Category Archives: Dissertation

Phil 3.27.20

Working with Zach and Aaron on the app. I think we’ll have something by this weekend

  • Added a starting zero on the regression
  • Added the regression to the json file, and posted to see if Zach can reach
  • Set up the hooks for export to excel workbook, with one tab per active country. I’ll work on that later today – done! countries

Got clarification from Wayne on some edits. Going to turn those around this morning and try to submit before COB today. Maryland is at 580 confirmed cases as of yesterday. I’d expect to see nearly 800 when they update the site this morning. Sent over all the edits. It’s in!




ProQuest submission site.

Phil 3.25.20

Waking up to the news these days makes me want to stay in bed with the radio off

Working on automating the process of downloading the spreadsheet, parsing out the countries, and calculating daily rates. The goal is to have a website up this weekend so you can see how your country is doing.


  • Set up converter class – done
  • download spreadsheet – done
  • parse out countries – working on it
  • Made mockups of the mobile and webpage displays, and refined a few times based on comments

Got notes for Chapter 11 from Wayne. Switching gears and rolling that in. Put in changes for all the items I could read. There are a few still outstanding. I’ll submit tonight if Wayne doesn’t come back for a discussion.

Back to Docker. Need to connect to the WLS. Done!


  • AIMS – status for all, plus technichal glitches. We’ll try Teams next time. Vadim has made GREAT progress. We might be able to get a real Yaw Flip soon as well
  • A2P – Infor demo. Meh.

Stampede theory proposal deadline was delayed a couple of days

Phil 3.19.20

I found the data sources for the dashboard in the previous few posts. Yes, everything still looks grim:

So rather than working on my dissertation, I thought I’d take a look at the data for the last 9(!) days in Excel:

This is for the USA. The data is sorted based on the cumulative total of new cases confirmed. If you look at the chart on the right, everything is in line with a pandemic in exponential growth. However, that’s not the whole story.

I like to color code the cells in my spreadsheets because colors help me visualize patterns in the data that I wouldn’t otherwise see. And one of the things that really stands out here is the red rows with one yellow cell on the left. These are all cases where the rate of confirmed new cases dropped to zero overnight. And they’re not near each other. They are in WA, NY, and CA. Is this a measuring problem or is something going right in these places?

Maybe we’ll find out more in the next few days. Now that I know how to get the data, I can do some of my own visualizations that look for outliers. I can also train up some sequence-to-sequence ML models to extrapolate trends.

One more thing. I had heard earlier (Twitter, I think?) that Vietnam was handling the crisis well. And it looks like it was, but things are back to being bad:

Ok, back to work

8:00 – 4:30 ASRC PhD, GOES

  • Working on the process section – done!
  • Working on the TACJ bookend – done! Made a new figure:
  • Submitted to Wayne. Here’s hoping it doesn’t fall through the cracks
  • Neuroevolution of Self-Interpretable Agents
    • Inattentional blindness is the psychological phenomenon that causes one to miss things in plain sight. It is a consequence of the selective attention in perception that lets us remain focused on important parts of our world without distraction from irrelevant details. Motivated by selective attention, we study the properties of artificial agents that perceive the world through the lens of a self-attention bottleneck. By constraining access to only a small fraction of the visual input, we show that their policies are directly interpretable in pixel space. We find neuroevolution ideal for training self-attention architectures for vision-based reinforcement learning tasks, allowing us to incorporate modules that can include discrete, non-differentiable operations which are useful for our agent. We argue that self-attention has similar properties as indirect encoding, in the sense that large implicit weight matrices are generated from a small number of key-query parameters, thus enabling our agent to solve challenging vision based tasks with at least 1000x fewer parameters than existing methods. Since our agent attends to only task-critical visual hints, they are able to generalize to environments where task irrelevant elements are modified while conventional methods fail.

Phil 3.18.20

7:00 – 5:00 ASRC GOES

Today’s dashboard snapshot (more data here). My thoughts today are about supression and containment, which are laid out in the UK’s Imperial College COVID-19 report. The TL;DR is that suppression is the only strategy that doesn’t overwhelm healthcare. Suppression is fever clinics, contact tracing, and enforced isolation, away from all others (in China, this was special isolation clinics/dorms). This has clearly worked in China (and a town in Italy), though Hong Kong and Singapore seem to be succeeding in different (more cultural?) ways. The thing that strikes me is that suppression is just putting a lid on things. The moment the lid comes off, then infections start up again? I guess we’ll see over the next few months in China.

There appear to be vaccines in (human already!) testing. Normally, there is an extensive evaluation process to see if the treatment is dangerous, but that was sidestepped during the AIDS crisis (the parallel track policy). I wonder if at risk populations (People older than 70?), will allowed to use less-tested drugs. My guess is yes, probably within a month.

  • Finished all the dissertation revisions and made a document that contains only those revisions. Need to make a change tableand then send (full and revisions only) to Wayne today.
    • Whoops! No I didn’t. After putting together the change table, I realize there are still a few things to do. Dammit!
  • Update SDaaS paper as per John’s edits
  • Phone call with Darren at 2:00
    • Start a google doc that has all the parts of a proposal, plus a good introduction.
    • Also the idea of sims came up again as ways to define, explain, train ML, and test a problem/solutions
  • AIMS meeting at 3:00

Phil 3.17.20

7:00 – ASRC PhD/GOES

Today’s view of the dashboard. Looking at the numbers, it’s pretty clear that China has things under control, which means that we can get an idea of what it will look like in the US on the other side. The symptomatic population was (3,111 deaths + 55,987 recovered) = 59,098. That means that the mortality rate for that (infected? symptomatic?) population (59,098/3,111) is 5.26%. The median age in China is 38.4 years. Interestingly, that’s about the same as the USA.

So, if you know 20 people who come down with symptoms, it looks like one probably won’t make it? The CDC says that between 160 million and 214 million people in the United States could be infected over the course of the epidemic. So that works out to 8.5M – 11.2M fatalities? That seems really high. For a comparison, cancer and heart disease kill roughly 1.2M/year in the US.

In a fit of unbridled optimism, I’m booking vacation flights for September – done! Got to use my cancelled TF Dev tix

  • Ok, back to finishing the dissertation. Boy, it is hard to concentrate.
    • Conclusions are done
    • Working on tying things back to the literature

Phil 3.16.20

7:00 – 5:00 ASRC PhD/GOES

  • Working from home for the duration of the COVID-19 pandemic. It’s estimated that we are approximately 10 days behind Italy, So I’m hoping that when things start to get better there, it will be a head’s up that things might start to get better here.

(Via Corriere delle Sera)

  • Needless to say, things are not getting better there yet.
  • So, before the university gets to the point where it can’t handle the submission of the dissertation, I’m going to work on getting the revisions done and submitted.
    • Finished first pass through Limitations and Research chapter
    • Tried to start on fixing the conclusions but ran out of motivation
  • #COVID-10 meeting at noon –
    • Set up folders for lit, assets, software and data
    • Started a rough draft of the (chi 2021?) paper
  • Write BSO about moving Mahler to Bach/Radiohead – done
  • Started to work through the SDaaS paper with John D.
  • From models of galaxies to atoms, simple AI shortcuts speed up simulations by billions of times
    • Modeling immensely complex natural phenomena such as how subatomic particles interact or how atmospheric haze affects climate can take many hours on even the fastest supercomputers. Emulators, algorithms that quickly approximate these detailed simulations, offer a shortcut. Now, work posted online shows how artificial intelligence (AI) can easily produce accurate emulators that can accelerate simulations across all of science by billions of times.

John’s Hopkins gets dashboard of the day

Phil 3.13.20

7:30 – 7:00 ASRC PhD

  • 2:00 Meeting with Daren D? Nope
  • Working on revisions – Finished the limitations and research agenda chapter body! Now I need to add the overview and the summary. Then on to the revisit of my hut.

Phil 2.7.20

7:00 – 5:00 ASRC GOES


  •  Dissertation
    • Fixed some math
  •  Defense
    • Added a math slide for agent calculations – done
    • Need to add the sim justification slide, based on Aaron’s comments last night – done
    • Drop off signed papers at graduate school this morning – done
    • Working on the abstract – done and submitted!

Phil 2.5.20

7:00 – 5:30 ASRC GOES

  • Social network proximity predicts similar trajectories of psychological states: Evidence from multi-voxel spatiotemporal dynamics put this in the lit review!
    • Temporal trajectories of multivoxel patterns capture meaningful individual differences.

    • Inter-subject similarity in pattern trajectories predicts social network proximity.

    • Friends may be exceptionally similar in how attentional states evolve over time.

    • There are distinct behavioral effects of neural response pattern and magnitude trajectories.

  • Irrational Politics, Unreasonable Culture: Justin Smith and Jessica Riskin held on January 29, 2020
    • Shouting and shaming, lying and trolling: How did we ever learn to speak to one another the way we do now? In matters political and cultural, public and private, on social media and in major newsrooms, it seems as though over the past few years a bizarre and frightening irrationality has taken hold of our discourse. But what is irrationality, and what is that thing—reason—with which we oppose it? 
    • Jessica Riskin is involved in some cross-cultural project at Stanford that is trying to bring the arts and STEM into closer orbits (techies and fuzzies?)? Send an email
    • Justin Smith is interested on the effects of algorithms on thinking. Can’t find any writing, but he gave a talk: “The Algorithmic Production of Social Kinds,” a lecture-performance at DAU, Paris, February 12, 2019.
  • Dissertation
    • Slides
  • Mission drive meeting
    • Send status report to Erik
    • 3/31/20 milestones
      • Evaluate GOES 16 and 17 high-fidelity simulators as training sources for multivariate anomaly detection
        • Evaluate transfer learning from GOES 16 <-> GOES 17
      • Evaluate reaction wheel scenarios on lofi model as training source for multivariate anomaly detection for GOES 17 and GOES 17
        • Evaluate transfer learning between models trained using hifi simulator data

Phil 1.31.20

7:00 – 4:00 PhD

  • Dissertation. Here’s how to do a timeline ( Nope – this is horrible
  • Let’s try Python. Woohoo! It’s overkill, but looks great: Timeline
  • Here’s the code:
    import matplotlib.pyplot as plt
    import numpy as np
    from datetime import datetime
    names = ['Le Bon', 'Arendt', 'Martindale', 'Moscovici & Doise', 'Grunbaum',
             'Kauffman', 'Card & Pirolli', 'Bacharach', 'Olfati-Saber', 'Munson & Resnick', 'Stephens',
             'Galotti', 'Bastos']
    dates = ['1895', '1951', '1991', '1994', '1998', '1993', '1999', '2006', '2007', '2010', '2011', '2017', '2019']
    namedates = []
    for i in range(len(names)):
        namedates.append("{} ({})".format(names[i], dates[i]))
    # Convert date strings (e.g. 2014-10-18) to datetime
    dates = [datetime.strptime(d, "%Y") for d in dates]
    # Choose some nice levels
    levels = np.tile([-5, 5, -4, 4, -3, 3, -2, 2, -1, 1],
    # Create figure and plot a stem plot with the date
    fig, ax = plt.subplots(figsize=(8.8, 4), constrained_layout=True)
    markerline, stemline, baseline = ax.stem(dates, levels,
                                             linefmt="C3-", basefmt="k-",
    plt.setp(markerline, mec="k", mfc="w", zorder=3)
    # Shift the markers to the baseline by replacing the y-data by zeros.
    # annotate lines
    vert = np.array(['top', 'bottom'])[(levels > 0).astype(int)]
    for d, l, r, va in zip(dates, levels, namedates, vert):
        ax.annotate(r, xy=(d, l), xytext=(-3, np.sign(l)*3),
                    textcoords="offset points", va=va, ha="right")
    # remove y axis and spines
    for spine in ["left", "top", "right"]:
    plt.subplots_adjust(left=0.1, right= 0.9)
  • PhD Day


Phil 1.30.20

7:00 – 5:00 ASRC GOES

  • Antonio created an Overleaf project for ACSOS. Fixed the widthg of all the figures. Need to fix the tables and equations
  •  Dissertation
    • Fix the > \pagewidth equations
    • Slides
    • Get the timeline prev work slide updated for Kauffman, Martindale, and Bacharach (how did I do number lines?
  • Add December to status and send to T
  • Finish slide deck and paperwork for GSAW – done, I think
  • Meetings at NSOF
    • 1:30 Isaac
      • More discussion about simulators. We’re going to try running multiple sims this weekend with all even number wheels degraded at 20%, 40%, 60%, and 80% and compare them to 100%
      • In future, set up synchronized tasks so we can run more often and iterate across all wheels
      • Reviewed slides. Making small fixes
    • 2:00 regular status

Phil 1.29.20

7:00 – 8:00 ASRC GOES

  • The Office of Inspector General conducted a review of the Chicago Police Department’s risk models known as the Strategic Subject List and Crime and Victimization Risk Model. CPD received $3.8 million in federal grants to develop these models, which were designed to predict the likelihood an individual would become a “party to violence”, i.e. the victim or offender in a shooting. The results of SSL were know n as “risk scores” while CVRM produced “risk tiers.” In August 2079, CPD informed OIG that it intended to decommission its PTV risk model program and did so on November l, 2079. The purpose of this advisory is to assess lessons learned and provide recommendations for future implementation of PTV risk models.
  • In “Towards a Human-like Open-Domain Chatbot”, we present Meena, a 2.6 billion parameter end-to-end trained neural conversational model. We show that Meena can conduct conversations that are more sensible and specific than existing state-of-the-art chatbots. (Google blog post)
  • Defense
    • Slides – started lit review
    • Drop off dissertation with Wayne
  • GSAW
    • Tweak slides – trying to get a good AIMS overview slide so I can
    • Walkthrough with T
    • Paperwork
  • GOES Meetings
    • Influx DB (Influx 2.0) is a high-performance data store written specifically for time series data. It allows for high throughput ingest, compression and real-time querying. InfluxDB is written entirely in Go and compiles into a single binary with no external dependencies. It provides write and query capabilities with a command-line interface, a built-in HTTP API, a set of client libraries (e.g., Go, Java, and JavaScript) and plugins for common data formats such as Telegraf, Graphite, Collectd and OpenTSDB. 
    • The plan is to have the sim place data from the sim into the Influx DB and have the dashboard display the plots
    • This will generate data: file:///D:/GOES/AIMS4_UI_Mock/3satellite-instrument-analysis.html?page=reportpage&channel=5&status=error, once the demo is unzipped into D:/GOES
  • Meeting with Wayne
    • Dropped off the dissertation
    • Got the reader form signed. Just needs Shimei and Aaron
    • Discussed slides. Can skim the parts that would be review from the proposal and status (but put a slide that says this)
    • Feb 10 as walkthrough? 6:00?

Phil 1.28.20

Make appt. to pick up Dad on Friday after PhD day – done

  • 655 West Baltimore St, Baltimore 21201

protest_mapThis Interactive Guide to Protest Campaigns around the World uses data on all violent and nonviolent campaigns around the world with maximalist claims from 1945–2014 and is based on the NAVCO 1.2 database, recently released by Erica Chenoweth and Christopher Wiley Shay. The data extend on the NAVCO data project, which you can read about (and download) at the project’s Dataverse.

Here’s a bird’s eye view of six state-backed information operations on Twitter, and how they evolved over the last decade. This research was funded by the Mozilla Foundation by an Open Source Support Award.

7:00 – 5:00 ASRC GOES

  • Defense
    • More slides
    • Picked up printed versions and dropped off copies with Shimei, Aaron, and Thom
  • GSAW
    • Change intro slide on GSAW to triangle of data, accuracy, and reliability – done
    • Reworked and tweaked. Walkthrough with T tomorrow.