krishna allani

I am a machine learning engineer by training. At the core, I am a problem solver. Till now I worked at a research lab. Now, I want to come out of research and use my technical and decision-making capabilities to build products that are customer-centric.

I would say that one of my strongest skills is to understand problem statements, analyze it, and identify the root cause, and built a solution from scratch to solve the problem.

My work mostly focused on using machine learning and deep learning techniques to make mobile robots smarter. My team and I explored techniques like convolution neural nets and deep neural nets to improve the functionality of mobile robots.

We explored how we can use machine learning algorithms to identify fraud and spam with the utmost accuracy.

Coming from a middle-class family in India, I personally faced problems with financial institutions numerous times. We do have the right technology to serve customers in a better way.

I personally think with the help of machine learning and artificial intelligence financial institutions can serve their customers faster, cheaper, and in a better way.

I want to be present at the intersection of machine learning and financial technology.



Simplefin is an ecosystem of apps, services and APIs that will create individualised experiences based on your financial history and longterm goals.Node.js, Firebase, GraphQL, Flutter, Figma, Dialogflow, Twilio


Artificial Intelligence
Machine Learning
Statistical Analysis


  • HP - Machine Learning Research Engineer
    October 2016 - November 2018

    I worked in a research lab as a machine learning research engineer. My team and I explored techniques like deep neural nets and convolution neural nets to improve the functionality of mobile robots.

    We use data from multiple sources like cameras, LIDAR's, and other sensors that help mobile robots to navigate better in an indoor environment.

    Work environment:
    Linux, C++, and Python, various machine learning libraries.