Fall 2026 (TBD)
Spring 2026
April 26: Granger Causality and Application in ML (Dang Nhat Huy, NEU)
April 25: AI-Assisted Detection of Greenwashing in Vietnam’s Banking Sector (Toan + Quyen + Quynh, UEL)
April 5: Minimum Specification Perturbation: Falsification Complexity for Causal Inference (Hoang Dang, Independent Researcher)
March 28: PlaSo: Unsupervised Residual Plug and Play for Image Super-Resolution (Hieu Le, University of Toulouse 1)
March 14: Interpretable Machine Learning for Financial Distress Prediction (Minh Anh Nguyen, Texas Tech)
March 1: When Do Observational Causal Conclusions Survive? Evidence from Patient Access to Medical Records (Hoang Dang, Independent Researcher)
February 7: Tracing the Evolution of Word Embedding Techniques in NLP (Minh Anh Nguyen, Texas Tech)
January 27: The power of firm disclosures in macroeconomic forecasting: A textual analysis approach (Tri Minh Phan, University of Basel)
January 24: Causal Discovery for Video Game Telemetry Data (Hoang Dang, Independent Researcher)
Fall 2025
December 9: The Position Effect (Minh Nguyen, FAU)
October 8: AI Governance in Vietnam (Tran Vu Ha Minh, Humane-AI Asia)
September 22: ESG Weighting Scheme Problem (Minh Nguyen, FAU)
September 18: Learning control variables and instruments for causal analysis in observational data (Martin Huber, University of Fribourg)
September 9: Causality in Finance and Banking 101 (Vinh Dang, British University Vietnam)
August 19: Gender Discrimination in Online Job Ads (Tho Pham, University of York)