Ciamac C. Moallemi: Research and Publications

My research is focused on the optimal control of large-scale stochastic systems, with an emphasis on applications in financial engineering.

Short research briefs that feature some of my work are available here:

2011

[23]

M. Broadie, Y. Du, C. C. Moallemi. Risk estimation via regression. Working paper. Initial version: November 2011. Revised: December 2011.
[pdf] [online supplement]

[22]

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, November 2011.
[pdf]

[21]

C. Chen, G. Iyengar, C. C. Moallemi. An axiomatic approach to systemic risk. Working paper. Initial version: August 2011. Revised: December 2011.
[pdf]

*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. To appear in Management Science. Initial version: August 2010. Revised: November 2011.
[pdf] [online supplement]

[19]

M. Broadie, Y. Du, C. C. Moallemi. Efficient risk estimation via nested sequential simulation. Management Science, 57(6):1172–1194, June 2011.
[pdf]

[18]

K. Iyer, R. Johari, C. C. Moallemi. Information aggregation and allocative efficiency in smooth markets. Working paper. Initial version: January 2010. Revised: August 2011.
[pdf]

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, pp. 199–206, June 2010.
[doi]

2009

[17]

C. C. Moallemi, M. Sağlam. The cost of latency. Working paper. Initial version: November 2009. Revised: July 2011.
[pdf]

*1st Place, INFORMS Financial Services Section Best Student Research Paper Competition, 2011

[16]

C. C. Moallemi, D. Shah. On the flow-level dynamics of a packet-switched network. Working paper. Initial version: November 2009. Revised: February 2010.
[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, pp. 83–94, June 2010.
[doi]

[15]

V. V. Desai, V. F. Farias, C. C. Moallemi. Approximate dynamic programming via a smoothed linear program. To appear in Operations Research. Initial version: August 2009. Revised: June 2011.
[pdf]

*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, pp. 459–467, 2009.

2008

[14]

C. C. Moallemi, B. Park, B. Van Roy. Strategic execution in the presence of an uninformed arbitrageur. To appear in The Journal of Financial Markets. Initial version: January 2008. Revised: December 2010.
[pdf]

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]

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, pp. 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]

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, 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]

[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: September 2008.
[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, pp. 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]

Preliminary version:

C. C. Moallemi, B. Van Roy. Consensus propagation. In Advances in Neural Information Processing Systems 18, MIT Press, pp. 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, 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]