• Applied advanced machine learning techniques to design and implement deep learning models in PyTorch for a novel classification task involving MemComputing circuits, based on a synthetic dataset that was generated, cleaned and labeled in-house• Assisted in creating a breakthrough method for large prime factorization using MemComputing circuits, achieving superior results compared to the current best solvers in terms of accuracy and efficiency (https://arxiv.org/abs/2309.08198)• Performed rigorous statistical analysis to improve the solution-finding probability of the Monte Carlo search, resulting in a more robust and flexible solver; also enhanced the solver’s functionality by enabling the identification of critical regions in the parameter space

• Simulated the circuit dynamics to predict the parameters for a state-of-the-art superconducting circuit used for creating low-energy computational devices• Designed and examined multiple superconducting circuits by solving second-order differential equations in Mathematica and Python that resulted in a ready-for-production electronic circuit • Analyzed a novel quantum system using Mathematica that led to a peer-reviewed publication; achieved 3x faster computation by utilizing the Python QuSpin library• Built computational models for a variety of physical systems using Python and Mathematica• Collaborated with experimental teams to reinforce and explain the theoretical findings• Organized journal club meetings to facilitate new research findings

• Taught a wide variety of courses ranging from Introductory Mechanics to Quantum Mechanics.• Explained different physics concepts to undergraduate students from diverse backgrounds. Conducted lab meetings and helped students perform classic physics experiments.• Assisted the students in problem solving sessions along with creating novel and thought provoking problem sets.

• Explored the influence of topology on the system’s collective degree of freedom. • Analysed 1D and 2D topological systems, and performed simulations on Mathematica .

• Used the I-Tensors library to investigate various properties of strongly correlated systems.• Performed simulations for non-trivial condensed matter systems and presented the results at MITACS research communication workshop.

• Tasked to investigate phase diagrams for strongly interacting systems by applying state-of-the-art algorithms in C++ and Python.