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Accomplished educator with extensive expertise in statistical reasoning, data modelling techniques, and regression analysis proficiency. Demonstrates strong leadership in curriculum planning and departmental planning, with a proven track record in external funding sourcing. Adept at guiding theses, developing curricula, and employing creative thinking to enhance student performance evaluation. Committed to professional ethics and educational leadership, aiming to advance the field of mathematical statistics through innovative research and inquiry-based learning. In addition, teaching mathematics for all curricula and levels with great professionalism and efficiency, taking into account the skills of the twenty-first century.

January 2022 - Present
Software Engineer and AI / ML Engineer Interview Preparation

  https://leetcode.com/rnotappl/: Solved approximately 2800 problems on Leetcode.
  https://www.kaggle.com/rishikumar1987: ML projects involving supervised and unsupervised learning, deep learning, natural language processing, computer vision.
  https://github.com/rnotappl8: System Design, Design Patterns, HTML, CSS, Javascript/Typescript, React, Django, Flask, Python, PHP.

October 2016 - January 2021
PhD in applied mathematics and mathematical physics
Imperial College London, London, UK

  Investigated analytically and computationally the linear and nonlinear stability of various shear flows and applied effectively a mixture of analytical, numerical and machine learning techniques to solve challenging problems in fluid dynamics/aerodynamics. The project aimed to develop, implement and exploit machine intelligence paradigms to enable a new approach to wall-turbulence control.
  Performed asymptotic analysis and carried out sophisticated numerical computations through various programming languages such as MATLAB, Python, and C++.

September 2012 - July 2016
Master of Mathematics (M.Math (Honours))
Applied mathematics and mathematical physics, Probability and statistics, 1st class, University of Manchester, Manchester, UK

  Cumulative average: 88.28%, and top 1% of the class.
  2012-2016 (Marks at the end of year Examinations): 1st Year – 92.4%, 2nd Year – 91.6%, 3rd Year – 91.1%, 4th Year – 83.75%.
  Subjects studied include: Probability 1; Introduction to Statistics; Sets, Numbers and Functions A; Linear Algebra A; Mathematical Workshop; Calculus and Vectors A; Calculus and Applications A; Calculus of Several Variables; Fluid Mechanics; Partial Differential equations and Vector Calculus A; Probability and Statistics; Metric Spaces; Introduction to Geometry; Real and Complex Analysis; Classical Mechanics; Asymptotic Expansions and Perturbation Methods; Riemannian Geometry; Stability Theory; Green Functions; Integral Equations and the Calculus of Variations; Elasticity; Wave Motion; Viscous Fluid Flow; Brownian Motion; Intro to Number Theory; Continuum Mechanics; Stochastic Calculus; Matrix Analysis; Mathematical Modelling in Finance.
  I worked on an industrially funded mathematical modelling project during the summer between years 3 and 4.
  I worked on fourth-year projects 'Introduction to Geophysical flows' and 'Flame balls in mixing layers'.
  I have worked on numerical Matlab projects (awarded 87%) in the 1st Year. I have used R-software to tackle a project (awarded 94%) in statistics, to analyse practical data using standard methods.


Results-driven professional with a strong background in data analysis, machine learning, and statistical modeling. Skilled at performing under high-pressure, high-volume environments and excelling in multidisciplinary team settings. Brings expertise in advanced analytical thinking, project management, and strategic planning, with a focus on delivering outcome-oriented results. Proficient in the use of BI tools and SQL databases to support data interpretation and trend analysis. Committed to ethical decision-making and regulatory compliance while fostering process improvement and innovation. Career aspirations center on applying quantitative research methodologies to advance business intelligence solutions.

  Dynamic energy market professional with extensive expertise in financial and physical energy markets. Deep understanding of advanced mathematical and analytical tools applicable to origination, structured products, risk management, and portfolio analytics. Strong background in macroeconomics and the fundamentals of Natural Gas, Power, Environmental Products, Crude and NGLs across North American and global markets, complemented by a robust track record in analyzing market data, numerical models, and forecasts. Committed to leveraging analytical insights to drive strategic decision-making and optimize market opportunities.  

Joe Bates

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Vattenfall Internship

Tutoring

Volunteering

Education

GCSEs -

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Bachelor of Science - Mathematics

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Bachelor of Science - Mathematics

Vattenfall Internship

Volunteering

Tutoring

A-Levels -

GCSEs -

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