Interviewing Prof. Bertsimas from MIT: Teaching our methods and successes can make a huge difference

His enthusiasm is palpable, even though we’re only meeting online. Asked after his passions, Dimitris Bertsimas sums them up without hesitation: “Being an advisor to my doctoral students – 81 so far, and 25 students at the moment – education and research, and starting companies, particularly in areas where I can help the world.”

Immediate effect on the world

Back in 2001, Bertsimas took the first opportunity he saw in this respect and started a company in applying analytics. Using claims data, it developed models that predicted costs and quality of healthcare for patients. It is rather typical that his first endeavor took place in the field of medicine, since medicine has remained a passion of his to this day. “In 2007, my father was diagnosed with gastric cancer; I was very involved in his care. Unfortu­nately, he passed away in March 2009. A few months later, my mother passed away. When you’re the one in the family who’s next in line for death, you start reconsidering your life. I resigned from the financial company I was working for at the time and decided to devote the rest of my career to things that have an immediate effect on the world, preferably on a large number of people.” Analytics for a Better World (ABW) is a direct result of this aspiration. To Bertsimas, it’s clear where analytics can add the most value. “Definitely the environment. In a world dealing with unprecedent climate change, it’s very important to deliver accurate predictions. Personally, I’m involved in a project predicting hurricanes – a big issue in global warming. The damage inflicted by a hurricane nowadays is a big multiple of what it was twenty years ago. We’ve achieved promising results with machine learning methods instead of physical models. If you combine computer vision with the new technologies we have today, you can outperform classical methods. It’s all still very academic, but we’re very close to be applying our models in practice.”

In a world dealing with unprecedented climate change, it’s very important to deliver accurate predictions.

Scalable solutions

Bertsimas believes that we can harness machine learning and analytics to help achieve all SDGs. “Take poverty and hunger, for instance. Using data to develop even simple models can make a material difference between life and death. You can significantly increase the number of people who can avoid hunger and potential death. Analytics are descriptive, predictive, and prescriptive. The descriptive part – understanding what the issues are, having the data – is not usually associated with highly academic work, but it is incredibly useful. What’s even more useful is a scalable solution. If you look at the academic world: they produce papers. They don’t produce software or implementations. And you can only conduct new research with students once. But even if studies turn out to be extremely useful, the major motivation for implementation in all areas of science is profit. How does a study materially affect the world? When the target is an underprivileged environment, implementation is even less common. I have focused on changing this. Whenever I had an idea that was promising in initial implementations and I thought would benefit the world, I started start a company. That’s why I call myself a serial entrepreneur.”

The art of the feasible

The ABW institute is an opportunity to bridge the gap between the outputs of academia and the real world, says Bertsimas. “But it will need to be a sustainable organization of its own. It has to maintain a level of standing to distinguish itself from significant organizations in the world. Attracting talented young people is a challenge we will have to tackle. We teach a course, which we also called ABW, and a lot of students are very excited about the initiative. But then life happens: they buy a house, have a family, and need to pay their bills. The organizations ABW wants to help are typically not well-funded, so there is a compensation gap with the commercial sector. Plus, a lot of humanitarian organizations don’t even have basic data. At ABW, we believe we can help with their ‘datafication’, increasing their data and data quality. NGOs have very good objectives, but they don’t have data expertise. Part of what we do is educate. I recently gave a series of lectures on analytics in healthcare to about 100 senior physicians, senior nurses, and senior administrators in a major hospital system, which has led to a veritable explosion of projects in their hospitals. Did they understand everything I said? No. But they understood the art of the feasible. Educating NGOs and their people on the art of the feasible will go a long way in enhancing ABW’s influence in the world. I recom­mend teaching our methods, our successes. Education can make a huge difference.”

Attracting talented young people is a challenge we will have to tackle.

Read some of Dimitris’ impact stories below: