Quantum Machine Learning for Finance ICCAD Special Session Paper. - Marco Pistoia; Syed Farhan Ahmad; Akshay Ajagekar; Alexander Buts; Shouvanik Chakrabarti; Dylan Herman; Shaohan Hu; Andrew Jena; Pierre Minssen; Pradeep Niroula; Arthur G. Rattew; Yue Sun; et al. (ICCAD, 2021)

Quantum Machine Learning for Finance. - Marco Pistoia; Syed Farhan Ahmad; Akshay Ajagekar; Alexander Buts; Shouvanik Chakrabarti; Dylan Herman; Shaohan Hu; Andrew Jena; Pierre Minssen; Pradeep Niroula; Arthur G. Rattew; Yue Sun; et al. (CoRR, 2021)

Constrained Quantum Optimization for Extractive Summarization on a Trapped-ion Quantum Computer. - Pradeep Niroula; Ruslan Shaydulin; Romina Yalovetzky; Pierre Minssen; Dylan Herman; Shaohan Hu; Marco Pistoia (CoRR, 2022)

Alignment between Initial State and Mixer Improves QAOA Performance for Constrained Portfolio Optimization. - Zichang He; Ruslan Shaydulin; Shouvanik Chakrabarti; Dylan Herman; Changhao Li; Yue Sun; Marco Pistoia (CoRR, 2023)

Evidence of Scaling Advantage for the Quantum Approximate Optimization Algorithm on a Classically Intractable Problem. - Ruslan Shaydulin; Changhao Li; Shouvanik Chakrabarti; Matthew DeCross; Dylan Herman; Niraj Kumar 005; Jeffrey Larson 001; Danylo Lykov; Pierre Minssen; Yue Sun; Yuri Alexeev; Joan M. Dreiling; et al. (CoRR, 2023)

Code from "Evidence of Scaling Advantage for the Quantum Approximate Optimization Algorithm on a Classically Intractable Problem". - Ruslan Shaydulin; Changhao Li; Shouvanik Chakrabarti; Matthew DeCross; Dylan Herman; Niraj Kumar 005; Jeffrey Larson 001; Danylo Lykov; Pierre Minssen; Yue Sun; Yuri Alexeev; Joan M. Dreiling; et al. (Zenodo, 2023)

Quantum Deep Hedging. - El Amine Cherrat; Snehal Raj; Iordanis Kerenidis; Abhishek Shekhar; Ben Wood; Jon Dee; Shouvanik Chakrabarti; Chun-Fu Richard Chen; Dylan Herman; Shaohan Hu; Pierre Minssen; Ruslan Shaydulin; et al. (Quantum, 2023)

Invited: Challenges and Opportunities of Quantum Optimization in Finance. - Zichang He; Shouvanik Chakrabarti; Dylan Herman; Niraj Kumar 005; Changhao Li; Pierre Minssen; Pradeep Niroula; Ruslan Shaydulin; Yue Sun; Shree Hari Sureshbabu; Romina Yalovetzky; Marco Pistoia (DAC, 2024)

Parameter Setting Heuristics Make the Quantum Approximate Optimization Algorithm Suitable for the Early Fault-Tolerant Era. - Zichang He; Ruslan Shaydulin; Dylan Herman; Changhao Li; Rudy Raymond; Shree Hari Sureshbabu; Marco Pistoia (ICCAD, 2024)

Prospects of Privacy Advantage in Quantum Machine Learning. - Jamie Heredge; Niraj Kumar 005; Dylan Herman; Shouvanik Chakrabarti; Romina Yalovetzky; Shree Hari Sureshbabu; Changhao Li; Marco Pistoia (CoRR, 2024)

Generalized Short Path Algorithms: Towards Super-Quadratic Speedup over Markov Chain Search for Combinatorial Optimization. - Shouvanik Chakrabarti; Dylan Herman; Guneykan Ozgul; Shuchen Zhu; Brandon Augustino; Tianyi Hao 006; Zichang He; Ruslan Shaydulin; Marco Pistoia (CoRR, 2024)

Parameter Setting in Quantum Approximate Optimization of Weighted Problems. - Shree Hari Sureshbabu; Dylan Herman; Ruslan Shaydulin; Joao Basso; Shouvanik Chakrabarti; Yue Sun; Marco Pistoia (Quantum, 2024)

On Speedups for Convex Optimization via Quantum Dynamics. - Shouvanik Chakrabarti; Dylan Herman; Jacob Watkins; Enrico Fontana; Brandon Augustino; Junhyung Lyle Kim; Marco Pistoia (CoRR, 2025)

Iterative Interpolation Schedules for Quantum Approximate Optimization Algorithm. - Anuj Apte; Shree Hari Sureshbabu; Ruslan Shaydulin; Sami Boulebnane; Zichang He; Dylan Herman; James Sud; Marco Pistoia (CoRR, 2025)

Provably faster randomized and quantum algorithms for k-means clustering via uniform sampling. - Tyler Chen; Archan Ray; Akshay Seshadri; Dylan Herman; Bao Bach; Pranav Deshpande; Abhishek Som; Niraj Kumar 005; Marco Pistoia (CoRR, 2025)