About

My name is Abi. I am a Computer Scientist working extensively in machine learning to make the software systems smarter. Over the past six years, my focus has been building machine learning models for various applications including recommendation systems, voice-tech, geopositional apps etc.

Prior to that, I also attended Insight in Toronto as a Data Science Fellow and was a Visiting Research Scholar at UCLA under Dr. Judea Pearl where I worked in AutoML, MultiAgent Systems and Emotion Recognition. At school, I majored in mathematics with minors in statistics and computer science with some finance and mangement courses loosely sprinkled in.

I am deeply fascinated by deep tech and its applications in various industries. To that end, I have been lucky enough to be a VC Fellow with Laconia Capital. deepening my expertise in private-equity, fund-raising and due-diligence for AI/ML startups. I am also passionate about communities and helping self-taught engineers get into technical careers. In my free time, you would find me working behind the scenes obsessing over content strategy and analytics at the MLOps Community. I do also occassionally appear as a co-host on some of the podcast episodes - talking about Foundational models with Alex Ratner, Founder and CEO of Snorkel, Managing Machine Learning Projects with Simon Thompson, Head of Data Science, GFT Technologies, HCI for MLOps Infra Companies with Murtuza Shergadwala, Senior Data Scientist, Fidder.ai, What is MLOps with Niklas Kühl, Managing Consultant for Data Science at IBM and many more.

On another note, I am also working on some self-study courses that I wish were there when I was starting out. As someone who has taught python and machine learning at over 40 events for Women Who Code, WiMLDS and PyData conferences, I have often felt that software engineers tend to make simple things un-necessarily hard with unintuitive terminologies. As a self-taught programmer, it took me years to figure the best frameworks to learn anything quickly and build a unique learning style that spoke to my dopamine-hungry brain. Tying technical concepts with fun story-telling and intuitive analogies, I am now slowly trying to package my hard-learnt lessons and learnings into courses that would allow more people to have the power to make cool things to solve real-world problems by breaking down initimidating concepts into simple, easy-to-follow and obvious explanations.

I am best reached via email. I’m always open to interesting conversations and collaboration.

I am, foremost, driven by the goal to create personalized humane-agents that can influence and alter human decision making, but subsconsciously, also the nagging desire to leave the world a slightly better place than I found it. A tad bit geeky and a gadget lover at heart, I am equally fascinated by large-scale engineering application design as well as low level computer hardware engineering including microprocessors, crafting compilers, integrated chip design etc.

Interested in hearing about Data Infrastructure, ML Systems, and new startups/research papers/tools in the MLOps space?¶

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This month's newsletter will be about Building Reliable Data Pipelines.