Visiting Columbia IEOR Dept
Researchers of interest to us are hidden in many depts in a typical university (CS, IS, OR, Business, EE, whatever), some even 100 city blocks uptown. I visited the Industrial Engineering and Operations Research dept at Columbia U, and presented an hour long talk on Ad Exchanges. I bring a CS/Algorithms perspective to problems, but the researchers in OR/Stochastic optimization have different perspective that will be particularly useful for problems in AdX and I look forward to learning from them.
- Nicolas Stier: Spoke about nonlinear optimization with complements and relationship to transportation systems; endogenizing smooth cost functions a la Klemperer's work on supply function equilibria; principle agents problem and contract theory for employer-employee relationship; models for net neutrality.
- Mariana Olvera, Assaf Zeevi and Ciamac C. Moallemi, over lunch. Relative sizes of display markets.
- Santiago Balseiro: Stochastic control modeling of AdX optimization problems.
- Mariana Olvera: Stochastic recursion and explanations for power law distribution of PageRank based on indegrees. Mariana noticed that short ads are repeated sometimes to fill in long slots, ad scheduling can do better.
- Vineet Goyal: Stochastic versions of query optimization problems. Electricity markets.
- Chris Wiggins: Applied mathematician, physicist, machine learner, computational biologist and more. Among other things, we managed to catch up on Mark Hansen's sabbatical at NY Times R&D and art installations.
- Jay Sethuraman: Reminisced about a SODA talk long time ago on combinatorial approach to computing determinants.
- Garud Iyengar: He pointed out that AdX standardizes the goods that are traded in spot auctions, and we discussed how to standardize goods to trade in futures market and pricing challenges.
- Garud Iyengar and Victoria Stodden ( a CS PhD + law, combining sparse approximation and legal/policy aspects of data, both of great interest to me): Dinner conversation on challenges with NSF's new data sharing policy.