Context Scout: Meet the Team — Mohammad Akbari

Here at Context Scout, we’re continuing our “Meet the Team” series with one of the recent additions to our Research team at Context Scout, Mohammad Akbari PhD.

What’s your role on the team?

I am a Data Science researcher in Context Scout and senior research associate at University College London (UCL) working on information retrieval and data mining.

Where are you from? What made you come to London/UK?

I am from Tehran, Iran but lived in Singapore for last 6 years. I relocated to London due to career goals. London includes several well-known educational and research institutes such as UCL and Imperial College. They are closely working with industrial firms to advance technology and research. Apart from that, London is well-known for it’s entrepreneurial opportunities, and this makes it best for researchers.

Why did you choose to join Context Scout?

I am a researcher that craves opportunities to solve complex challenges. Meanwhile I have an entrepreneur mindset. I am someone who cares about solving problems people face in their daily life. Context Scout and UCL permit me to achieve this by bringing intelligence to web search; an online activity each of us perform several times daily.

What’s your favorite part of working at Context Scout?

The entrepreneurial spirit at Context Scout encourages collaboration, diversity, and individuality. You indeed work, innovate, and play which gives the right fit to you and help you easily solve challenges.

What’s the most interesting thing you’ve read lately?

I’m just coming back from the International Conference on Machine Learning (ICML), so my recent readings were mostly on Machine Learning. In my opinion, one of the best readings of ICML is “Delayed Impact of Fair Machine Learning” which focuses on bias in machine learning. The paper demonstrates that even in a one-step feedback model, common fairness criteria in general do not promote improvement over time. In other words, it demonstrates how machine learning models may exhibit discriminatory biases based on sensitive characteristics, such as, gender, race, religion, physical ability, and sexual orientation, or perform less well for historically disadvantaged groups.

What future technology excites you the most?

I envision the future of healthcare technology where smart devices measure, estimate, guide, and influence our lifestyle and wellness, assisting us better understand and control our health. These devices assist us to better fight diseases that out a mystery for us now.

What startup do you admire and why?

Evernote for helping people organizing tasks, notes, ideas; essential tasks everyone may deal with it daily.

—

Want to see what the team is working? Head to contextscout.com to give our Chrome extension a try.