Rishi Kumar

Summary

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.

Blueskytec Ltd.

Bath, United Kingdom

2021.09 - 2021.12

Developing distributed simulation software for scalable simulation of AI-based security mechanisms in IoT-enabled Critical National Infrastructure.
Working with subject matter experts to integrate security and AI solutions into the digital twin system.
Provisioning and supporting cloud-native infrastructure components (e.g., Docker, Kubernetes).
Developing software simulations of BSTs hardware components, and systems for simulating the network traffic generated by end devices.
Using existing technologies such as containerization on a virtual network to deploy the simulation at scale, simulating large-scale deployments of BSTs technology.
Developing the overarching software systems for specifying, deploying, controlling, and interrogating the digital twin system.
Integrating Artificial Intelligence (AI)-enabled security threat detection and mitigation tools developed in another workstream of the project, enabling the simulation and validation of the technology in a range of scenarios including large-scale cyber attacks.

Team leadership, extremely organized, self-motivated, and strong verbal communication
Proficiency in Matlab, Python, Microsoft Excel, C, VS code, Linux, SQL, Git, Github, R, Docker, Kubernetes, Qt, Django, Flask, PHP, NoSQL, Redis
Expertise with HTML, CSS, Javascript/Typescript, React, networking protocols like TCP/IP, HTTP Competency in cloud computing services, namely AWS and GCP

In-depth understanding of front-end frameworks such as Angular, jQuery, Bootstrap
Mastery in stochastic calculus, Monte Carlo simulation, machine learning, time-series analysis, pattern recognition, option pricing theory, finite difference method, computational fluid dynamics, asymptotic and numerical analysis, data science, probability and statistics, mathematical modelling, scientific computing, numerical simulation, and academic research
Strong Computer Science fundamentals (data structures and algorithms, system design, API design, architecture, object-oriented design, and complexity analysis) Significant experience with high-performance computing, distributed systems, CUDA programming, and deep learning frameworks: TensorFlow, PyTorch, and MXNet Understanding of Software Development Life Cycle (SDLC) and knowledge of full life-cycle software engineering practices including coding standards, testing, source control management, and operations

Blueskytec Ltd.

2021.09 - 2021.12