Page 12 - PTC Catalogue November 2020

PERSONAL BACKGROUND
Mr S has over 200 hours teaching experience and is currently a research assistant at leading American university, MIT, contributing to the latest developments in artificial intelligence.
Dedicated to the computer science field he takes pride in guiding pupils who are interested in engineering. Allowing them to maximise their capacity to excel within exams as well as fulfilling their academic potential beyond their classes.
SKILLS
•Programming: Python, PyTorch, TensorFlow, C++, Bash, AWS etc. •Computer Science: Computer Vision, Machine Learning, Reinforcement Learning, Neural Networks, Graphical Models
•Electrical Engineering: Signal Processing, State Space Control, Robotics, Algorithms, Estimation, Electromagnetics, Arduino, Circuits
•Mathematics: Optimisation, Real & Fourier Analysis, Linear Algebra, Matrix Calculus, Probabilistic Inference
Other: TS/SCI Security Clearance, QT Modeler
AVAILABILITY
Availability upon request
SPECIALISMS
US university entry, electrical engineering, engineering projects, computer science, AI, maths, physics, online remote teaching, DBS cleared
MR SANDERS MIT COMPUTER SCIENCE & ENGINEERING TUTOR
Teaching Assistant at Massachusetts Institute of Technology
Professional Tutor of Engineering and Computer Science
EDUCATION
• Massachusetts Institute of Technology, Cambridge, MA B.S. Electrical Engineering & Computer Science, Mathematical Economics (2020) M.Eng, Artificial Intelligence (2021)
•MA Graduate Coursework: VNAV, Computer Vision, Machine Learning, Prob. Programming & AI, Embodied Intelligence •Undergraduate Coursework: Robotics, Signals & Systems, Inference, Algorithms, Electromagnetics, Circuits
•Grade Point Average: 5.0/5.0
EXPERIENCE
Teaching Assistant
MIT Global Startup Labs |
2020
•Developing lessons and tutorials for MIT's Machine Vision course. Subjects covered include: computer vision and Python machine learning packages, such as PyTorch, TensorFlow, and OpenCV •Collaboratively developing an AWS EC2 Python code base for managing cloud computing resources for our students
Research Assistant
MIT CSAIL, Distributed Robotics Lab |
2019 - Present
•Investigating experience replay augmentation methods for model-free Reinforcement Learning agents
•Developing a Multi-Agent Reinforcement Learning simulation codebase using Python, TensorFlow Agents, and OpenAI
Data Science & Machine Learning Intern
Nasdaq Machine Intelligence Lab | June - August 2020
•Implementing and training Deep Reinforcement Learning agents for portfolio optimisation using TensorFlow
• Collaboratively developing an ensemble-based trading volume prediction model using unsupervised clustering algorithms and Temporal Convolutional Neural Networks
Lidar Imagry Scientist
National Geospatial-Intelligence Agency | Summer 2018, 2019
• Developing a neural network-based building footprint extraction pipeline using PyTorch and AWS
• Organising a machine learning seminar for my career service to facilitate further interest in this field
• Developing and briefing a proposal for a sentiment analysis- based automation tool, which we presented to NGA senior leadership