Research topics include:
- Combinatorics – Developed algorithm in Python to determine the canonical position of a given permutation, and permutation at a given canonical position without enumerating all permutations. (Bijection of the natural integers with the sorted permutation set.)
- Prime numbers – Developing theories about location and prediction of prime numbers.
- Machine Learning – Developed systems to analyze and predict stock price fluctuation, social comment toxicity, ML prediction of hash function results, and ML prediction of unpredictable/psuedorandom datasets including lottery draws. Competed in contests hosted by Kaggle and others. Developed algorithms for prediction of customer interactions/software bottlenecks for client firms.
- Developing custom ML models in Python Scikit and Tensorflow, exploring alternative structure/update options.
- AGI – Various aspects being explored.
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Ranking and Unranking Unordered Combinatorial Elements, Simplified.