Isha Chaturvedi: A Driven Data Scientist
Interview by Tammy Lee, Marketing & Communications & Digital Manager, Advance.
Isha Chaturvedi is a data scientist based out of San Francisco. Although she’s always working “behind the scene”, her work is highly visible in our daily lives – from our simple internet searches to medical diagnosis.
Isha realised early in life that mathematics and sciences were her calling and has pursued her dream of a career in STEM. She earned her bachelor’s degree in Environmental Technology and Computer from the Hong Kong University of Science and Technology, during which she undertook an exchange program in Engineering at UNSW where she has fond memories.
Can you tell us what you do and a little about your role.
I am currently a Data Scientist at Ericsson, working heavily in the Machine Learning space. My role involves applying machine learning and deep learning architectures to solve real business problems. My day-to-day job is a lot about reading research papers and implementing the methodologies and algorithms to a business use case, which makes my work very practical and relevant to everyday lives.
What drew you to a career in STEM?
This is a very interesting question. And a trip down memory lane. I loved science and mathematics since my junior school days. In fact, solving math problems was my route to escapism from all my issues. Though I started coding from the eighth grade, I couldn’t understand the application of all the coding I learnt. I started my bachelor’s degree studying an interdisciplinary major in Environmental Science and Technology. It was a very practical and flexible major, which allowed me to explore diverse subject areas, and learn to connect dots between different areas and apply technical skills to real application cases. As part of my bachelor’s degree, I took computer science courses and I simply loved it and it gave me the understandings of its applicability. I further undertook courses with the main focus of Data Science & AI. Machine Learning Coding brings me a lot of peace and is like a meditation session for me. To be able to apply my technical skills to solve real-life problems brings me a lot of joy and satisfaction.
What’s the hardest part of working on machine learning algorithms?
The hardest part for me is to actually implement the algorithm and see its relevance in solving a real-life use case. To be able to see practical implication of an algorithm is challenging and something very important to me.
How has machine learning impacted our everyday life?
Machine Learning is all around us! From getting those quick internet search results to getting recommendations on Amazon, Netflix, or YouTube, it’s all machine learning. The main reason behind the huge success of AI and ML is that it lowers the cost of prediction. We tend to plan ahead our daily activities and we strive to make the outcome of each activity align with our expectations. Our expectations are very much the product of our own predictive capabilities. However, they are subject to bias. Being able to use predictive tools to help us maximise each outcome or, to say it better , adjust our expectations to reality, is of tremendous help in re-adjusting our plans and consequently, run our daily lives.
ML has made our lives more efficient – from having ride-sharing apps like Uber and Lyft, to fraud prevention mechanisms, smart-homes devices, and efficient security surveillance, ML has improved our quality of life. Further, ML is also used in health-care areas, for example in improving medical diagnosis to help doctors. One of my projects has been on detecting breast cancer from ultrasound images.