Dr. Amir Hajian is Arteria AI’s Vice President of Data Science. He holds a Bachelor of Science in Physics, a Master of Science in String Theory, and a Ph.D. in Astrophysics. His career began at Princeton University as a Research Physicist, then as a Senior Research Associate at the Canadian Institute for Astrophysical Sciences at the University of Toronto. He is a published author, having led and contributed to many scientific articles. As he transitioned to Data Science, he spent nearly four years as a Senior Data Scientist and Director of AI Research at Thomson Reuters and then founded the Canadian branch of applied AI research for Scribd as their Director of Applied Research. Dr. Hajian is one of the many incredible members of the Arteria AI team bringing diverse perspectives to our NLP developments.

As Data Scientists, Dr. Hajian and his team are combining the best components of machine learning and deep learning, statistics, engineering and product development all together to create brand new products that help people be more productive and more successful. Legal text can be challenging to deal with, especially the slow manual processes experienced with contracts. At Arteria, we are training models to automate these processes at high accuracy to speed them up for every user.

Let’s begin at the start of your career - Astrophysics! What drew you to the stars?
In the beginning, I didn’t know I wanted to do astrophysics – I was doing a lot of mathematics and geometry. Then, I realized, what I actually wanted was a way to understand the universe. There were two things I was excited about: quantum mechanics and astrophysics. So, I started learning both, and I ended up getting my master’s in string theory, which is the “mathematical-physics” way of explaining the universe. Then I found a chance to do cosmology, and from day one, I found cosmology amazing because it looks for answers to some fundamental questions about our universe. Questions like, how does the universe work, what is the history of the universe, what are the building blocks of our universe, how old is the universe, what’s the shape of the universe and other questions of that sort – I think that’s a passion that everyone is born with, figuring out what’s going on and understanding the universe around us. That was my motivation, and that is what has been my driving force throughout my life.  

Dr. Hajian in front of the Green Bank Telescope, the largest steerable radio telescope on Earth.

Dr. Hajian teaching an AI-Deep Learning workshop

Now heading into data science, what inspired you to divert to this path?
When I was an astrophysicist at the University of Toronto, one of my friends started working at a start-up and had a problem. He contacted me and said, “we’re working with all of these large data sets, but the signal we’re getting out of this is so noisy that we are close to throwing it all away. Can you take a look and see if you can use the same techniques you use in astrophysics to extract something meaningful out of this noisy data?” I said yes, and after spending 90-100 hours on it, I solved the problem. When I showed them, they were so excited and used this solution! It was a great experience because I solved an interesting problem using similar techniques to what I was doing in astrophysics. I found joy in building something that people would use, knowing it would impact their lives. This became my motivation and my new passion – I started learning more about data science, and I retrained myself to become a data scientist, and then I joined this world.  
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Looking back again now, having founded so many innovations throughout your lifetime, what is a key strategy you’ve taken away from these experiences that all teams should keep in mind when building something from the ground up?
Vision, strategy, and patience. And if someone is going to create something out of nothing, they should know that this is an incredibly hard thing to do –  the success rate is so low when you are creating something brand new, and you’re most probably going to fail. What’s important is not being discouraged by failing and continuing with the same passion you had as a kid learning how to ride a bike. When you fall onto the pavement and scratch up your knees, don’t think twice about getting back on the bike and trying again.

What excites you about the future of AI and NLP capabilities?
What I am excited about is the fast pace of progress in this field, and the rapid adoption of the result of that research in real life. It is exciting to witness that and to be part of that.

Who has been the most influential person in your life, and why?
It is certainly more than one person. And it’s impossible to name them all because I have lived in different countries - I have been in many different organizations, universities, and as a scientist, I have travelled a lot. I would start with my family, and then the people I have learned with: my teachers, many of my colleagues, a lot of my friends - even strangers. Sometimes, just watching someone doing something can teach you an important lesson.  

Dr. Hajian sharing some wisdom on a "Transitioning to Data Science" panel.

If you could know the absolute and total truth to one question, what question would you ask?
I would ask, how can we live in this world in harmony with nature in a sustainable way and innovate our lifestyle along the lines of why we are here? Looking around us, we are destroying a lot of our environment. We have learned a lot, but we haven’t learned how to live in harmony with our environment – so I would want to know the right source of energy, the right way to produce things – all of that.

When your computer is off, and you’re away from your desk, what is your favourite way to spend the time?
I read a lot, and that’s what gives me a lot of joy. I recommend the classics based on what you enjoy, and Tagore, Rumi and Tolstoy for sure. All of Tolstoy’s books are amazing, especially War and Peace.  

What is something that your coworkers might be surprised to know about you?
I have taught courses in AI, computer science and statistics, but I have never taken an official computer science course.  I have learned everything myself through books or videos, and online material. If you want to learn something new, you just need that willpower to find it, read it, and teach yourself!