Hello! My name is Daniel / Dan and I am currently working towards my Ph.D. in Operations Research and Financial Engineering at Princeton University.

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

My professional interests include:

  • Network science
  • Dynamical systems and control
  • Systemic risk
  • Continuous-time mathematics
  • Data analytics

See here for an up-to-date copy of my full CV.

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


Research

I have been fortunate to work on a wide variety of projects. I participated in the Fragile Families Challenge with Prof. Pentland's Human Dynamics group at the MIT Media Lab, and developed my undergraduate thesis at the Newman Biomechanics Lab with Prof. Hogan.

My current work studies networks and their applications. In particular, I am interested in the relationship between a structure that governs the interactions of individuals, and emergent phenomena in a population.

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. The first branch of my research seeks to understand how small changes to the network's structure can drive a population closer to consensus.

Financial networks are allegedly responsible for the propagation of local crises to a global scale. Any individual bank might make optimal decisions for their own purposes, but the price of anarchy may be a fragile system. My research in this area develops new models of financial networks that highlight the difference between individual and collective optima.

In practice, network effects are extremely difficult to estimate; in many cases the network is not even observable. This is a major disconnect between theory and practice. Although this problem has been approached from the perspective of factor models and controlled experiments, these techniques suffer from identification issues, and cannot provide a statistical certificate of validity. The final area of my research addresses this challenge by solving the fundamental network identification issue.


Education

  • B.S. in Mechanical Engineering

    Graduated in 2018, minors in Economics and Statistics.

  • Ph.D. Candidate in ORFE

    Advised by Miklos Racz and Ronnie Sircar.


Publications

  • Working Paper

    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.

  • 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 exhibit experimental findings. PDF