The Great Balancing Act

13 September 2014

There are several methods for reading papers. There is the “read-on-a-laptop” method, which gives a good idea of what is going on, and then there is the “print-the-paper-and-spend-6-hours-going-through-it-word-by-word” method. The second method seems to inevitably require referencing textbooks to look up the derivation of key concepts. Frequently, it also requires constructing a dependency graph based upon the paper’s citations, such that to truly understand one paper, one has to read 10 others.

The same can be said of anything, really. Doing something right requires a huge dedication of time. And therein lies the problem.

I have never really learned how to balance my time - if I focus on classes, then I spend my waking hours immersed in the class materials, searching the internet and textbooks for supplemental content. If I have a personal project, I disappear from civilization for weeks, skipping classes and assignments. When I get to certain parts of my research projects, I forget that the sun exists, and my sleep schedule rotates around the clock as I come home from the office later and later each day (…just let me finish this one last thing!).

Such a mindset is great when all I have in my life is research, or classes. It becomes less so with several things competing for my attention. It becomes horrible once deadlines get involved (my undergraduate transcript can attest to that).

A couple of days ago, I realized that I was spending all of my time on homework and obligations. Classes are important to me now, especially since I have switched disciplines from Physics to Machine Learning. Ultimately, though, it is not classes that truly excite me. I am here to do research!

I found myself falling extremely quickly into a “deadline-chasing” mindset - working on assignment after assignment, going through one thing on my to-do list after another, focusing only on the short-term, but fixed due-dates.

It is clear to me that this is not the optimal way to go about spending my time. There exists a point at which long-term goals without fixed and recurring deadlines (like research) trump the circle of recurring “things-I-should-do”. I have already learned the hard way that I can’t just ignore my duties at any time, but on the other hand, there will always be something waiting to be done. So how do I fulfill my duties adequately, while still dedicating time to long-term goals?

My claim is that there exists an “optimal schedule” of work. There exists a balance for each person - an optimization point where duties are fulfilled, but time spent on the “important things” is maximized.

Such a schedule is not easy to calculate. Perhaps it takes 3 hours to shift attention from one subject to another. Perhaps it is best to take care of light duties right after eating, or attack the difficult problems after midnight? And maybe not starting the day off with something intellectually stimulating leads to motivational difficulties for the rest of the day? Perhaps leaving an assignment unfinished until near a deadline allows me to work with much greater efficiency? Or maybe it is the opposite? And what about sleep? Will a nap during the day to allow greater focus in the afternoon? How will it affect my efficiency the next day? What about tuning motivation? Perhaps it is best to intersperse the hard stuff with the simple things, such that I get some motivation from feeling that I am getting somewhere?

How exactly do I schedule things around my deadlines to both maximize my efficiency, and fit as much research and papers/books in as possible?

All of these are extremely difficult questions to answer. But answering them in a rigorous, data-driven way promises a pathway to immense efficiency.


Over the summer I created a simple web-app called “meDB”, which I have been using for the past few months to gather data about myself, such as the amount of sleep I am getting, when, and what I eat, and how much time is spent on specific tasks, along with subjective ratings such as my mood and progress towards goals. The goal of the app was to find specific correlations in the data - how much does sleep affect my performance? Does eating fatty food lower my mood? How long will the effects of an all-nighter last?

I have recently been thinking that it might be a good idea to spend some of my (yet to be found) time in attempting to create a scheduling algorithm which uses this data to optimize both my well-being, and the amount of things I can accomplish.

Sounds like the perfect use case for some machine learning!

For the forseeable future, I still need to learn how to balance my obligations manually… So inefficient.

But what can ya do ¯\_(ツ)_/¯

Might as well get started.