J. David Smith

PhD in Computer Science
Software Engineer

emallson [at] emallson [dot] net

About Me

My name is (Johnathan) David Smith. Over the past decade, my career has taken a number of unexpected turns. A Software Engineer by trade, I received my Bachelor's while working alternately as an assistant for Dr. Nathan Jacobs on geometry in Computer Vision and as a summer intern at IBM. Following this, I pursued a doctorate at the University of Florida, studying Approximation Algorithms & Social Network Analysis under Dr. My T. Thai. After a long and interesting journey, I defended my dissertation in March 2020 and graduated May the same year.

Over the course of my career, I've explored many of my interests. I have spent many a day designing and implementing approximation algorithms that are efficient not only in theory but also in practice, and have developed a sizeable repertoir of skills and tools to evaluate program performance. At the same time, I have honed my skills in data analysis and visualization, having used both in my evaluation of program performance—and additionally in my independent work on community formation in social networks.

Outside of work, I am an avid gamer, electronic music afficionado, and casual student of Brazilian Jiu-Jitsu. I am currently the team lead and main tank for Occasional Excellence's weekend team in World of Warcraft, and have a seemingly ever-increasing list of RPG and turn-based strategy games to play through.


Ph.D. in Computer Science, University of Florida
Graduated May 2020.
B.Sc. in Computer Science & Mathematics, University of Kentucky
Graduated Summa cum laude in May 2015.

Personal Projects

WoW Progression Stats
Source Site

  • Collects, aggregates, and visualizes data about World of Warcraft players' progression through the highest difficulty content.

  • This data has previously been publicly available but never aggregated across the high-end community.

  • Frontend implemented in TypeScript / React, backend and analysis in Rust. Charts are implemented with Vega-Lite

WoWAnalyzer — Brewmaster Monk Analysis Module
Site Source

  • Current maintainer of the WoWAnalyzer module covering Brewmaster Monks.

  • This module analyzes user-submitted logs from World of Warcraft and provides suggestions and analytics to help players improve.

Slab - WoW Nameplate Addon

  • Built an addon for World of Warcraft to replace the built-in nameplates with a highly-efficient substitute.

  • Exploring the use of color as a signal in combat, inspired by the rainbow-identifiers Emacs package.

Profiling2 - WoW Profiling Addon

  • Built an addon for World of Warcraft to collect detailed runtime histogram for all addon scripts, with the goal of enabling analysis of the long tail of runtimes as well as identifying features that are a problem.

  • Built an associated site to visualize the data, incorporating Rust + WASM to parse the serialized data files.

Work Experience

Software Engineer, RPGLogs
January 2022 Present

  • Working on features across Warcraft Logs, FF Logs, and ESO Logs, including major contributions to game content releases, improving our internal tech for game support, major contributions to the Retail WoW talent tree support, and ongoing work on core site features.

  • Manage the WoWAnalyzer open-source project, keeping contributors un-blocked and building new Warcraft Logs features to support their work.

Lead Software Engineer, Doseform
June 2020 December 2021

  • Built new features to streamline patient prescription handling for Pharmacists.

  • Built features to interact with insurance claim processors, streamlining (and in some cases outright removing) data entry for handling thousands of COVID-19 vaccination claims.

  • Worked primarily in Clojure and ClojureScript. We made heavy use of many PostgreSQL-specific feature.

  • Continued as Technical Advisor for Doseform following my official departure in 2021.

Graduate Research & Teaching Assistant, University of Florida
August 2015 May 2020

  • Conducted research under Dr. My T. Thai at the intersection of social network analysis, discrete optimization, and approximation theory.

  • Designed algorithms for a number of optimization tasks on network data, with a focus on information flow and structural analysis built on randomized sampling procedures.

  • Communicated results effectively, resulting in 14 peer-reviewed conference & journal publications in top-tier venues such as ICML.

  • Taught Programming in C. Assisted with Introductory Programming in C++, Operating Systems, Algorithms, Networks, and Machine Learning.

Software Engineering Intern (AppScan Source), IBM
May 2015 August 2015

  • Developed a dataflow visualization from concept to complete prototype.

  • Specialized the visualization for use by developers in fixing security vulnerabilities.

  • Prototype built in JavaScript using Node.js with the React.js and D3.js libraries.

Undergraduate Research Assistant, University of Kentucky
May 2013 May 2014 August 2014 May 2015

  • Assisted with Computer Vision research under Dr. Nathan Jacobs

  • Developed a web-based interface for image calibration and the measuring of objects in images. Built in JavaScript using the HTML5 inline SVG with Django (a Python MVC framework) on the backend.

  • Helped with data collection, model construction, and model training for research papers. Primarily worked in Python and used Caffe for deep-learning.

ExtremeBlue Technical Intern, IBM
May 2014 August 2014

  • Designed and built a service for IBM’s Bluemix PaaS offering that enables users to manage & analyze traffic flowing to their application.

  • Researched competing search engine offerings, prepared comparative analysis and recommendation based on intended use case.

  • Used IBM’s DataPower appliance as a control point to enforce traffic policies and ElasticSearch with Kibana to provide rapid feedback on policies.

  • Written in JavaScript. Used Node.js for the service implementation and AngularJS for the user interface.

  • Managed tooling and built continuous deployment pipeline using Jenkins.


J David Smith, My T. Thai Measuring Edge Sparsity on Large Social Networks
In the Proceedings of ICWSM 2020. Canonical Version Author Version
J David Smith, My T. Thai Supporting a Storm: The Impact of Community on GamerGate's Lifespan
In the IEEE Transactions on Network Science and Engineering (2019). Canonical Version Author Version
Lan N. Nguyen, J David Smith, My T. Thai Vulnerability Assessment of Social Smart Grid: An Algorithmic Approach
In the Proceedings of IEEE GLOBECOM 2019. Canonical Version
Lan N. Nguyen, J. David Smith, Jinsung Bae, Jungmin Kang, Jungtaek Seo, My T. Thai Auditing on Smart-Grid with Dynamic Traffic Flows: An Algorithmic Approach
In the IEEE Transactions on Smart Grid (2019). Canonical Version
Xiang Li, J David Smith, Thang N. Dinh, My T. Thai TipTop: Almost Exact Solutions for Influence Maximization in Billion-Scale Networks
In the IEEE/ACM Transactions on Networking (2019). Canonical Version arXiv
Alan Kuhnle, J David Smith, Victoria Crawford, My T. Thai Fast Maximization of Non-Submodular, Monotonic Functions on the Integer Lattice
In the Proceedings of ICML 2018. arXiv
Xiang Li & J David Smith, Tianyi Pan, Thang N. Dinh, My Thai Quantifying Privacy Vulnerability to Socialbot Attacks: An Adaptive Non-submodular Model
In the IEEE Transactions on Emerging Topics in Computing (2018). Canonical Version
J David Smith, Alan Kuhnle, My T. Thai An Approximately Optimal Bot for Non-Submodular Social Reconnaissance
In the Proceedings of HyperText 2018. Canonical Version
Lan Nguyen, J David Smith, Jungmin Kang, My T. Thai Optimal Auditing on Smart-Grid Networks
In the Proceedings of ICC 2018. Canonical Version
Xiang Li, J David Smith, My T. Thai Adaptive Crawling with Multiple Bots: A Matroid Intersection Approach
In the Proceedings of INFOCOM 2018. Canonical Version
Alan Kuhnle, Xiang Li, J David Smith, My T. Thai Online Set Multicover Algorithms for Dynamic D2D Communications
In the Journal of Combinatorial Optimization (2017). Canonical Version
Xiang Li, J David Smith, My T. Thai Adaptive Reconnaissance Attacks with Near-Optimal Parallel Batching
In the Proceedings of ICDCS 2017. Canonical Version
Xiang Li, J David Smith, Thang Dinh, My T. Thai Why approximate when you can get the exact? Optimal Targeted Viral Marketing at Scale.
In the Proceedings of INFOCOM 2017. Canonical Version arXiv
Xiang Li, J David Smith, Thang Dinh, My T. Thai Privacy Issues in Light of Reconnaissance Attacks with Incomplete Information.
In the Proceedings of Web Intelligence 2016. Canonical Version