Hello! My name is Daniel (Dan) and I am currently a Lecturer in Operations Research and Financial Engineering at Princeton University.

You can also find me on Google Scholar, LinkedIn, and GitHub.

My research interests include:

  • Network science and social opinion dynamics
  • Algorithmic fairness
  • Dynamical systems and control
  • Systemic risk and financial networks
  • Computational social science

See here for a reasonably up-to-date copy of my CV.

In my free time, I enjoy music, ceramics, board games, cooking and reading.

Research

I have been fortunate to work on a wide variety of projects.

In the past, I participated in the Fragile Families Challenge with Prof. Sandy Pentland's Human Dynamics group at the MIT Media Lab, and developed my undergraduate thesis at the Newman Biomechanics Lab with Prof. Neville Hogan.

A branch of my work studies networks and their applications. In particular, I am interested in modeling and addressing sources of fragility in socioeconomic networks.

In social networks, our views are shaped by others - but not everyone. The connections we make create a complex structure which governs the spread of opinions. However, the rise of social media has been accompanied by increases in sociopolitical polarization. My research seeks to understand how small changes to the network's structure can drive a population closer to consensus.

Financial networks are believed to exacerbate crises -- facilitating the propagation of local distress to a global scale. Any individual bank might make optimal investment decisions for their own purposes, but may contribute to systemic fragility and inefficiency. My research in this area develops new models of financial networks -- based on portfolio optimization -- that highlight the difference between individual and collective optima.

A second and more recent area of work understands tradeoffs in algorithmic fairness seen through distinct ethical theories. In doing so, it becomes possible for the preferences of model builders -- or even users -- over different measures of the 'good' to inform their ideal design choice.

Other branches of my work study optimal design of robust global supply chains, and real-time measurement of business dynamics with data from Google Places -- both motivated by challenges seen during the COVID pandemic.

I also have the privilege and pleasure of advising undergraduate senior theses; here are a couple recent examples.

Education

  • B.S. in Mechanical Engineering, 2018

    Minors in Economics and Statistics.

  • Ph.D. in ORFE, 2023

    Advised by Miklós Rácz and Ronnie Sircar.

Selected Publications

  • Princeton ORFE2023

    Collective Good and Optimization in Socioeconomic Systems

    PhD Thesis supervised by Miklós Rácz and Ronnie Sircar.

    Essays on tensions between what different decision-makers may deem 'optimal' and competing notions of societal good.(PDF)

  • Preprint2023

    From Utilitarian to Rawlsian Designs for Algorithmic Fairness

    Tradeoffs between two different (and often conflicting) ethical frameworks when building predictive models. (PDF)

  • Preprint2022

    Formation of Optimal Interbank Lending Networks under Liquidity Shocks

    with R. Sircar

    Understanding how portfolio optimization yields systemic inefficiencies. (PDF)

  • IEEE TNSE2022

    Towards Consensus: Reducing Polarization by Rewiring Social Networks

    with M. Racz

    Quantifying the sensitivity of polarization to social network structures. (PDF)

  • AEA P&P2023

    Timely Business Dynamics using Google Places

    with T. Duprey, A. Kotlicki, P. Shnattinger

    Unique advantages of our methodology. (Forthcoming)

    Working paper version available (PDF)

  • JRFM2022

    Business Closures and (Re)Openings in Real-Time Using Google Places: Proof of Concept

    with T. Duprey, A. Kotlicki, P. Shnattinger, S. Baharian, and T. R. Hurd.

    A novel methodology for timely estimation of business dynamics. (PDF)

  • IMF Econ. Review2021

    From “Just in Time” to “Just in Case”: Simple Models of Global Supply Chains and Aggregate Shocks

    with B. Jiang and R. Rigobon.

    Understanding the vulnerabilities of optimized supply chains. (PDF)

  • PNAS2020

    Measuring the Predictability of Life Outcomes with a Scientific Mass Collaboration

    with M. Salganik et al.

    Participated in a large-scale challenge to predict sociological outcomes out-of-sample. (PDF)

  • Socius2019

    Winning Models for GPA, Grit, and Layoff in the Fragile Families Challenge

    with E. Jahani, Y. Suhara, A. Pentland and A. Almaatouq et al.

    Predicting children's later-in-life outcomes with a set of diverse statistical learning techniques. (PDF)

  • MIT2018

    Models of Entrainment of Human Walking

    Undergraduate Thesis with N. Hogan and J.Lee.

    Modeling the emergence of the rhythmic patterns in gait. (PDF)

  • ASME DSCC2017

    Entrainment of Ankle-Actuated Walking Model to Periodic Perturbations via Leading Leg Angle Control

    with J. Ochoa and N. Hogan.

    Designing a simple energy-based controller to replicate experimental findings. (PDF)