Now
- Building ML Infra @stealth
- Working on a mentorship project integrating Nvidia GPU compability into TensorFlow Quantum
Where I've worked
Untether AI - Compute Kernel Engineer Intern
- Developed 3 custom kernels in C++ specialized for rapid neural network inference on the UntetherAI chip architecture.
Institute for Quantum Computing - Research Intern
- Researched a method to effectively realize Bose Hubbard Hamiltonian dynamics through Rydberg atom arrays.
- Built infrastructure to run 100+ theoretical simulations under various experimental conditions and constraints.
- Developed a python package for efficiently calculating sparse matrix exponentials using the Krylov Method.
Zapata Computing - Quantum AI Intern
- Researched more efficient training methods for quantum generative models.
- Developed Orquestra codebase to enable effortless development of QGANs (quantum generative adversarial networks).
What I've done
April 2022 - Authored article on quantum graph neural networks [article]
- Wrote a deep dive into classical graph neural networks, graph convolutions & attention-based graph learning, and QML applied to high energy physics [article]
Feb 2022 - Top 5 QHack 2022 Project [github]
- Improved a hybrid quantum graph neural network that was used to solve the particle trajectory reconstruction problem [link]
Dec 2021 - Authored closing chapter in the Qiskit QML course [link] [blog]
- As part of the Qiskit Advocate Mentorship Program, authored the chapter on QGANs for the newly released quantum machine learning course by IBM's Qiskit team [link]
- Under the guidance of a research scientist from AWS Braket, built a hybrid quantum-classical version of the Wasserstein generative adversarial network. [link]
- Evaluated learnability of conditional QGANs for sequential data prediction [link]
- Investigated heuristics for optimal training of QGANs [link]
Feb 2021 - Quantum portfolio optimization project with QHack 2021 [link]
- Used quantum generative adversarial networks for portfolio optimisation
- We built an exploratory project applying qGANs and VQE to solve the mean-variance portfolio problem. This placed our team in the 95th percentile of participants in the QHack quantum machine learning hackathon winning over $4000 in AWS credits.
Apr 2021 - Authored an overview of quantum generative adversarial networks [link]
- Explained QGANs for quantum computing enthusiasts.
- Derived the cost function and other mathematical properties stated in the original paper
Feb 2021 - Generalized QAOA to solve the Max-Cut problem [link]
- Built a general quantum approximate optimization algorithm for solving weighted cases of the Max-Cut problem
Mar 2021 - Developed an AI SMS-based text engine in a project partnered with UN Women [link]
- An alternative search engine that we’ve developed & trialed, allowing rural South Africans with a mobile phone to be able to send internet search queries & receive back summarized results all through SMS
- Placed top 3 in challenge out of 150+ teams — project built as part of a TKS challenge w/ United Nations.
Dec 2020 - Challenge project for Instacart [link]
- Addressed customer experience holdbacks by providing an easy-to-implement solution filling data gaps in the Instacart to retailer to CGP pipeline.
- Won first place in consulting challenge out of 30+ teams.