher

Independent Research – Scientific Discovery

• Investigating transformer-based symbolic regression frameworks
• Evaluating efficacy of k-fold cross-validation on model generalization under small-data scenarios
• Benchmarking divide-and-conquer strategies against ensemble and data-augmentation methods

Research Intern – Principled Scientific Discovery

IBM T.J. Watson Research Center (with SLMath program)

• Selected for a competitive graduate research program on principled scientific discovery with formal methods (in partnership with SLMath)
• Engaged with IBM Research on formal reasoning and computational methods for rigorous scientific investigation

Graduate Researcher

McMaster University – Department of Mathematics and Statistics

• Identified limitations of the Dirichlet–Hawkes Process and developed the Pitman–Yor–Hawkes Process to model heavy-tailed cluster distributions in large text corpora
• Implemented full inference pipeline including Python tools, topic visualization, and Sequential Monte Carlo algorithms
• Proposed the Hierarchical Pitman–Yor–Hawkes Process to improve topic cluster continuity

Teaching Assistant (Graduate & Undergraduate)

McMaster University

• Led labs for introductory statistics, provided office-hour instruction and mentoring, assisted grading and exam evaluation

Private Tutor

Freelance

• Tutored Bayesian statistics, regression modeling, and statistical computing (R, Python, SPSS)

Researcher – Survival Analysis

University of Piraeus

• Derived likelihood and Fisher information matrices under random censoring
• Constructed MLEs with Monte Carlo validation and proposed extensions for dependent censoring models

Researcher – Theoretical Statistics

University of Piraeus – Department of Statistics and Insurance Science

• Analytical investigation of likelihood ratio properties in exponential mixtures, progressing from two-component to three-component cases

Stock Trader

Independent

• Designed active trading strategies based on liquidity, Level-II, book-map analysis, and risk control; consistent annual returns with documented performance

Ph.D. Candidate

McMaster University

Statistics

Research at the intersection of statistical machine learning, Bayesian nonparametrics, probabilistic modeling, and stochastic processes, with applications in language modeling and quantitative finance. Fully funded doctoral position.

Master of Science (M.Sc.)

McMaster University

Statistics

Thesis: Power-Law Nonparametric Bayesian Models for Continuous-Time Document Streams (Supervisor: Prof. Narayanaswamy Balakrishnan). First Class with Honours (GPA: 4.00/4.00); multiple competitive scholarships.

Bachelor of Science (B.Sc.)

University of Piraeus

Statistics & Insurance Science

GPA: 4.00/4.00 (Top 1% of cohort). Research projects on exponential mixture likelihood ratio and random censorship. Academic Excellence Awards from the University of Piraeus and the Insurance Union of Greece.

Extensive Simulation of K-Fold Cross-Validation for Transformer Symbolic Regression Models

Manuscript in preparation

Author: Banos, K.

Power-Law Nonparametric Bayesian Models for Continuous-Time Document Streams

Manuscript in preparation

Author: Banos, K.

Power-Law Nonparametric Bayesian Models for Continuous-Time Document Streams

• McMaster University

Hawkes Processes: A Switching-State Marked Hawkes Extension

• IBM T.J. Watson Research Center

Regression Models for Count Data with Excess Zeros

• McMaster University

Likelihood Ratio Order in Mixtures of Exponential Distributions

• University of Piraeus

Random Censoring and the Exponential Distribution

• University of Piraeus

McMaster University Graduate Scholarship

McMaster University

McMaster University Departmental Scholarship

McMaster University

McMaster University Research Scholarship

McMaster University

Academic Excellence Award

Insurance Union of Greece

Academic Excellence Award

University of Piraeus