Inside Ople – Srikanth Munjuluri
In order to achieve a dream, people make decisions that seem unreasonable at the moment. Our Research Engineer, Srikanth Munjuluri, made such irrational decision a few years ago. He left his Ph.D. program and came to the U.S. to get a Master’s degree in Computer Science because he wanted to dive deeper into the world of data science.
Tell us a little bit about yourself.
I studied Electronics and Communications Engineering and worked in telecommunications before shifting my career. I worked on big data technologies, like Hadoop, to enhance the performance of wireless protocols on 5G networks. When I was working on statistical signal processing, I was using estimation and detection peering. One day, all of a sudden, I realized that I was doing machine learning and how I can combine my skills in big data to become a great data scientist.
Can you be more specific?
Yes. I think there are three core skills that a data scientist should have: programming skills, math and statistical skills, and big data skills. As an engineer, I have worked as a software engineer and taught languages like Java and R to students. I have also studied math and statistics extensively and utilized them working on statistical signal processing. Finally, I have handled big data to manage networks.
So, how are you using your skills right now at Ople?
In one sentence, I am translating data science magic into code. When our data scientists come up with new ways to improve Ople’s AI to the next level, it is my job to make sure that new improvements will work, and more importantly, scale to handle big data. Our platform is a very complicated system, so when we find new cool features to add, I have to implement the features and test them out very extensively to confirm each one works, and the system does not break with new additions.
That sounds very difficult. What are some challenges that you face every day?
The biggest challenge is that we don’t know what’s going to work and what’s not going to work. We are pioneering the field of data science, so new challenges pop up here and there. But we cannot find any support, and we are on our own. That’s why I used the word “very extensively” when I was talking about testing the system. There are no references for possible bugs or compatible issues so it’s up to all of us to push the software to its limit in every way.
Do you have a memorable challenge or a mistake you have made that you want to go back and fix?
I do, in fact. One of the reasons why I left my doctoral program to study computer science is to gain more hands-on experience rather than do pure research. But still, I have spent too many years studying when I could have been gaining a real-life experience. I guess it took me longer to figure out what I want to do and what I am good at. So if I could go back and fix, I would love to gain a variety of experience as fast as I can and figure out what I really want to do early on.
What do you like to do for fun?
I like many things. Mentally, I like playing chess. In fact, I was an international chess master before. Physically, I like taking long hikes because it helps me set my mind and mood right. I also enjoy politics, studying different cultures, and news around the globe. The latest hobby I picked up is cooking. Unfortunately, I wasn’t aware that when you cook, you also have to eat. =)
I also have a private project that I am working on.
That sounds interesting. What is it?
I am currently using machine learning to see if I can discover scientific foundations on astrology and numerology.
If you find any evidence, you will become famous!
Yes, that is the plan.