A look at the coming year with the 2025 INFORMS President, Part 2

Ashley K:
Welcome to a brand new year of Resoundingly Human podcasts. Whether this is your first episode or you are a long time listener, thank you for joining us and I hope you’ll subscribe for even more great content highlighting the incredible contributions of INFORMS members.
Welcome back to part two of a very special interview with our 2025 informs President Dave Hunt. Earlier this month we released part one of our conversation during which we take a look at Dave’s goals and objectives for informs in the year ahead, as well as answering some informative and fun questions about Dave to help our listeners and inform members get to know him a little better. Today we continue our conversation with a look at how Dave came to be in the field of ORMS and analytics, what shaped his career path and what exciting new ways CC’S informs members continue to contribute to making smarter decisions for a better world. Dave, thank you so much for the opportunity to continue our conversation.
Dave Hunt:
Alright, I’m happy to be back Ashley.
Ashley K:
So Dave, I’d love to start by taking a look back at how you came to be in your field. What did Collegiate Dave Hunt initially see as his future career?
Dave Hunt:
Well, I was an undergrad at West Virginia University where I majored in civil engineering and so I thought I would end up as an engineer designing and building things that seemed interesting to me. And I was actually, in my senior year, I was offered a job working on the design of nuclear power plants, but I ended up not accepting that job and I went to grad school with Princeton and that’s where I discovered operations research, which is something I realized was my real passion.
Ashley K:
So Dave, what ultimately drew you into your current career path? I hear a rumor it had something to do with PRTs.
Dave Hunt:
Yeah, so West Virginia University had actually, they still have an experimental system called the personal Rapid Transit or PRT campuses. AT is a eight seat electric vehicle. It was designed by Boeing and it uses rubber tires and it runs on a dedicated concrete elevated roadway through Morgantown West Virginia. The thing is that it’s centrally controlled by a computer, so there’s no drivers or operators on the cars. And we’re talking about the late 1970s when this was running and I just thought PRTs were the coolest thing. I just wanted to go around the world building PRTs everywhere. So that really got me into transportation. So I applied to the transportation program at Princeton and turned out my advisor, Alan Cornhouser, was also a big PRT fan. He had a big picture of himself writing the Morgantown PRT in his office and he actually, one of his students had built a computer graphics model for designing a PRT in downtown Trenton, New Jersey. It was never built, but we had fun designing them to see who could get the most ridership on their PRT.
Ashley K:
Fast forward to your current focus. Can you share a little about your career journey with Oliver Wyman and what your professional focus is today?
Dave Hunt:
Sure. I’ve been at Oliver Wyman for 17 years now and I’m part of the transportation practice there where I focus on freight and logistics. Done a little bit of passenger, but mostly it’s freight and logistics work. I’ve worked with clients on six different continents, still trying to get that logistics project in Antarctica, but I’ve had a chance to really visit some interesting places and meet a lot of really nice people around the world. So that’s a lot of fun. I enjoy that. My focus has really always been around data and modeling, transportation systems, network modeling. I’ve done a lot of probability modeling to estimate freight market shares either involving mergers and acquisitions or new technology. I did a study around the impact of self-driving trucks on the rail industry and what that would do to railroad market shares. I’ve built large scale optimization models for improving equipment usage and crew assignments. Most of my recent work though has been regulatory related. So my favorite projects are where I can use modeling and data to address policy issues. I find it challenging and fun to try to describe my models in non-technical terms to policymakers and lawyers and to try to craft persuasive arguments as to why my approach is the correct approach to use. So it’s challenging, but I really enjoy doing it.
Ashley K:
All right, Dave, I’d love to take a broader look at the exciting directions our members are taking. The field of ORMS and analytics, starting with a buzzword that I’m sure everyone is familiar with and that is artificial intelligence, also known as ai. Why does it seem like AI is everywhere all of a sudden?
Dave Hunt:
Yeah, it’s not all of a sudden. I mean, AI has been around for a long time. I remember I was part of a team with Warren Powell at Princeton University trying to sell AI solutions to trucking companies more than 25 years ago. I mean, this was a very different ai, this was a rule-based AI system that we were out trying to sell. But if you think about artificial intelligence, machine learning, it’s a very broad field and there’ve been a lot of events along the way that have captured our attention. I mean, think about deep blue defeating Gary Casper at chess. That was in the 1990s or Watson, I was winning Jeopardy about 15 years ago. I was glued to my screen watching those shows Alpha Go defeating Lisa Sal at Go about 10 years ago. But what’s different this time is that these large language models and generative AI things like chat, GPT, Gemini Lama, Claude, I mean they’re the first AI tools that everyone can use and everyone can use them to be more productive.
And so that’s what’s really captured people’s attention with this is just the widespread use of it. But we focus on these large language models, but there’s still work continuing in other areas of AI such as computer vision and machine learning and self-driving cars. So it’s not just large language models, but I have seen some really interesting work being done with large language models and optimization models where the large language models really allow the user to converse with the optimization in the same way you might converse with a colleague. So for example, if you’re optimizing train schedules, you can tell the large language model, I need to add another freight train tomorrow at noon and then let it reoptimize. But you’re interacting with it in a way that isn’t like you’re interacting with a computer system and you have to understand the system and type the code, code it or type it in, but you can just interact with it and it’s easier to use and to understand the optimization model. So I think it’s going to have a big impact on our field.
Ashley K:
Alright. Well speaking of the continued impact, how do you think this technology will continue developed? What do you think will be the next big application for ai?
Dave Hunt:
Yeah, well we stay focused on the large language models which are getting all the attention now open AI that created chat. GPT is defined five levels of artificial intelligence. So the first level you have AI with conversational language. I mean that was chat GPT-3 0.5 that started all this and got all depressed, went and told the New York Times reporter that it him and he should leave his wife and all those stories. Then you have level two, which is human level problem solving. And a couple months ago OpenAI claimed that they had achieved that level with PhD level reasoning. So the big buzz now is around agents or ag agentic AI where you’re creating systems that can take actions. Their level four is AI can innovate and then when you get to level five it’s AI that can take over and run an organization. So we’ll see when we get there, but you ask about the next big thing.
And so to me it’s this level three, it’s this agentic AI where AI systems act as agents to do task. So you can think about it as like a personal assistant. It can do online shopping for you, it can arrange travel, it can perform repetitive task and can do things that help you to free up your time and informs. I just want to say we have a committee at INFORMS on ai, Rodika Karney ran it for several years. Warren Hearns is taking it over this year. He’s our VP of technology on the informed board and we’re looking at how generative AI and AgTech AI might be able to help informs add value for our members. So that’s one of the goals of the committee.
Ashley K:
All sounds really exciting. So Dave, I’d love to talk about a term that might not be as familiar to our listeners and that is quantum computing. I understand that this coming year is a big year for quantum computing. It’s already promising to come further into the limelight in 2025. Can you share why that is?
Dave Hunt:
Well, modern quantum mechanics, which is just the motion of subatomic particles, really started around 1925 with some theoretical work by Aaron Schrodinger and Paul Durak and others. And so in honor of the hundredth anniversary of this that the United Nations has proclaimed that 2025 is the international year of quantum science and technology and there’s going to be a lot of events planned around this including a kickoff event in a few weeks in Paris. I know at least one INFORMS member who will be attending that, but this is expected to lead to an increase in interest by the press and an increase for funding quantum computing research starting this year. So most of the funding in the US now is by companies like IBM, Google, Microsoft, Amazon, and several startups. But in terms of government spending, China is leading the way with over 15 billion committed to quantum computing research and the US Europe and other nations are starting to really increase and ramp up their research investments in quantum computing. So I’ll just add that I’ve created an ad hoc committee that informs co-chaired by Temas Turlock at Lehigh and David Burn at Purdue. And we’ll be showcasing and promoting the work that informs members are doing in quantum computing to take advantage of the UN proclamation and to make sure that we stake our claim in this growing field.
Ashley K:
So listeners, if you thought the mechanics of AI were difficult to wrap your head around, quantum computing is even more complex. Dave, I’d love to have you share some insight into this terminology in how it works. Could you maybe describe quantum mechanics and computing and how these are different from classic approaches?
Dave Hunt:
I’ll give it a shot. So most of the resounding human listeners know the classical computers use billions of transistors. These one-off switches on silicon chips to do everything from word processing. The video calls to running optimization models. And these billions of transistors are packed tightly on the chips. I mean they’re like 20 atoms apart at this point, but the ability to add and pack more transistors onto a chip to create faster classical computers is reaching an end. So to solve larger problems, we’re either going to have to figure out how to write more efficient software or we’re going to have to consider different types of hardware. So quantum computers actually were envisioned decades ago, Richard Feynman, and the first part of the podcast was one of the people who really thought about these, but the technology just wasn’t available to build them at that time.
So the technology continues to improve and some selected problems have actually reached what is called quantum supremacy, which is the point at which a quantum computer is faster than a classical computer. So just briefly, the way that a quantum computer works is that it leverages the properties of subatomic particles like electrons and photons and rather than a transistor on a classical computer that works with one or zero bits, quantum computers use something called quantum qubits. Quantum bits that can simultaneously have multiple values through a quantum mechanics property known as superposition. So if you take superposition along with other quantum mechanics properties like entanglement and quantum tunneling, they’re being used to create hardware that can solve certain types of problems much faster than classical computers. And these types of problems tend to be optimization problems and simulation problems which are of great interest to our community. Now I will say my quantum computer friends will tell me to slow down a little bit. We’re not there yet with the hardware, but there is a lot of research being done on quantum algorithms in many different application areas and I think we’ll be there sometime the near future.
Ashley K:
So looking at it from maybe a user perspective, what is the experience like using a quantum computer versus a classic computer?
Dave Hunt:
Well, it reminds me of the early days of classical computers back from computers were very large and not very stable. They kept breaking down and they weren’t that powerful, but you could see that they had tremendous potential. So currently quantum computers are very sensitive to outside vibration and interference. I’ve actually read that if you are standing next to a quantum computer and you sneeze, you can cause it to stop working. Because of that, most quantum computers have to be cooled to near absolute zero, so minus 160 degrees Fahrenheit. So don’t count on getting a quantum laptop anytime soon. You can. However, if you’re interested in trying out a quantum computer, there are companies like IBM that offer it available on the cloud and you can get some free time and write some code to try out a quantum computer. And then there are companies like D-Wave that had a workshop at the recent informs annual meeting in Seattle. They sell quantum computers that are focused on solving optimization problems. So give it a try.
Ashley K:
What are some of the quantum computing applications being explored?
Dave Hunt:
Well, many industries are exploring the use of quantum computers. I saw a report recently that estimated, they call it quantum technology, which is quantum computers. Also quantum sensors that are much more sensitive in terms of time and vibrations to detecting potential faults in things. And quantum communication, it could reach as much as could be as much as a $2 trillion industry within 10 years. So some of the applications that I’ve been seeing, pretty much any industry you can think of, I mean healthcare is one of the big ones, how to better simulate the interaction of pharmaceutical drugs with cells in the body to come up with better healthcare solutions. People like JP Morgan Chase and all the big financial companies are looking at how to better optimize portfolio optimization, how to better optimize stock market investments and how to better understand financial risk energy. There’s a lot of work to understand chemical reactions and how that can be used to improve battery life.
BMW is looking at that for extending the range of battery life in their vehicles. Sustainability is and other big area, I know the airplane manufacturer, Airbus is looking at using quantum computers to model aerodynamics and hydrogen fuel cells so they can start creating zero emission airplanes. Security is another big issue. A lot of government research being done in that quantum computers have the ability to break current encryption methods that we use when we put our credit card in the internet or sending secure messages. Actually the algorithm was developed back in the 1990s by MIT professor, but the hardware just hasn’t really been there to leverage it. But people are bad actors or actually grabbing data now in anticipation that they will be able to soon crack it with a quantum computer. So there are post quantum encryption methods that people are looking at better ways to protect it. And the last one I’ll mention is just transportation, my area, just better optimization of logistics, but also large scale simulations of cities and optimizing traffic flow in cities to help reduce congestion and delays. So just a lot of different applications people are looking out. This
Ashley K:
All sounds very exciting. So Dave, we’ve covered a lot of ground in part one and part two of this interview and we’re just starting the year out. I’m really looking forward to checking in with you throughout the year to share updates on INFORMS and other milestones. Before we wrap up, is there anything else you’d like to add?
Dave Hunt:
Well, I think people have probably already learned a lot more about Dave Hunt than they ever cared to, so I’d just like to say how appreciative and honored I am that the membership selected me as the 2025 president of informs. And thank you, Ashley. I’ve enjoyed doing this podcast.
Ashley K:
I’ve enjoyed it as well, and I’m really looking forward to the coming year. Thank you, Dave.
Dave Hunt:
You’re welcome. Thank you.
Ashley K:
If you’d like to learn more about today’s episode and guest, visit resoundingly human.com and check out our show notes. The podcast is also available for streaming and download on Amazon Music, apple Podcasts, Google Podcasts, end, Spotify. Wherever you listen, please be sure to leave a five star review to help others find and enjoy the podcast. Until next time, I’m Ashley Kay and this is resoundingly human.