About
Ilya Shabanov
Not your average academic. I spent 12 years in industry, co-founded a brain training startup NeuroNation, ran a web design firm, and travelled the world.
When I first had the idea of starting my PhD in Biology in 2021, I was 36 years old and more than a decade out of touch with academic work (I finished my MSc in 2010, when programming took years to learn, not 15 minutes of prompting).
Fair to say, I had a lot of doubt about whether this made any sense or whether I would even succeed. I just wanted to try it, as I almost studied Biology after school, but was put off by the pipetting as a youth.
A severe midlife crisis was probably to blame, too. (COVID hit my previous career as a globe-trotting freelance web designer pretty hard.)
A kind student advisor I spoke to back then recommended that I volunteer in a lab, and I reached out to every professor at the University of Arizona (where I lived at the time) and across the United States. Having no relevant expertise, few replied.
But I was lucky enough to find one person who gave me a big biology textbook and quite a few hours of his time. This was around April 2021.
To apply for a PhD in the US, you need to send out your application by late November. I had about 6 months to go from “I watched a few YouTube videos” to “I am doing a PhD”.
Being a computer scientist, I analysed the problem from an engineering standpoint: How do I store and access information effectively, and what solutions exist?
The two solutions I found were digital notes (oh, how messy they were back then…) and visual mind mapping with Draw.io. And, wow, did that make an impact!
Fun moments scanning and collecting plant samples for my PhD. Displayed are the leaves of one of the prettiest tree in New Zealand: Rewarewa.
Everything started moving fast after that – I got a grip on the subject matter and wrote a paper with my supervisor, which, thanks to him, went through peer review relatively smoothly and was published in Nature Scientific Reports. He also wrote me a glowing recommendation letter that opened the door to a few PhD programs in the US.
In the end, I couldn’t take any of these opportunities because my visa arrived just a few weeks too late.
So I shifted gears once again and came to New Zealand to do a PhD in Ecology.
Some delays in the starting date led to the founding of EffortlessAcademic in December 2022, which I maintained and grew during my PhD years.
Thanks to the information skills obtained previously I finished the PhD ~5 months ahead of time (~2.5 years) and had written 4 first-author papers in that time.
In that time, I have seen firsthand how broken some parts of the academic system are. Everyone knows about the overloaded peer-review system, but universities and libraries are also terribly bureaucratic and slow, students are simply not taught any “information handling” skills, and faculty often lack even the basic leadership training. All of that compounds into burnout and unnecessary suffering. At EA, I want to change that through teaching the skills that can remedy these shortcomings and developing software to make it easy.
What exactly is
Information Management
It all begins with a digital note-taking system. The software I am using is called Obsidian and it allows you to create a Wikipedia for your research. Just like on Wikipedia, every page is connected through links to other pages, in Obsidian, every note is connected to other notes.
The best part is that this also includes PDFs of papers or books. Your notes can link your directly into PDF annotations – a so-called deep-link.
Each note is essentially a collection of claims backed up by a paper and easily verified, thanks to the deep-links (see the screenshot).
All of that lives locally on your computer as a collection of text-based notes that Obsidian helps you organise.
This helped me create a repository with over 500,000 words spread across thousands of notes and PDFs. The Information Management Course introduces the key ideas for managing such a knowledge repository.
As you work with this information management system over months and years, it becomes an extension of your mind and contains every claim you ever found, every paper you have read, every question and idea you cared to write down.
And because all of it is digital, it is easily searchable and interconnected, just like Wikipedia but hand-crafted for your niche research domain.
Obsidian, as a software for organising ideas, is very flexible and offers over 3000 plugins to fit every workflow. With the introduction of AI, most of these workflows are now more efficient and easier to use.
For instance, AI can draft paragraphs based on your notes and sources, or synthesise ideas across years of thinking, generating new insights and “deeper” research. This only works because AI works on top of YOUR note-taking system and does not generate facts and ideas from the internet.
As these systems keep evolving, I keep experimenting and distilling what works for academics.