Stefan Talpa

About Stefan

My name is Stefan Talpa, I am a Computer Science and Applied Mathematics student at Georgia Institute of Technology. I have previously worked for a European logistics company as a quantitative researcher where I was responsible for optimizing company performance. 

As I came to college I got passionate about theoretical computer science and quantum computing, so my most recent experience is related to applying quantum algorithms for optimizations problems. I have also done research on a new machine learning technique – competitive gradient descent, which can be used to solve 2 player games like cyber physical attacks and pairs trading. 

Now, I am looking to apply my research knowledge to the industry and hope to contribute to meaningful quantum projects


  • Deep Learning
  • Machine learning
  • Numerical Analysis
  • NumPy
  • Pandas
  • Probability & Statistics
  • python
  • pytorch
  • Quantum Computing
  • Research
  • Stochastic Processes

Work Experience

May 2022 - August 2022
Quantum Machine Learning Intern
Imperial College London
◦ Improved on current medical image processing techniques, using Quantum-Classical Transfer Learning. Used a 10,000 image sample for training and benchmarking. ◦ Implemented Pennylane and Qiskit for more optimal computation of quantum gradients and compatibility with Pytorch. ◦ Developed a model that recognises COVID-19 thought CT scans with 96% accuracy.
May 2022 - August 2022
Software Research Intern
Software/Hardware Co-Design for Intelligence and Efficiency Lab
◦ Implemented Pytorch version of Complex-Valued Neural Network (CVNN) and tested it on MNIST FFT data ◦ Generalized the toy ConvNet architecture to the ResNet architecture ◦ Performed unstructured pruning over ResNet version to achieve comparable performance
June 2021 - January 2023
Quantitative Researcher
Inter Business Partner
◦ Enhanced performance of the company through developing a quantitative model to identify signals of the customs market, automizing the declaration-creating process, and analyzing large company datasets. ◦ Statistically analyzed world supply chain data to identify countries to work with, increasing client flow by 25% ◦ Implemented an algorithm to reduce the declaration-creating process by almost 50%, doubling annual profit.
August 2020 - Present
Quantum Computing Researcher
Georgia Institute of Technology
◦ Developed optimization software using Qiskit and Game API, to enhance quantum circuits from quantum assembly files ◦ Amplified neural network accuracy through reduction of circuit noise on abstract architectures using LSTM to select optimization steps. ◦ Assisted in the invention of a more efficient noise estimation function for circuits, reducing the error by 60%

Education & Training

Computer Science & Applied Mathematics
Georgia Institute of Technology
BS/MS in Computer Science & Mathematics; Major GPA: 4.0 Concentrations: Theory, Modeling & Simulation, Applied Mathematics Courses: Numerical Analysis, Probability Theory, Stochastic Processes, Quantum Information/Quantum Computing, Math Statistics, Data Structures and Algorithms, Applied Combinatorics, Computational Problem Solving
United States of America