Research interests: Analysis, optimization, and control of stochastic systems; applications in financial engineering, market microstructure, quantitative and algorithmic trading, and blockchain technology.

Research profiles: Google Scholar / arXiv / SSRN / Semantic Scholar / DBLP

Podcast appearances:

2026

[73]
C. C. Moallemi, D. Robinson, B. Zhu. Uniform-loss automated market making for prediction markets. Working paper. Accepted to AFT 2026. Initial version: July 2026.
[pdf]
[72]
W. Xi, C. C. Moallemi, M. Pai, S. Wang. Volatility in prediction markets: A structural approach. Working paper. Initial version: July 2026.
[pdf] [arXiv]
[71]
M. Ehab, A. El Gadarri, V. F. Farias, A. Jozefiak, C. C. Moallemi. OS-Pruner: Pruning chains-of-thought of reasoning models via optimal stopping. Working paper. Initial version: July 2026.
[arXiv]
[70]
S. Campbell, N. Hey, C. C. Moallemi, M. Nutz. Risk-based auto-deleveraging. Working paper. Accepted to ACM EC 2026. Initial version: March 2026. Revised: July 2026.
[pdf] [arXiv]

2025

[69]
W. Zhang, Y. Li, C. C. Moallemi, T. Peng. Tail-optimized caching for LLM inference. In Advances in Neural Information Processing Systems, pages 164419–164447, 2025.
[arXiv]
[68]
C. C. Moallemi, D. Robinson, D. White. Orbital. Paradigm Research. June 2025.
[link]
[67]
R. Dewey, J. Botyanszki, C. C. Moallemi, A. T. Zheng. Outbidding and outbluffing elite humans: Mastering liar's poker via self-play and reinforcement learning. Working paper. Initial version: November 2025.
[arXiv]
[66]
S. Wang, D. Crapis, C. C. Moallemi. A framework for combined transaction posting and pricing for layer 2 blockchains. In FC 2025: Proceedings of the International Conference on Financial Cryptography and Data Security, Part I, Springer, pages 56–72, 2025.
[doi] [arXiv]
[65]
B. Z. Zhu, D. Liu, X. Wan, G. Liao, C. C. Moallemi, B. Bachu. What drives liquidity on decentralized exchanges? Evidence from the Uniswap protocol. In Financial Cryptography and Data Security. FC 2025 International Workshops, Springer, pages 78–93, 2025.
[doi] [arXiv]
[64]
C. C. Moallemi, M. M. Pai, D. Robinson. Latency advantages in common-value auctions. Working paper. Accepted to FC 2026. Initial version: April 2025. Revised: May 2026.
[pdf] [arXiv]

2024

[63]
B. Z. Zhu, X. Wan, C. C. Moallemi, D. Robinson, B. Bachu. Quantifying the value of revert protection. In FC 2025: Proceedings of the International Conference on Financial Cryptography and Data Security, Part II, Springer, pages 72–88, 2025.
[doi] [arXiv]
[62]
C. C. Moallemi, D. Robinson. pm-AMM: A uniform AMM for prediction markets. Paradigm Research. November 2024.
[link]
[61]
C. C. Moallemi, U. Patange. An analysis of fixed-spread liquidation lending in DeFi. In Financial Cryptography and Data Security. FC 2024 International Workshops, Springer, pages 105–127, 2024.
[doi] [SSRN]
[60]
Y. Zhang, S. Wang, S. Tan, X. Liu, C. C. Moallemi, R. A. Popa. Proof of sampling: A Nash equilibrium-based verification protocol for decentralized systems. Working paper. Initial version: May 2024.
[arXiv]
[59]
C. C. Moallemi, D. Robinson. Loss-versus-fair: Efficiency of Dutch auctions on blockchains. Working paper. Initial version: May 2024. Revised: July 2024.
[pdf] [arXiv]
[58]
B. Bachu, X. Wan, C. C. Moallemi. Quantifying price improvement in order flow auctions. Working paper. Initial version: April 2024. Revised: May 2024.
[pdf] [arXiv]
[57]
G. Angeris, T. Diamandis, C. C. Moallemi. Multidimensional blockchain fees are (essentially) optimal. Working paper. Initial version: February 2024.
[pdf] [arXiv]
[56]
A. Adams, C. C. Moallemi, S. Reynolds, D. Robinson. am-AMM: An auction-managed automated market maker. In FC 2025: Proceedings of the International Conference on Financial Cryptography and Data Security, forthcoming, February 2024.
[pdf] [arXiv]

2023

[55]
R. Dewey, C. C. Moallemi, A. Brown. Free exchange is not free. Wilmott Magazine, 2023(127), September 2023.
[pdf] [doi]
[54]
D. Crapis, C. C. Moallemi, S. Wang. Optimal dynamic fees for blockchain resources. In FC 2024: Proceedings of the International Conference on Financial Cryptography and Data Security, forthcoming, May 2023.
[pdf] [arXiv]
[53]
J. Milionis, C. C. Moallemi, T. Roughgarden. Automated market making and arbitrage profits in the presence of fees. Working paper. Initial version: February 2023. Revised: May 2023.
[pdf] [arXiv]

2022

[52]
J. Milionis, C. C. Moallemi, T. Roughgarden. A Myersonian framework for optimal liquidity provision in automated market makers. In 15th Innovations in Theoretical Computer Science Conference (ITCS 2024), 2024.
[pdf] [doi] [arXiv]
[51]
J. Milionis, C. C. Moallemi, T. Roughgarden. Complexity-approximation trade-offs in exchange mechanisms: AMMs vs. LOBs. In FC 2023: Proceedings of the International Conference on Financial Cryptography and Data Security, pages 326–343, 2023.
[pdf] [doi] [arXiv]
[50]
J. Milionis, C. C. Moallemi, T. Roughgarden, A. L. Zhang. Automated market making and loss-versus-rebalancing. Working paper. Initial version: August 2022. Revised: May 2024.
[pdf] [arXiv]
Preliminary version:
  • J. Milionis, C. C. Moallemi, T. Roughgarden, A. L. Zhang. Quantifying loss in automated market making. In DeFi'22: Proceedings of the 2022 ACM CCS Workshop on Decentralized Finance and Security, pages 71–74, November 2022.
    [pdf] [doi]
[49]
C. C. Moallemi, U. Patange. Hybrid scheduling with mixed-integer programming at Columbia Business School. INFORMS Journal on Applied Analytics, forthcoming, August 2022.
[pdf] [doi] [SSRN]
[48]
V. F. Farias, C. C. Moallemi, T. Peng, A. T. Zheng. Synthetically controlled bandits. Working paper. Initial version: February 2022. Revised: December 2022.
[pdf]
[47]
S. Min, C. C. Moallemi, C. Maglaras. Risk-sensitive optimal execution via a conditional value-at-risk objective. Working paper. Initial version: January 2022.
[pdf] [arXiv] [SSRN]

2021

[46]
C. C. Moallemi, M. Wang. A reinforcement learning approach to optimal execution. Quantitative Finance, 22(6):1051–1069, March 2022.
[pdf] [doi] [SSRN]
[45]
C. Maglaras, C. C. Moallemi, M. Wang. A deep learning approach to estimating fill probabilities in a limit order book. Quantitative Finance, 22(11):1989–2003, October 2022.
[pdf] [doi] [SSRN]

2020

[44]
S. Min, C. C. Moallemi, D. J. Russo. Policy gradient optimization of Thompson sampling policies. Working paper. Initial version: June 2020. Revised: August 2022.
[pdf] [arXiv]

2019

[43]
R. Dewey, C. C. Moallemi. The unsolved mystery of the Medallion Fund's success. Bloomberg Businessweek, November 2019.
[link]
[42]
S. Min, C. Maglaras, C. C. Moallemi. Thompson sampling with information relaxation penalties. Management Science, forthcoming, February 2022.
[pdf] [arXiv] [online supplement]
Preliminary version:
  • S. Min, C. Maglaras, C. C. Moallemi. Thompson sampling with information relaxation penalties. In Advances in Neural Information Processing Systems 32, pages 3549–3558, 2019.
[41]
G. Huberman, J. Leshno, C. C. Moallemi. An economist's perspective on the Bitcoin payment system. In American Economic Association Papers and Proceedings, 109:93–96, May 2019.
[pdf] [doi]

2018

[40]
S. Min, C. Maglaras, C. C. Moallemi. Cross-sectional variation of intraday liquidity, cross-impact, and their effect on portfolio execution. Operations Research, 70(2):830–846, March–April 2022.
[pdf] [doi] [arXiv] [SSRN] [online supplement]

2017

[39]
G. Huberman, J. Leshno, C. C. Moallemi. The economics of the Bitcoin payment system. Vox EU, December 2017.
[link]
[38]
G. Huberman, J. Leshno, C. C. Moallemi. Monopoly without a monopolist: An economic analysis of the Bitcoin payment system. The Review of Economic Studies, 88(6):3011–3040, November 2021.
[pdf] [doi] [SSRN]

2016

[37]
C. C. Moallemi, K. Yuan. A model for queue position valuation in a limit order book. Working paper. Initial version: December 2016. Revised: June 2017.
[pdf] [SSRN]
[36]
C. C. Moallemi, K. Yuan. Portfolio liquidity estimation and optimal execution. Working paper. Initial version: December 2016. Revised: August 2019.
[pdf]

2015

[35]
N. Bhat, V. F. Farias, C. C. Moallemi, D. Sinha. Near optimal A-B testing. Management Science, 66(10):4477–4495, October 2020.
[pdf] [doi]
[34]
C. Maglaras, C. C. Moallemi, H. Zheng. Optimal execution in a limit order book and an associated microstructure market impact model. Working paper. Initial version: May 2015.
[pdf] [SSRN]

2014

[33]
O. Besbes, J. M. Chaneton, C. C. Moallemi. The exploration-exploitation tradeoff in the newsvendor problem. Stochastic Systems, 12(4):319–339, December 2022.
[pdf] [doi] [SSRN] [online supplement]
[32]
P. Glasserman, C. C. Moallemi, K. Yuan. Hidden illiquidity with multiple central counterparties. Operations Research, 64(5):1143–1158, September–October 2016.
[pdf] [doi] [SSRN]
[31]
K. Iyer, R. Johari, C. C. Moallemi. Welfare analysis of dark pools. Working paper. Initial version: October 2014. Revised: June 2018.
[pdf] [SSRN]
[30]
C. Chen, G. Iyengar, C. C. Moallemi. Asset price-based contagion models for systemic risk. Working paper. Initial version: October 2014.
[pdf]
[29]
C. C. Moallemi, M. Sağlam, M. Sotiropoulos. Short-term trading skill: An analysis of investor heterogeneity and execution quality. Journal of Financial Markets, 42:1–28, January 2019.
[pdf] [doi] [SSRN]

2013

[28]
P. Collin-Dufresne, K. Daniel, C. C. Moallemi, M. Sağlam. Strategic asset allocation with predictable returns and transaction costs. Working paper. Initial version: August 2013. Revised: June 2015.
[pdf] [SSRN]

2012

[27]
N. Bhat, V. F. Farias, C. C. Moallemi, Andy T. Zheng. Non-parametric approximate dynamic programming via the kernel method. Stochastic Systems, 13(3):321–397, September 2023.
[pdf] [doi]
Preliminary version:
  • N. Bhat, V. F. Farias, C. C. Moallemi. Non-parametric approximate dynamic programming via the kernel method. In Advances in Neural Information Processing Systems 22, pages 395–403, 2012.
[26]
C. Maglaras, C. C. Moallemi, H. Zheng. Queueing dynamics and state space collapse in fragmented limit order book markets. Operations Research, 69(4):1324–1348, June 2021.
[pdf] [doi] [SSRN]
*Honorable Mention, INFORMS Financial Services Section Student Research Paper Competition, 2012
[25]
C. C. Moallemi, M. Sağlam. Dynamic portfolio choice with linear rebalancing rules. Journal of Financial and Quantitative Analysis, 52(3):1247–1278, June 2017.
[pdf] [doi] [SSRN]

2011

[24]
M. Broadie, Y. Du, C. C. Moallemi. Risk estimation via regression. Operations Research, 63(5):1077–1097, September–October 2015.
[pdf] [doi] [online supplement]
[23]
V. V. Desai, V. F. Farias, C. C. Moallemi. Bounds for Markov decision processes. Chapter in Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (F. L. Lewis, D. Liu, eds.), IEEE Press, pages 452–473, December 2012.
[pdf]
[22]
M. Broadie, Y. Du, C. C. Moallemi. Risk estimation via weighted regression. In Proceedings of the 2011 Winter Simulation Conference, pages 3854–3865, December 2011.
[pdf] [doi]
[21]
C. Chen, G. Iyengar, C. C. Moallemi. An axiomatic approach to systemic risk. Management Science, 56(6):1373–1388, June 2013.
[pdf] [doi]
*Honorable Mention, INFORMS George Nicholson Student Paper Competition, 2011

2010

[20]
V. V. Desai, V. F. Farias, C. C. Moallemi. Pathwise optimization for optimal stopping problems. Management Science, 58(12):2292–2308, December 2012.
[pdf] [doi] [online supplement]
*Best Simulation Publication Award, INFORMS Simulation Society, 2014
[19]
M. Broadie, Y. Du, C. C. Moallemi. Efficient risk estimation via nested sequential simulation. Management Science, 57(6):1172–1194, June 2011.
[pdf] [doi]
[18]
K. Iyer, R. Johari, C. C. Moallemi. Information aggregation and allocative efficiency in smooth markets. Management Science, 60(10):2509–2524, July 2014.
[pdf] [doi] [SSRN]
Preliminary version:
  • K. Iyer, R. Johari, C. C. Moallemi. Information aggregation in smooth markets. In EC '10: Proceedings of the 11th ACM Conference on Electronic Commerce, pages 199–206, June 2010.
    [doi]

2009

[17]
C. C. Moallemi, M. Sağlam. The cost of latency in high-frequency trading. Operations Research, 61(5):1070–1086, September–October 2013.
[pdf] [doi] [SSRN]
*1st Place, INFORMS Financial Services Section Student Research Paper Competition, 2011
Selected for publication in the Operations Research Forum
[16]
C. C. Moallemi, D. Shah. On the flow-level dynamics of a packet-switched network. Working paper. Initial version: November 2009. Revised: October 2012.
[pdf]
Preliminary version:
  • C. C. Moallemi, D. Shah. On the flow-level dynamics of a packet-switched network. In SIGMETRICS '10: Proceedings of the ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, pages 83–94, June 2010.
    [doi]
[15]
V. V. Desai, V. F. Farias, C. C. Moallemi. Approximate dynamic programming via a smoothed linear program. Operations Research, 60(3):655-674, May–June 2012.
[pdf] [doi] [arXiv]
*1st Place, INFORMS Junior Faculty Paper Competition, 2011
Preliminary version:
  • V. V. Desai, V. F. Farias, C. C. Moallemi. A smoothed approximate linear program. In Advances in Neural Information Processing Systems 22, pages 459–467, 2009.

2008

[14]
C. C. Moallemi, B. Park, B. Van Roy. Strategic execution in the presence of an uninformed arbitrageur. Journal of Financial Markets, 15(4):361–391, January 2012.
[pdf] [doi] [arXiv] [SSRN]

2007

[13]
C. C. Moallemi. A message-passing paradigm for optimization. Ph.D. thesis, Stanford University, September 2007.
[pdf]
[12]
V. F. Farias, C. C. Moallemi, B. Van Roy, T. Weissman. Universal reinforcement learning. IEEE Transactions on Information Theory, 56(5):2441–2454, May 2010.
[pdf] [doi] [arXiv] [SSRN]
Preliminary version:
  • V. F. Farias, C. C. Moallemi, B. Van Roy, T. Weissman. A universal scheme for learning. In Proceedings of the IEEE International Symposium on Information Theory, pages 1158–1162, Adelaide, Australia, September 2005.
    [doi]
[11]
C. C. Moallemi, B. Van Roy. Resource allocation via message passing. INFORMS Journal of Computing, 23(2):205–219, Spring 2011.
[pdf] [doi] [online supplement]
[10]
C. C. Moallemi, B. Van Roy. Convergence of min-sum message passing for convex optimization. IEEE Transactions on Information Theory, 56(4):2041–2050, April 2010.
[pdf] [doi] [arXiv] [SSRN]
Preliminary version:
  • C. C. Moallemi, B. Van Roy. Convergence of the min-sum algorithm for convex optimization. In Proceedings of the 45th Allerton Conference on Communication, Control and Computing, pages 840–847, Monticello, IL, September 2007.

2006

[9]
C. C. Moallemi, B. Van Roy. Convergence of min-sum message passing for quadratic optimization. IEEE Transactions on Information Theory, 55(5):2413–2423, May 2009.
[pdf] [doi] [arXiv]
[8]
C. C. Moallemi, S. Kumar, B. Van Roy. Approximate and data-driven dynamic programming for queueing networks. Working paper. Initial version: December 2006. Revised: January 2013.
[pdf]

2005

[7]
V. F. Farias, C. C. Moallemi, B. Prabhakar. Load balancing with migration penalties. In Proceedings of the IEEE International Symposium on Information Theory, pages 558–562, Adelaide, Australia, September 2005.
[pdf] [doi]
[6]
C. C. Moallemi, B. Van Roy. Consensus propagation. IEEE Transactions on Information Theory, 52(11):4753–4766, November 2006.
[pdf] [doi] [arXiv]
Preliminary version:
  • C. C. Moallemi, B. Van Roy. Consensus propagation. In Advances in Neural Information Processing Systems 18, MIT Press, pages 899–906, 2006.

2003

[5]
J. M. Johnson, K. Mason, C. C. Moallemi, H. Xi, S. Somaroo, E. Huang. Protein family annotation in a multiple alignment viewer. Bioinformatics, 19(4):544–545, 2003.
[doi]
[4]
C. C. Moallemi, B. Van Roy. Distributed optimization in adaptive networks. In Advances in Neural Information Processing Systems 16, MIT Press, pages 887–894, 2004.
[pdf] [appendix]
Preliminary version:
  • C. C. Moallemi, B. Van Roy. Decentralized protocols for optimization of sensor networks. In Proceedings of the 42nd Allerton Conference on Communication, Control and Computing, Monticello, IL, September 2003.
[3]
K. Mason, N. M. Patel, A. Ledell, C. C. Moallemi, E. A. Wintner. Mapping protein pockets through their potential small-molecule binding volumes: QSCD applied to biological protein structures. Journal of Computer-Aided Molecular Design, 18(1):55–70, 2004.
[doi]

2000

[2]
E. A. Wintner, C. C. Moallemi. Quantized Surface Complementarity Diversity (QSCD): A model based on small molecule-target complementarity. Journal of Medicinal Chemistry, 43(10):1993–2006, 2000.
[doi]

1991

[1]
C. C. Moallemi. Neural networks in the computer analysis of voided urine cells for bladder cancer. IEEE Expert, 6(6):8–12, December 1991.
[doi]
Copyright 2003–2026 Ciamac C. Moallemi
Last Modified: 2026/07/21 01:48pm