I'm an AI Researcher who is
Chief Data Scientist and Cofounder at AI Squared.

My primary research interests are explainable artificial intelligence, deep learning, machine learning optimization, and human-machine teaming.

Duties at AI Squared

I am the Chief Technologist and head of research and open source at AI Squared, where I am responsible for leading the development of our company's technology products and oversee our company's Research and Development efforts, including our open source technologies. In this role, I help oversee the development of the AI Squared platform and browser extension, and I contribute directly to our Python and JavaScript software development kits (SDKs).

As head of research and open source, I lead the development of our next-generation technologies, including various research efforts such as UI/UX research, machine learning architecture improvements, and human-machine collaboration. One of our main research projects is the Reduction of Sub-Network Neuroplasticity (RSN2) algorithm, which enables the creation of sparse, lightweight, multitask neural networks. This research has resulted in the BeyondML project, an open-source implementation of our RSN2 methodology that works with both PyTorch and TensorFlow. We contributed BeyondML to the Linux Foundation AI and Data in 2022.

I am also the lead researcher and developer of DLite, a series of chatbot LLMs that are lightweight so that they can be run in resource-constrained environments, even on laptop CPUs. Please check out our Github repo and our Hugging Face page for info on how to train and use these models.

To learn more about our work at AI Squared, visit our company blog. You can also check out the Linux Foundation AI and Data homepage and GitHub pages for the BeyondML project.

Duties at Capitol Technology University

In addition to the work I do at AI Squared, I am also an Adjunct Professor of Computer Science at Capitol Technology University. In this role, I serve as Doctoral Committee Chair for students in PhD in Artificial Intelligence program, assist in the dissertation defense procress as an external examiner, and I have taught CS 150 - Programming in C.

Open Source Projects

Over the course of my career thus far, I have had the privilege of creating and contributing to multiple open-source projects and initiatives. Below are links to a select set of such projects.

Education

I received a Bachelor of Science (BS) in Mathematics in 2017 and a Master of Science (MS) in Business Analytics in 2018, both from the University of Maryland. In 2022, I earned a Doctor of Philosophy (PhD) in Technology with a focus on Explainable Artificial Intelligence from Capitol Technology University. My research focused on improving the accuracy of classification trees through a new method of creating multivariate splits, resulting in the development of the LRCT algorithm. If you're interested, you can watch a recording of my dissertation defense on YouTube or view my dissertation online here. Alternatively, you can download the entire manuscript by clicking the button below.

Selection of Talks and Publications