About Me
An avid coder and an enthusiastic entrepreneur looking for an interesting project in the domain of machine learning, data analytics and software development. I have worked in a variegated assortment of projects in the areas spanning from deep learning, quantitative portfolio allocation, data science, software design to antenna design with good performance in all of them. I am studying Communication systems in EPFL specializing in Data Analytics and minoring in Financial Engineering. I spend my free time diving deeper into Machine Learning. I believe that to be successful in life, one needs to be obsessive with their dreams and keep working towards them.
Contact Details
Keshav Singh
https://keshavsingh.ch
Education
Ecole Polytechnique Federale de Lausanne
Majoring in Communication System • Aug 2020
Specializing in Data Analytics and Minor in Financial Engineering
Courses completed at EPFL (Grades in bracket): Database Systems (5.75), Distributed Information Systems(5.75), Deep Learning(5.5), Artificial Neural Networks(5.25), Machine Learning(5), Applied Data Analysis(5), Intelligent Agents(5.5), Network Tour of Data Science(5.75), Data Visualization(5.25), Information Security and Privacy(5.5), Distributed Algorithms(5.25), Advanced Algorithms (4.75), TCP/IP(4.75). Courses enrolled in next semester: Introduction to Finance, Econometrics, Computational Finance, Financial Big data and semester project on Machine Learning knowledge distillation and Encrypted Machine Learning.
City University of Hong Kong
Majoring in Electronics and Communication Engineering • Aug 2017
Completed Maximum possible credits, 144 instead of minimum 120 for a bachelors’ cycle and graduated First Class Honours with 4.01 CGPA / 4.3. Awarded Outstanding Student awards and others.
Work
Siemens Healthineers
Summer Research Intern• Sept 2019
Hyper parameter optimization of deep learning machine learning models aimed at better medical diagnosis using MRI images as datasets.
CIGP
Quantitative Analyst Intern• Feb 2019
At CIGP, I worked with the Asset Management team with the following goals (goals are numbered, extra tasks in bullets)