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In the Three Minute Thesis (3MT) competition, graduate students convey the essence and importance of their master’s thesis or doctoral dissertation research in an engaging way to a non-specialist audience in just three minutes using one static PowerPoint slide.
This research communication competition originally developed by The University of Queensland (UQ) in 2008. Over time the contest has exploded in popularity, and 3MT contests now occur worldwide at over 900 universities across more than 85 countries.
3MT is not an exercise in trivializing or ‘dumbing-down’ research but challenges students to consolidate their ideas and research discoveries so they can be presented concisely to a non-specialist audience. The challenge for participants is to take all the months spent on research and writing their thesis or dissertation and distill it down to a three-minute summary!
"A Digital Heartbeat: Looking for Ways to Avoid Bankruptcies”
by Stephen Bowman
Who here remembers Blockbuster? Toys “R” Us? Bed Bath & Beyond? What do these companies have in common? Each were giants that filed for bankruptcy. To the public, these bankruptcies seem sudden. But in my 20 years of television and feature productions, I’ve learned a universal truth: major illnesses rarely strike out of nowhere; they develop from small, invisible symptoms that go ignored.
If a corporation can’t detect the symptoms, they can’t treat the underlying condition. So, how do we find symptoms earlier? Traditional auditing can be like an autopsy. It tells you why the patient died, but it often comes too late to save them.
My research is a preventative checkup. I used machine learning to analyze financial data from 6,000 companies for over a decade. While human auditors can check 5 to 10 key indicators, my model scans nearly 100 indicators simultaneously to detect an irregular "digital heartbeat."
So, what did the computer model find? As you can see on this slide, the loudest warnings aren't necessarily about day-to-day profits. They’re about Structural Stability.
Our top indicator is Equity to Liability. It measures the company’s Net Worth against its obligations. It is the 'bones' of ownership, checking if they are strong enough to support the weight of the debt.
Right below that is Borrowing Dependency. This is the company's Oxygen. It determines how much a company relies on debt just to breathe. If a firm can't survive without a constant 'ventilator' of new loans, the heartbeat is already failing.
Finally, look at the bar all the way at the bottom: Net Income to Total Assets. This is the company’s Metabolism. Traditionally, investors obsess over profit. But my model discovered that while profit is a vital sign, it is actually a weaker predictor of survival than the structural stability at the top.
My model can listen to these heartbeats and predict a collapse up to two years in advance with over 82% balanced accuracy. In an industry where traditional methods often fail, correctly flagging 4 out of 5 high-risk firms is a massive leap forward.
In the end, Predictive Leadership is the answer. It means shifting from reacting to a crisis to preventing one, it’s fundamentally good risk management. We no longer need to wait for things to go wrong to know there’s a problem, because when we can hear the digital heartbeat, we don’t just predict failure—we create a chance to prevent it. Thank you.
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