I am an assistant professor in Industrial Engineering and Operations Research (IEOR) at Columbia University. From 2015-2017 I was an NSF postdoctoral fellow in the Division of Applied Mathematics at Brown University, and before that I completed my Ph.D. in 2015 at Princeton University in the department of Operations Research and Financial Engineering (ORFE). My research so far has focused largely on the theory and applications of mean field games, where the areas of interacting particle systems, stochastic control, and game theory intersect. More broadly, I am interested in many topics in probability and mathematical finance. Click here for a complete CV.
In the Fall 2017 semester I am teaching IEOR 4701, Stochastic Models. Information and course materials are posted on Courseworks.
Office: Mudd 306
Email: daniel.lacker (at) columbia (dot) edu
Publications and Preprints
Mean field and n-agent games for optimal investment under relative performance criteria
With Thaleia Zariphopoulou. Preprint. [arXiv]
Rare Nash equilibria and the price of anarchy in large static games
With Kavita Ramanan. Preprint. [arXiv]
Limit theory for controlled McKean-Vlasov dynamics
To appear in SIAM Journal on Control and Optimization. [arXiv, DOI]
A non-exponential extension of Sanov's theorem via convex duality
Mean field games of timing and models for bank runs
With René Carmona and François Delarue. Applied Mathematics & Optimization. [arXiv, DOI]
Liquidity, risk measures, and concentration of measure
To appear in Mathematics of Operations Research. [arXiv]
Law invariant risk measures and information divergences
Translation invariant mean field games with common noise
With Kevin Webster. Electronic Communications in Probability. [arXiv, DOI]
A general characterization of the mean field limit for stochastic differential games
Probability Theory and Related Fields. [arXiv, DOI]
Winner of the 2014 SIAG/FME Conference Paper Prize.
Mean field games with common noise
With René Carmona and François Delarue. Annals of Probability. [arXiv, DOI]
Mean field games via controlled martingale problems: Existence of Markovian equilibria
Stochastic Processes and their Applications. [arXiv, DOI]
A probabilistic weak formulation of mean field games and applications
With René Carmona. Annals of Applied Probability. [arXiv, DOI]
Stochastic differential mean field game theory
My PhD Thesis. [PDF]
Last updated: September, 2017.