Qian, S. “Multi-Agent Deep Reinforcement Learning and GAN-Based Market Simulation for Derivatives Pricing and Dynamic Hedging” (February 2023). Master’s Thesis, Massachusetts Institute of Technology. https://hdl.handle.net/1721.1/150206

Chen, Yinan and Song, Yiwen and Qian, Samson and Fleiss, Alexander. "Applying Machine Learning to SEC 13F Investment Manager Filings for Portfolio Construction and Rebalancing" (February 2023). SSRN Preprint. http://doi.org/10.2139/ssrn.4352145

Pandian, K., Pfeiffer, D., and Qian, S. (January 2023), "Decentralized Finance", Baker, H.K., Benedetti, H., Nikbakht, E. and Smith, S.S. (Ed.) The Emerald Handbook on Cryptoassets: Investment Opportunities and Challenges, Emerald Publishing Limited, Bingley, pp. 141-156. https://doi.org/10.1108/978-1-80455-320-620221010

Pazzani, M., Soltani, S., Kaufman, R., Qian, S., and Hsiao, A. “Expert-Informed, User-Centric Explanations for Machine Learning”. Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, no. 11, June 2022, 12280-12286, https://doi.org/10.1609/aaai.v36i11.21491

Qian, S. “Generating Explanations for Chest Medical Scan Pneumonia Predictions” (June 2021). Columbia University Academic Commons. https://doi.org/10.7916/d8-t9np-xk59

Fleiss, A., Qian, S., “A Statistical Analysis of The Challenger Disaster” (March 2021). Rebellion Research 2021, SSRN Aerospace Engineering Journal, http://doi.org/10.2139/ssrn.3936047

Mackey T., Miyachi K., Fung D., Qian S., Short J. “Combating Health Care Fraud and Abuse: Conceptualization and Prototyping Study of a Blockchain Antifraud Framework” (September 2020). Journal of Medical Internet Research, 22(9): e18623, http://doi.org/10.2196/18623