Divanisha Patel was working for a bank when the possibilities AI holds for positive change caught her imagination.
Divanisha decided to make the jump from finance to AI. Now an InstaDeep research engineer based in South Africa, she drives projects ranging from logistics to energy optimisation using reinforcement learning (RL) techniques. She’s balancing her work with a part-time PhD in AI, where Divansha’s RL focus helps drive her research.
What inspired you to work in AI?
I used to work in finance. I always enjoyed maths, statistics and coding. At that time (around 2019), I started reading a lot about AI and its potential. I was excited by how AI could be used to enhance people’s capabilities, improve productivity, and provide positive social impact in the areas of healthcare, education, climate change and agriculture, to name a few. I love that AI research has synergies with research into the human mind and intelligence. Working in AI, you’re not restricted to finance, but can learn about and build applications for a variety of fields. For example, I’ve worked on logistics and energy applications in my time at InstaDeep. We are also often exposed to how it’s being applied in biology. So that is definitely stimulating, because you’re constantly learning about different fields and applications.
What led you to where you are today?
I worked in a bank as a quantitative analyst for five years before joining InstaDeep as an AI research engineer. About two years prior to joining InstaDeep, I started a part-time PhD in reinforcement learning (RL). Arnu Pretorius, a research scientist at InstaDeep, was presenting to my university’s lab about how InstaDeep was using multi-agent RL for train scheduling. There was some overlap in the techniques the InstaDeep team was using to solve this problem and the ones I was using in my own research. I decided to reach out by email to ask a few questions and to ask for some advice. That introduction ended up opening the door to more conversations between me and other employees at InstaDeep. A couple of months after that, there was an opportunity to join InstaDeep which I took up. I made the transition from banking to applied AI engineering and it was the best decision.
What advice would you give to women just beginning their journey in the field?
I would encourage women to not hesitate to engage with people and organisations that interest them, regardless of how much they feel they know at any point in time. My being at InstaDeep right now is a direct result of me asking a question out of pure interest.
What has been very important in my journey is learning to have a growth mindset. This is the idea that your abilities are not fixed, but that they can be improved and developed with time and effort. Sometimes, you can be hard on yourself when something doesn’t click fast enough, or you encounter some sort of failure or rejection. But, these should actually be used as learning and growth experiences and not as some final verdict on your abilities.
Could you be the next Divanisha? If you’re interested in working on exciting AI projects, apply to join our team at www.instadeep.com/careers
