Wenpin Tang's Home Page

About me

Currently, I am an Assistant Professor at Department of Industrial Engineering and Operations Research, Columbia University. Before joining Columbia IEOR, I was a postdoctoral researcher at Department of Industrial Engineering and Operations Research, UC Berkeley, and an assistant adjunct professor at Department of Mathematics, UCLA. I obtained my Ph.D. from Department of Statistics, UC Berkeley. My advisor was Jim Pitman . Before coming to Berkeley, I obtained an engineer diploma (Diplôme d'ingénieur) from Ecole Polytechnique, France.


My research interests are probability theory, machine learning, and financial technology.


[47] Mallows-DPO: fine-tune your LLM with preference dispersions .
with Haoxian Chen, Hanyang Zhao, Henry Lam and David Yao. Submitted.

[46] Fine-tuning of diffusion models via stochastic control: entropy regularization and beyond .

[45] Score-based diffusion models via stochastic differential equations -- a technical tutorial .
with Hanyang Zhao. Submitted (growing out of the writeup).

[44] Contractive diffusion probabilistic models .
with Hanyang Zhao. Submitted. .

[43] Transaction fee mechanism for Proof-of-Stake protocol .
with David D. Yao. Submitted.

[42] Finite and infinite weighted exchangeable sequences .

[41] Exact Bayesian geostatistics using predictive stacking .
with Lu Zhang and Sudipto Banerjee. Submitted.

[40] The convergence rate of vanishing viscosity approximations for mean field games .
with Yuming Paul Zhang. Submitted.

[39] Policy iteration for the deterministic control problems -- a viscosity approach .
with Hung Vinh Tran and Yuming Paul Zhang. Submitted.

[38] Systemic robustness: a mean-field particle system approach .
with Erhan Bayraktar, Gaoyue Guo and Yuming Paul Zhang. Submitted.

[37] Stability of shares in the Proof of Stake protocol -- concentration and phase transitions .

[36] Learning an arbitrary mixture of two multinomial logits .


[35] Discrete simulated annealing: a convergence analysis via the Eyring--Kramers law .
with Yuhang Wu and Xun Yu Zhou. To appear in Numerical Algebra, Control and Optimization .

[34] Polynomial voting rules .
with David D. Yao. To appear in Mathematics of Operations Research.

[33] Trading and wealth evolution in the Proof of Stake protocol .
Proof-of-Stake for Blockchain Networks: Fundamentals, Challenges and Approaches (2024) Chapter 7, 135-161.

[32] Fixed-domain asymptotics under Vecchia's approximation of spatial process likelihoods .
with Lu Zhang and Sudipto Banerjee. To appear in Statistica Sinica.

[31] McKean-Vlasov equations involving hitting times: blow-ups and global solvability .
with Erhan Bayraktar, Gaoyue Guo and Yuming Paul Zhang. Annals of Applied Probability (2024) vol.34, no.1B, 1600–1622.

[30] Escaping saddle points efficiently with occupation-time-adapted perturbations .
with Xin Guo, Jiequn Han and Mahan Tajrobehkar. Journal of Computational Mathematics and Data Science (2024) vol.10, 100090.

[29] Policy optimization for continuous reinforcement learning .
with David D. Yao and Hanyang Zhao. Advances in Neural Information Processing Systems (Neurips 2023) vol.36, 13637-13663.

[28] One-dependent hard-core processes and colorings of the star graph .
with Thomas Liggett. Annals of Applied Probability (2023) vol.33, no.6A, 4341–4365.

[27] Trading under the Proof-of-Stake protocol -- a continuous-time control approach .
with David D. Yao. Mathematical Finance (2023) vol.33, no.4, 979-1004.

[26] Tail probability estimates of continuous-time simulated annealing processes .
with Xun Yu Zhou. Numerical Algebra, Control and Optimization (2023) vol.13, no.3-4, 473-485.

[25] Fixed-domain inference for Gausian processes with Matérn covariogram on compact Riemannian manifolds .
with Didong Li and Sudipto Banerjee. Journal of Machine Learning Research (2023) vol.24, no.101, 1-26.

[24] Extreme order statistics of random walks .
with Jim Pitman. Annales de l'Institut Henri Poincaré (2023) vol.59, no.1, 97-116.

[23] The Poisson binomial distribution -- Old & New .
with Fengmin Tang. Statistical Science (2023) vol.38, no.1, 108-119.

[22] Exploratory HJB equations and their convergence .
with Yuming Zhang and Xun Yu Zhou. SIAM Journal on Control and Optimization (2022) vol.60, no.6, 3191-3216.

[21] Ergodicity of the infinite swapping algorithm at low temperature .
with Georg Menz, André Schlichting and Tianqi Wu. Stochastic Processes and their Applications (2022) vol 151, 519-552.

[20] Hidden symmetries and limit laws in the extreme order statistics of the Laplace random walk .
with Jim Pitman. Annals of Probability (2022) vol.50, no.4, 1647-1673.

[19] Parallel search for information in continuous time -- optimal stopping and geometry of the PDE .
with T. Tony Ke, J. Miguel Villas-Boas and Yuming Zhang. Applied Mathematics and Optimization (2022) vol.85, article 3, 1-25.

[18] Asset selection via correlation blockmodel clustering .
with Xiao Xu and Xun Yu Zhou. Expert Systems with Applications (2022) vol.195, 116558.

[17] A stochastic game and stochastic free boundary problem .
with Xin Guo and Renyuan Xu. SIAM Journal on Control and Optimization (2022) vol.60, no.2, 758-785.

[16] On identifiability and consistency of the nugget in Gaussian spatial process models .
with Lu Zhang and Sudipto Banerjee. Journal of the Royal Statistical Society: Series B (2021) vol.83, no.5, 1044-1070.

[15] Arcsine laws for random walks generated from random permutations with applications to genomics .
with Xiao Fang, Han Liang Gan, Susan Holmes, Haiyan Huang, Erol Peköz and Adrian Röllin. Journal of Applied Probability (2021) vol.58, no.4, 851-867.

[14] The existence of maximum likelihood estimate in high-dimensional generalized linear models with binary responses .
with Yuting Ye. Electron. J. Statist (2020) vol.14, no.2, 4028-4053.

[13] The Buckley-Osthus model and the block preferential attachment model: statistical analysis and application .
with Xin Guo and Fengmin Tang. Proceedings of the 37th International Conference on Machine Learning (ICML 2020) PMLR 119, 9377-9386.

[12] Mallows ranking models: maximum likelihood estimate and regeneration .
Proceedings of the 36th International Conference on Machine Learning (ICML 2019) PMLR 97, 6125-6134.

[11] Exponential ergodicity and convergence for generalized reflected Brownian motion .
Queueing Systems: Theory and Applications (2019) vol.92, no.1, 83-101.

[10] Renewal sequences and record chains related to multiple zeta sums .
with Jean-Jil Duchamps and Jim Pitman. Transactions of AMS (2019) vol.371, no.8, 5731-5755.

[9] Regenerative random permutations of integers .
with Jim Pitman. Annals of Probability (2019) vol.47, no.3, 1378-1416.

[8] Transporting random measures on the line and embedding excursions into Brownian motion .
with Günter Last and Hermann Thorisson. Annales de l'Institut Henri Poincaré (2018) vol.54, no.4, 2286-2303.

[7] The argmin process of random walks, Brownian motion and Lévy processes .
with Jim Pitman. Electro. J. Probab (2018) vol.23, no.60, 1-35.

[6] Optimal surviving strategy for drifted Brownian motions with absorption .
with Li-Cheng Tsai. Annals of Probability (2018) vol.46, no.3, 1597-1650.

[5] Tree formulas, mean first passage times and Kemeny's constant of a Markov chain .
with Jim Pitman. Bernoulli (2018) vol.24, no.3, 1942-1972.

[4] The spans in Brownian motion .
with Steve Evans and Jim Pitman. Annales de l'Institut Henri Poincaré (2017) vol.53, no.3, 1108-1135.

[3] The Slepian zero set, and Brownian bridge embedded in Brownian motion by a spacetime shift .
with Jim Pitman. Electro. J. Probab (2015) vol.20, no.61, 1-28.

[2] Patterns in random walks and Brownian motion .
with Jim Pitman. Séminaire de probabilité XLVII - In Memoriam Marc Yor (2015), 49-88.

[1] The Vervaat transform of Brownian bridges and Brownian motion .
with Titus Lupu, Jim Pitman. Electro. J. Probab (2015) vol.20, no.51, 1-31.

Recent talks

April, 2024: Rice Univeristy, CMOR Colloquium .
Jan, 2024: University of Texas at San Antonio, ECE seminar .
Oct, 2023: Pheonix, INFORMS .
Sept, 2023: Virtual, CityU-NUS Mean Field Game and Control Seminar .
Sept, 2023: University of Pennsylvania, Wharton Statistics seminar .
July, 2023: Lisbon, 43rd Conference on Stochastic Processes and their Applications .
May, 2023: Carnegie Mellon University, Secure Blockchain Summit .
Mar, 2023: University of Pennsylvania, Penn/Temple Probability Seminar .
Feb, 2023: Columbia University, Applied Mathematics Colloquium .
Nov, 2022: Virtual, Hong Kong-Singapore joint seminar in Financial Mathematics/Engineering .
Nov, 2022: Columbia University, Mathematical Finance seminar .
Oct, 2022: Indianapolis, INFORMS .
July, 2022: SIAM Annual Meeting, Machine Learning in Finance: Theory and Application .
May, 2022: Institute for Mathematical and Statistical Innovation, Workshop: Machine Learning and Mean Field Games .
Feb, 2022: University of Southern California, Mathematical Finance Colloquium .
Nov, 2021: Princeton University, ORFE Financial Mathematics seminar .
Oct, 2021: UCLA, Probability seminar .
July, 2021: Institute for Mathematical and Statistical Innovation, Program: Introduction to Decision Making and Uncertainty .
June, 2021: Paris, Séminaire Bachelier .
May, 2021: University of Mannheim, Probability seminar .
Dec, 2020: Virtual, Workshop on Optimization, Probability, and Simulation.
Oct, 2020: Virtual, INFORMS .
Mar, 2020: University of Michigan, Financial/Actuarial Mathematics Seminar .
Feb, 2020: Cornell University, ORIE Colloqium .
Feb, 2020: Columbia University, IEOR Department Seminar .
Jan, 2020: Baruch College, Mathematics Colloquium .
Jan, 2020: University of Utah, Mathematics Colloqium .
Jan, 2020: Northwestern University, Mathematics Colloqium .
Dec, 2019: University of Cincinnati, Probability Seminar .
Dec, 2019: University of Miami, Mathematics Colloquium .
Nov, 2019: North Carolina State University, Mathematics Colloquium .
Nov, 2019: Riverside, AMS meeting .
Nov, 2019: UCSD, Probability Seminar .
Oct, 2019: University of Washington, Probability Seminar .
Oct, 2019: Seattle, INFORMS .
Sept, 2019: UC Berkeley, Probabilty Seminar .
June, 2019: Los Angeles, ICML Oral .
Feb, 2019: UCLA, Combinatorics Seminar .
Dec, 2018: Los Angeles, Southern California Probability Symposium .
Oct, 2018: San Francisco, AMS meeting .
July, 2018: Stanford, Workshop in memory of Larry Shepp .
Feb, 2018: Stanford University, Probability Seminar .
Feb, 2018: UC Berkeley, IEOR Colloquium .
Dec, 2017: University of Chicago, Probability and Statistical physics seminar .
Nov, 2017: UCLA, Probability Seminar .
Mar, 2017: UCLA, Probability Seminar .
Mar, 2017: UC Berkeley, Probability Seminar .
July, 2016: Edmonton, IMS-FIPS Workshop .
Mar, 2016: Berkeley, Berkeley-Columbia Meeting in Engineering and Statistics .
Feb, 2015: UC Davis, Mathematical Physics and Probability Seminar .
Feb, 2015: UC Berkeley, Probability Seminar .
Oct, 2014: UC Berkeley, Student Probability/PDE Seminar .
July, 2014: Saint-Flour, 44th probability summer school.
June, 2014: San Diego, Combinatorial Stochastic Processes: A conference in celebration of Jim Pitman's 65th birthday .
July, 2013: Saint-Flour, 43rd probability summer school.
Sept, 2013: UC Berkeley, SGSA Student Seminar .


In Fall 2021, I will teach IEOR E4706: Foundations of Financial Engineering.