Ashwin Manoharan

Background

About Ashwin Manoharan

I love problem solving. Ever since I was in high school I excelled in math and physics class because each problem was like solving a puzzle to me. I looked forward to those tests because, they presented a new problem for me to tackle with the knowledge I had about the topic in Algebra or Linear Momentum and Collisions. That's how I knew I did not want to be a doctor but become an engineer. And so I pursued Bachelor's in Technology in Automation Engineering Technology at McMaster University. This degree allowed me to explore various fields of engineering in my undergraduate career, namely electricity and electronics, mathematics, PLC programming, organic chemistry and computer programming. 🤖 For our capstone project, my team and I decided to create a Bee Pollination Robot to tackle the decline in bee population and its impact on our ecology. I took the initiative to work on the software side of the robot - creating the database, the programming for the robot, and creating the web application for the user. The outcome of this project, resulted in a robot that successfully identified plants, pollinated them, collected necessary data and displayed them in a neat dashboard for the user. This project allowed me to extrapolate the data that was collected first hand by the robot and it gave me a small taste of Data Science. ‍Once I graduated, I worked at Brock Solutions as an On-Site Support Engineer at Pearson International Airport (Client), where a new baggage conveyor system was installed, and I was responsible to maintain the health of the system as well as assist the client in smoothly migrating over to the new system. I also created ad-hoc solutions as well as fostered and sustained a great relationship between the client and Brock Solutions. After a year, I became a Controls Engineer and moved on to working on a new conveyor system for Kansas City International Airport where I worked alongside other Controls Engineers, Software Engineers, HMI Engineers and Electrical Panel Engineers. My passion for Data Science was still present during full time employment. So to learn more, I pursued courses to learn more statistical concepts. One such course was provided by MIT in Applied Data Science, where I used Python to learn ANN, CNN, Classification, Decision Trees and Neural Networks using libraries such as Pandas, Matplotlib, and Scikitlearn. Now I am taking that interest further to tackle intricate business problems as an MSc Business Analytics Candidate at the Ivey Business School.