Hi! My name is Stylianos DespotakisGreek: Στυλιανός Δεσποτάκης, pronounced [stiʎa'nos ðespo'takis] steel-yah-NOHSS theh-spoh-TAH-kees. I usually go by SteliosGreek: Στέλιος, pronounced ['steʎos] STELL-yohs.

Research Interests

My research interests lie in the interdisciplinary area of game theory, marketing, microeconomics, and operations research.

Topics: Competitive Strategy, Online Markets, Online Advertising, Auction Theory, Marketing Analytics


August 2012–May 2018
August 2012–May 2014
Carnegie Mellon University, Pittsburgh, PA, USA
September 2010–July 2012
MSc in Logic, Algorithms, and Computation
GPA: 10.00/10.00 (ranked 1st in my year)
September 2006–June 2010
BSc in Mathematics
GPA: 9.56/10.00 (ranked 1st in my year)
September 2003–June 2006
Pefka High School, Thessaloniki, Greece
GPA: 19.5/20.0

Research Papers



We examine the effect of the presence of expert buyers on other buyers, the platform, and the sellers in online markets. We model buyer expertise as the ability to accurately predict the quality, or condition, of an item, modeled as its common value. We show that nonexperts may bid more aggressively, even above their expected valuation, to compensate for their lack of information. As a consequence, we obtain two interesting implications. First, auctions with a “hard close” may generate higher revenue than those with a “soft close”. Second, contrary to the linkage principle, an auction platform may obtain a higher revenue by hiding the item's common-value information from the buyers. We also consider markets where both auctions and posted prices are available and show that the presence of experts allows the sellers of high quality items to signal their quality by choosing to sell via auctions.



In this paper, we study the problem of attributing credit for customer acquisition to different components of a digital marketing campaign using an analytical model. We investigate attribution contracts through which an advertiser tries to incentivize two publishers that affect customer acquisition. We situate such contracts in a two-stage marketing funnel, where the publishers should coordinate their efforts to drive conversions.

First, we analyze the popular class of multi-touch contracts where the principal splits the attribution among publishers using fixed weights depending on their position. Our first result shows the following counterintuitive property of optimal multi-touch contracts: higher credit is given to the portion of the funnel where the existing baseline conversion rate is higher. Next, we show that social welfare maximizing contracts can sometimes have even higher conversion rate than optimal multi-touch contracts, highlighting a prisoners' dilemma effect in the equilibrium for the multi-touch contract. While multi-touch attribution is not globally optimal, there are linear contracts that “coordinate the funnel” to achieve optimal revenue. However, such optimal-revenue contracts require knowledge of the baseline conversion rates by the principal. When this information is not available, we propose a new class of ‘reinforcement’ contracts and show that for a large range of model parameters these contracts yield better revenue than multi-touch.



While online advertising is the lifeline of many internet content platforms, the usage of ad blockers has surged in recent years presenting a challenge to platforms dependent on ad revenue. Using a simple analytical model with two competing platforms, we show that the presence of ad blockers can actually benefit platforms. In particular, there are conditions under which the optimal equilibrium strategy for the platforms is to allow the use of ad blockers (rather than using an adblock wall, or charging a fee for viewing ad-free content). The key insight is that allowing ad blockers serves to differentiate platform users based on their disutility to viewing ads. This allows platforms to increase their ad intensity on those that do not use the ad blockers and achieve higher returns than in a world without ad blockers. We show robustness of these results when we allow a larger combination of platform strategies, as well as by explaining how ad whitelisting schemes offered by modern ad blockers can add value. Our study provides general guidelines for what strategy a platform should follow based on the heterogeneity in the ad sensitivity of their user base.

Honors and Awards

2015 Winner (team of two) of the SMART Workshop Structural Modeling Challenge, Carnegie Mellon University
2014 Egon Balas Award for the Best paper in Operations Research / Algorithms, Combinatorics & Optimization, Carnegie Mellon University
2012–2016 William Larimer Mellon Fellowship, Carnegie Mellon University
2010–2011 Mytilinaios Prize for ranking 1st among the students of the Logic, Algorithms, and Computation graduate program
2008–2010 Thomas Papamichailidis Scholarship for ranking 1st among the students of the Faculty of Sciences and the Faculty of Engineering (2 years)
2006–2010 Four Awards from the State Scholarships Foundation (IKY) for ranking 1st among the students of the Department of Mathematics
2006 First member of the national team at the 23rd Balkan Mathematical Olympiad
2006 Gold Medal at the 23rd National Mathematical Olympiad
2005 Bronze Medal at the 22nd National Mathematical Olympiad
2002–2005 Two First Prizes and two Honorable mentions at the National Mathematical Competition Euclid held by the Hellenic Mathematical Society

Teaching Experience

Co-instructor for
  • Optimization for Interactive Marketing, Tepper 45-853, MBA, Fall 2016
Teaching Assistant for
  • Optimization for Interactive Marketing, Tepper 45-853, MBA, Spring 2016
  • Business Networks, Tepper 45-951, MBA, Fall 2015
  • Business Networks, Tepper 45-951, MBA, Fall 2014
  • Linear Programming, Tepper 47-834, PhD, Fall 2014
  • Optimization, Tepper 45-751, MBA, Spring 2014
  • Graph Theory, Tepper 47-835, PhD, Fall 2013
  • Applications of Operations Research, Tepper 45-850, MBA, Fall 2013

Graduate Coursework (selected)

  • Fall 2015: Econometrics I (47-811)
  • Spring 2015: Analytical and Structural Marketing Models (47-744)
  • Fall 2014: Advanced Stochastic Analysis and Applications I (47-774), Advanced Stochastic Analysis and Applications II (47-775)
  • Spring 2014: Random Graphs (21-801)
  • Fall 2013: A Theorist's Toolkit (15-859), Real Analysis (21-620), Introduction to Lebesgue Integration (21-621)
  • Spring 2013: Graduate Algorithms (15-750), Algorithms Games and Networks (15-896), Integer Programming (47-830), Advanced Integer Programming (47-831)
  • Fall 2012: Discrete Mathematics (21-701), Linear Programming (47-834), Graph Theory (47-835), Networks and Matchings (47-836), Dynamic Programming (47-840)
  • Fall 2011: Computational Game Theory, Computational Algebra, Advanced Approximation Algorithms
  • Spring 2011: Mathematical Logic, Algorithms and Complexity II, Set Theory, Approximation Algorithms
  • Fall 2010: Computability, Algorithms and Complexity I, Graph Theory, Cryptography and Complexity

Computer Skills

Mathematica, C/C++, Python, R, HTML/CSS, Javascript (jQuery), LaTeX, Cambridge IT Skills Proficiency

Other Activities

  • Chess: I was an active member of the Pefka Chess Club during the period 2002–2006 (participating in tournaments with many distinctions).
  • Solving algorithmic and mathematical problems (e.g. ranked 1st in the world on ProjectEuler.net in December 2008 after solving all 221 problems by then).