Research

I am interested in Reinforcement Learning, Inference, Approximation Algorithms and applications thereof (recently, to Commerce Platforms and Biology). More broadly, I am interested in Dynamic Optimization and the analysis of complex stochastic systems.

Preprints
43 V. F. Farias, A. A. Li, T. Peng and A. Zheng. “ Markovian Interference in Experiments. ” Submitted.
Preliminary version:
  • V. F. Farias, A. A. Li, T. Peng and A. Zheng “ Markovian Interference in Experiments. ” 36th Annual Conference on Neural Information Processing Systems (NeurIPS), 2022. [Oral]
2022 RMP Jeff McGill Student Paper Award, First Prize
2022 Applied Probability Society Student Paper Prize, First Prize
42 V. F. Farias, A. A. Li and T. Peng. “ Uncertainty Quantification For Low-Rank Matrix Completion With Heterogeneous and Sub-Exponential Noise. ” Submitted.
Preliminary version:
  • V. F. Farias, A. A. Li and T. Peng. “ Uncertainty Quantification For Low-Rank Matrix Completion With Heterogeneous and Sub-Exponential Noise. ” 25th International Conference on Artificial Intelligence and Statistics (AISTAT), 2022.
41 J. Baek and V. F. Farias. “ Fair Exploration via Axiomatic Bargaining. ” Submitted.
Preliminary version:
  • J. Baek and V. F. Farias. “ Fair Exploration via Axiomatic Bargaining. ” 35th Annual Conference on Neural Information Processing Systems (NeurIPS), 2021. [Spotlight]
2022 MSOM Student Paper Competition, Second Prize
2021 RMP Jeff McGill Student Paper Award, Finalist
2021 MIT ORC Best Student Paper Award, Honorable Mention
2021 George Nicholson Student Paper Competition, finalist
40 V. F. Farias, A. A. Li and T. Peng. “ Learning Treatment Effects with General Intervention Patterns. ” Submitted.
Preliminary version:
  • V. F. Farias, A. A. Li and T. Peng. “ Learning Treatment Effects with General Intervention Patterns. ” 35th Annual Conference on Neural Information Processing Systems (NeurIPS), 2021. [Oral]
2022 MSOM Student Paper Competition, Finalist
39 V. F. Farias, A. A. Li and T. Peng. “ Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise. ” Submitted.
Preliminary version:
  • V. F. Farias, A. A. Li and T. Peng. “ Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise. ” 38th International Conference on Machine Learning (ICML), 2021.
38 J. Baek, V. F. Farias, A. Georgescu, R. Levi, T. Peng, D. Sinha, J. Wilde and A. Zheng. “ The Limits to Learning a Diffusion Model. ” Submitted.
Preliminary version:
  • J. Baek, V. F. Farias, A. Georgescu, R. Levi, T. Peng, D. Sinha, J. Wilde and A. Zheng. “ The Limits to Learning a Diffusion Model. ” 21st ACM Conference on Economics and Computation (EC), 2021.
37 V. F. Farias, A. A. Li and D. Sinha. “ Optimizing Offer Sets in Sub-Linear Time. ” R & R in Management Science.
Preliminary version:
  • V. F. Farias, A. A. Li and D. Sinha. “ Optimizing Offer Sets in Sub-Linear Time. ” 21st ACM Conference on Economics and Computation (EC), 2020.
2020 RMP Jeff McGill Student Paper Award, Finalist
36 N. Bhat, V. F. Farias, C. C. Moallemi and A. Zheng “ Non-parametric Approximate Dynamic Programming via the Kernel Method. ” Confitionally accepted in Stochastic Systems.
Preliminary version:
  • N. Bhat, V. F. Farias, and C. C. Moallemi. “ Non-parametric Approximate Dynamic Programming via the Kernel Method. ” Advances in Neural Information Processing Systems (NIPS) 25, 2012.
Publications
35 Ferdosi, S. et al. “ Enhanced competition at the nano‐bio interface enables comprehensive characterization of protein corona dynamics and deep coverage of proteomes. ” Forthcoming in Advanced Materials.
34 Cramer, E. Y. et al. “ Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US. ” Forthcoming in Proceedings of the National Academy of Sciences.
33 V. F. Farias and E. Gutin. “ Optimisitc Gittins Indices. ” Forthcoming in Operations Research.
Preliminary version:
  • V. F. Farias and E. Gutin. “ Optimisitc Gittins Indices. ” Advances in Neural Information Processing Systems (NIPS) 29, 2016.
32 C. Corbo, A. A. Li, H. Poustchi, G. Lee, S. Stacks, R. Molinaro, P. Ma, T. Platt, S. Behzadi, R. Langer, V. F. Farias, O. C. Farokhzad “ Analysis of the Human Plasma Proteome Using Multi‐Nanoparticle Protein Corona for Detection of Alzheimer's Disease ” Advanced Healthcare Materials 10, No. 2 (2021): 2000948.
31 J. E. Blume*, W. C. Manning, G. Troiano, D. Hornburg, M. Figa, L. Hesterberg, T. L. Platt, X. Zhao, R. A. Cuaresma, P. A. Everley, M. Ko, H. Liou, M. Mahoney, S. Ferdosi, E. M. Elgierari, C. Stolarczyk, B. Tangeysh, H. Xia, R. Benz, A. Siddiqui, S. A. Carr, P. Ma, R. Langer, V. F. Farias*, and O. C. Farokhzad* “ Rapid, Deep and Precise Profiling of the Plasma Proteome with Multi-Nanoparticle Protein Corona ” Nature Communications 11, No. 1 (2020): 1-14.
    Top 50 Read Nature Communications chemistry and materials science articles published in 2020
    30 J. M. Andrews, V. F. Farias, A. I. Khojandi, C. M. Yan “ Primal–Dual Algorithms for Order Fulfillment at Urban Outfitters, Inc. ” Interfaces, 49, No. 5 (2019): 355-370.
      2018 Daniel H. Wagner Prize, Finalist
      29 A. Aouad, V. F. Farias, and R. Levi. “ Assortment Optimization Under Consider-then-Choose Choice Models ” Management Science 67, No. 6 (2021): 3368-3386.
        2015 MIT ORC Best Student Paper Award
        28 V. F. Farias, S. Jagabathula, and D. Shah. “ Inferring Sparse Preference Lists from Partial Information ” Stochastic Systems 10, No. 4 (2020): 335-360.
          2016 Gary L. Lilien ISMS-MSI Practice Prize, Finalist           		pdf link
          27 Y. C. Chen, V. F. Farias, and N. Trichakis. “ On the Efficacy of Static Prices for Revenue Management in the Face of Strategic Customers. ” Management Science, 65, No. 12 (2019): 5535-5555.
          Preliminary version:
          • Y. C. Chen, and V. F. Farias. “ On the Efficacy of Static Prices for Revenue Management in the Face of Strategic Customers. ” 17th ACM Conference on Economics and Computation (EC), 2016.
          26 N. Bhat, V. F. Farias, C. C. Moallemi, and D. Sinha. “ Near Optimal A-B testing ” Management Science 66, No. 10 (2020): 4477-4495.
          25 A. Aouad, V. F. Farias, R. Levi, and D. Segev,. “ The Approximability of Assortment Planning Under Ranking Preferences ” Operations Research, 66, No. 6 (2018): 1661-1669.
          24 V. F. Farias and A. A. Li. “ Learning Preferences with Side Information. ” Management Science, 65, No. 7 (2019): 3131-3149.
          Preliminary version:
          • V. F. Farias and A. A. Li. “ Optimal Recovery of Tensor Slices. ” Artificial Intelligence and Statistics (AISTAT), 2017.
          2017 MIT ORC Best Student Paper Award
          2017 George Nicholson Stident Paper Competition, first place
          23 Y. C. Chen, and V. F. Farias. “ Robust Dynamic Pricing With Strategic Customers. ” Mathematics of Operations Research, 43, No. 4 (2018): 1119-1142.
          • Y. C. Chen, and V. F. Farias. “ Robust Dynamic Pricing With Strategic Customers. ” 16th ACM Conference on Economics and Computation (EC), 2015.
          22 F. Bravo, M. Braun, V. F. Farias, R. Levi, C. Lynch, J. Tumolo, and R. Whyte “ Optimization-driven framework to understand health care network costs and resource allocation.” Health Care Management Science, (2021): 1-21. pdf link
          21 C. W. Chan, V. F. Farias, and G. J. Escobar. “ The Impact of Delays on Service Times in the Intensive Care Unit.” Management Science, 63, No. 7 (2017): 2049-2071. pdf link
          20 P. Cho, V. F. Farias, J. Kessler, R. Levi, T. Magnanti, E. Zarybnisky. “ Maintenance and flight scheduling of low observable aircraft.” Naval Research Logistics (NRL), 62, No. 1 (2015): 60-80. pdf link
          19 Y. Chen, V. F. Farias. “ Simple Policies for Dynamic Pricing with Imperfect Forecasts ” Operations Research, 61, no. 3 (2013): 612-624. pdf link
          18 V. F. Farias, S. Jagabathula, and D. Shah. “ A Non-Parametric Approach to Modeling Choice with Limited Data. ” Management Science, 59, no. 2 (2013): 305-322.
          Preliminary version:
          • V. F. Farias, S. Jagabathula, and D. Shah. “ A Data-Driven Approach to Modeling Choice. &rdquo Advances in Neural Information Processing Systems 22, 2009. [Spotlight]
          2010 INFORMS MSOM Student Paper Competition, first place
          2015 INFORMS Revenue Management and Pricing Section Prize
          2016 INFORMS MSOM Best Paper in Management Science           		pdf link
          17 D. Bertsimas, V. F. Farias, and N. Trichakis. “ Fairness, Efficiency and Flexibility in Organ Allocation for Kidney Transplantation. ” Operations Research, 61, No. 1 (2013): 73-87.
            2011 INFORMS Pierskalla Award, finalist.             		pdf link
            16 D. F. Ciocan, V. F. Farias. “ Dynamic Allocation Problems with Volatile Demand ” Mathematics of Operations Research, 37, No. 3 (2012): 501-525.
              2013 INFORMS MSOM Student Paper Competition, Honoroable Mention.
              		 pdf link
              15 V. V. Desai, V. F. Farias, and 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 (2012): 452–473. pdf link
              14 V. V. Desai, V. F. Farias, and C. C. Moallemi. “ Pathwise Optimization for Optimal Stopping Problems. ” Management Science, 58, No. 12 (2012): 2292-2308.
                Best Simulation Publication Award, INFORMS Simulation Society, 2014                 		pdf link
                13 D. Bertsimas, V. F. Farias, and N. Trichakis. “ On the Efficiency-Fairness Tradeoff. ” Management Science, 58, No. 12 (2012): 2234-2250. pdf link
                12 C. W. Chan, V. F. Farias, N. Bambos, and G. J. Escobar. “ Optimizing ICU Discharge Decisions with Patient Readmissions.” Operations Research, 60, no. 6 (2012): 1323-1341. pdf link
                11 V. V. Desai, V. F. Farias, and C. C. Moallemi. “ Aproximate Dynamic Programming via a Smoothed Linear Program. ” Operations Research, 60, No. 3 (2012): 655-674.
                Preliminary version:
                • V. V. Desai, V. F. Farias, and C. C. Moallemi. “ A Smoothed Approximate Linear Program. ” Advances in Neural Information Processing Systems 22,2009. [Spotlight]
                2011 INFORMS JFIG Paper Competition, first place.                 		pdf link
                10 V. F. Farias, D. Saure, and G. Y. Weintraub. “ An Approximate Dynamic Programming Approach to Solving Dynamic Oligopoly Models ” RAND Journal of Economics, 43, No. 2 (2012): 253-282.
                  2009 INFORMS JFIG Paper Competition, second place.                   		pdf link
                  9 D. Bertsimas, V. F. Farias, and N. Trichakis. “ The Price of Fairness. ” Operations Research, 59, No. 1 (2011): 17-31. pdf link
                  8 V. F. Farias, R. Madan. “ Irrevocable Multi-Armed Bandit Policies. ” Operations Research, 59, No. 2 (2011): 383-399. pdf link
                  7 V. F. Farias, B. Van Roy. “An Approximate Dynamic Programming Approach to Network Revenue Management.” Submitted. pdf link
                  6 V. F. Farias, B. Van Roy. “Dynamic Pricing with a Prior on Market Response.” Operations Research, 58, No. 1 (2010): 16-29.
                    2006 INFORMS MSOM Student Paper Competition, second place.
                    		 pdf link
                    5 V. F. Farias, C. C. Moallemi, B. Van Roy, and T. Weissman. “ Universal Reinforcement Learning.” IEEE Transactions on Information Theory, 56, No. 5 (2010): 2441-2454.
                    Preliminary version:
                    • V. F. Farias, C. C. Moallemi, B. Van Roy, and T. Weissman. “ A Universal Scheme for Learning.” Proceedings of the IEEE International Symposium on Information Theory, Adelaide, Australia, September 2005.
                    		pdf link
                    4 C. W. Chan, V. F. Farias. “ Stochastic Depletion Problems: Effective Myopic Policies for a class of Dynamic Optimization Problems.” Mathematics of Operations Research, 34, No. 2 (2009): 333-350. pdf link
                    3 V. F. Farias, C. C. Moallemi, and B. Prabhakar. “Load Balancing with Migration Penalties.” Proceedings of the IEEE International Symposium on Information Theory, Adelaide, Australia, September 2005. pdf link
                    2 V. F. Farias, B. Van Roy. “Approximation Algorithms for Dynamic Resource Allocation.” Operations Research Letters, 34, No. 2 (2006): 180-190. pdf link
                    1 V. F. Farias, B. Van Roy. “Tetris: A Study of Randomized Constraint Sampling.” Probabilistic and Randomized Methods for Design Under Uncertainty, Springer Science & Business Media, 2006. [Tetris Demo] pdf link
                    Thesis
                    V.F. Farias. “Revenue Management Beyond "Estimate, Then Optimize"” Stanford University Ph. D. Thesis, 2007. pdf link