Dr. Nkongho Ayuketang Arreyndip

-Develop, evaluate, and fine-tune frontier generative AI models to accurately solve highly complex, graduate-level theoretical and mathematical physics problems. - Design adversarial testing frameworks and rigorous benchmark datasets to probe model reasoning, isolating and correcting logical, mathematical, and physical flaws. - Synthesize complex physical constraints and mathematical proofs to optimize LLM training data, improving multi-step reasoning capabilities and objective evaluation metrics.

As a Media Data Analyst at Telus Digital (Remote, Dec 2022–Present), I analyze and process large-scale media datasets to optimize data quality, algorithmic performance, and content delivery. I apply statistical methods to uncover hidden patterns, anomalies, and bottlenecks that improve recommendation models, while collaborating in fast-paced tech workflows to ensure strict data integrity and timely delivery.

As a Marie Skłodowska-Curie Postdoctoral Research Fellow at Ca’ Foscari University of Venice & CMCC (Oct 2023–Sept 2025), I served as Principal Investigator on an EU-funded (€170K+) project. I developed advanced risk and predictive models simulating global economic shocks from coupled weather-geopolitical extremes, processed large climate/geospatial datasets with Python/R, and managed all data governance, milestones, and reporting.

Ph.D. in Physics (Renewable Energy and Climate) from the University of Buea, Cameroon (2014–2019). Thesis: Complete Onshore Wind Farm Project in Cameroon: Modeling, Simulation, and Comparative Analysis, supervised by Prof. Dr. Alain Moise Dikande and Prof. Joseph Ebobenow