Fred Higgs is John and Ann Doerr Professor of Mechanical Engineering at Rice University, where he is also vice provost for academic affairs and director of the Rice Center for Engineering Leadership. A past winner of a National Science Foundation CAREER Young Investigator Award and a fellow of the American Society of Mechanical Engineers, Fred is the founder and director of the Particle Flow and Tribology Lab at Rice.
We would try to define what tribology is, but Ted, our host, kind of got it wrong in the interview, and there’s no need to embarrass ourselves twice. The good news is Fred is awesome at explaining things in terms even a non-engineer can understand.
Back in March, we had the opportunity to watch him give an Edison Lecture hosted by Notre Dame’s College of Engineering—and held virtually, of course—about some of the research they do in his lab in the area of additive manufacturing, or 3D printing. Here he and Ted talked about how 3D printing actually works, some real-world applications that illustrate why you’d do it in the first place, and whether we’ll ever be able to print three-dimensional objects as easily as we use a Xerox machine.
Before that, though, they spent some time on the rise of intelligent machines and the ensuing paradigm shift for engineers looking to bring products to market. It’s a great example of why Fred and others see ethics as a core component of engineering education.
LINK
- Fred’s Research: Particle Flow & Tribology Lab at Rice University
Episode Transcript
*Note: We do our best to make these transcripts as accurate as we can. That said, if you want to quote from one of our episodes, particularly the words of our guests, please listen to the audio whenever possible. Thanks.
Ted Fox 0:00
(voiceover) From the University of Notre Dame, this is With a Side of Knowledge. I'm your host, Ted Fox. Before the pandemic, we were the show that invited scholars, makers, and professionals out to brunch for informal conversations about their work. And we look forward to being that show again one day. But for now, we're recording remotely to maintain physical distancing. If you like what you hear, you can leave us a rating on Apple Podcasts or wherever you're listening. Thanks for stopping by.
Fred Higgs is John and Ann Doerr Professor of Mechanical Engineering at Rice University, where he is also vice provost for academic affairs and director of the Rice Center for Engineering Leadership. A past winner of a National Science Foundation CAREER Young Investigator Award and a fellow of the American Society of Mechanical Engineers, Fred is the founder and director of the Particle Flow and Tribology Lab at Rice. I would try to define what tribology is, but I kind of got it wrong in the interview, and there's no need to embarrass myself twice. The good news is Fred is awesome at explaining things in terms even a non-engineer like me can understand. Back in March, I had the opportunity to watch him give an Edison Lecture hosted by Notre Dame's College of Engineering--and held virtually, of course--about some of the research they do in his lab in the area of additive manufacturing, or 3D printing. Here, we talked about how 3D printing actually works, some real-world applications that illustrate why you do it in the first place, and whether we'll ever be able to print three-dimensional objects as easily as we use a Xerox machine. Before that, though, we spent some time on the rise of intelligent machines and the ensuing paradigm shift for engineers looking to bring products to market. It's a great example of why Fred and others see ethics as a core component of engineering education. (end voiceover)
Fred Higgs, welcome to With a Side of Knowledge.
Fred Higgs 2:05
Thank you, I'm glad to be here, Ted. Thanks for inviting me.
Ted Fox 2:09
So the Edison Lecture that you recently delivered to Notre Dame's College of Engineering, which was the first opportunity I had to learn a little bit about your work, it was titled "Industry 4.0 Design for Additive Manufacturing in Energy and Bioengineering Systems." And I wanted to start by asking you about two of the terms used there. What do we mean when we talk about Industry 4.0? And maybe even before that, what are industries 1, 2, and 3 that led up to Industry 4.0?
Fred Higgs 2:40
Oh, that's a great question. So I'm just going to jump right into the industry part. Industry 1.0 or 2.0 or Industry X is essentially talking about the Industrial Revolution. So the first Industrial Revolution was we went from kind of an agrarian society worldwide to one that was mechanized with steam-powered and water-powered engines then. So now, things move faster because you had a single machine. Well, in Industrial 2.0, you kind of assembled the machines together in assembly lines. And now you have, like, the Model T assembly line to make an automobile. In Industry 3.0, you started having softwares that could control these machines, and so you were able to optimize a little bit better and make production a little more automated than just kind of single-machine controls. We're now in Industry 4.0, which we're in now and progressively moving into--the machines themselves can have sensors on them so they can sense their environment. You also have the cloud, which is kind of a data repository somewhere else, where you can send data to that. And if you have an algorithm on the cloud that tells that data what to do, you could send it back to those machines, which from Industry 3.0 were already controllable by data, but now they have sensors and ports to take in that base data; they can take that data back and react to things. So now all of a sudden, you have a machine that's intelligent, that can sense its environment and react to things based off of what happens to it.
So for example, in Industry 4.0, you might think of a coffee maker that has a sensor on it. And all the coffee makers that are in Houston or in South Bend, Indiana, that are this particular type are taking in data, and they're seeing that, Wait a minute, nobody's using our coffee maker outside of 8 a.m. to 10 a.m, so let's go into energy saving mode and shut all of them down at that time there. So because it senses what's going on with its environment and the data is coming out, you can make a decision in the cloud, usually through an algorithm, right, automatically, and send that back, and now the machines are smarter there. So all of a sudden the machines become distinct entities that can sense their environment, and a brain outside of themselves somewhere in the cloud can tell them how to make a better decision in the way in which you're being used. That is Industry 4.0. So it's the merger of the physical and the digital systems offered through cyber connections.
Ted Fox 5:48
And is it one and the same or similar to what we're talking about when we talk about the Internet of Things? Basically these physical machines that are--they're no longer just physical things that we act on, but they can actually make decisions or optimize themselves?
Fred Higgs 6:05
Yes. That's a very good point. The Internet of Things is certainly a large part of this. Because you're right: The Internet of Things will basically say that the internet is made of these things that have--they have a distinct identity on the internet. So like a sensor that sits there, and this would be, say, if you've gone to a Home Depot or Lowe's, you see these kind of expensive smart bulbs. And it seems ridiculous. But wait a minute: So that single bug has an IP address that I could access? (Ted laughs) Oh, so now my phone could access it, and turn it on and off. That's ridiculous inside Lowe's; it's really brilliant when you're laying on the bed and don't want to get up to turn off the light. (Ted laughs)
But you're right. So it's these things that are on the internet. Industry 4.0 is that, but it's a bit broader because you're thinking of the entire way in which people work and live, and how products are produced and consumed. So you think of, like, a factory that has these machines. And there are things that are on the internet. But then with that paradigm shift in how these machines are connected, how they can sense and how they can make decisions through their data, now what ways should you change things? So for example, you know, I lead the Rice Center for Engineering Leadership. And, you know, it's about creating, producing leaders of engineering technology; in other words, leaders that can lead other teams of engineers. Right now the paradigm under which I've been trained as an engineer is that we optimize to try to get the product performing really well through models and things like that, and then once it's at its best, now you deploy it, you deploy a nice, robust, long-lasting technology. But in the Industry 4.0 period, if that product can sense in the field, Wait a minute, there's a lot of things I can learn from the customer and their use of that product. So why am I rushing to put that product--I'm sorry, why am I taking my time to put that product out there? I need to get it out there fast. As a matter of fact, I need to get the minimum viable product that we can make, get it out there fast. We learn from the data, all of us engineers are sitting in the room learning, the marketing people can learn from the data that's coming back from them, and then we iterate, improve that, and then we deliver the next one.
The other way you could look at it is Tesla had a machine that you purchased on day one, several years ago, and then on day 1000, you got a note saying, Bing!--Your car is now autonomous. Wait, what? (Ted laughs) Yeah, it's autonomous now. What? What're you talking about? I didn't drive it anywhere, I didn't, what do you mean?
Ted Fox 9:10
(laughing) Right.
Fred Higgs 9:10
They made the machine to have more functionality than you could currently use as a customer when they sold it to you. But it was interacting with the processor in the cloud somewhere, and so it learned from that data. And they were somewhere in a research lab developing new technology. And since the engine can be controlled by data, it just got new data saying, Look, here's a new algorithm, this is how you could react to things. So why do I mention that it makes a mechanical engineer a little scared? Because it suggests that, number one, software is potentially eating the world; software in the cloud is potentially eating the world because now they just come to me as a mechanical engineer once, and they say, Hey, we need an engine, and we need to be able to vary it at any speed, vary the gas levels, make everything as variable as possible, and then we're gonna put a control system on it. And I'm saying, Wait, but you're going to come back to me for the next generation? No, we won't. This thing can do everything. We're going to learn from it, and the data is going to create new algorithms. And then we're going to upload that back to the machine. We don't need you for a long while. (Ted laughs) And that's the potential.
Ted Fox 10:36
And I was gonna ask this--and I still want to get into additive manufacturing, what that is, but I was gonna ask this in the context of that, but it seems appropriate here. I imagine there's a lot of ethical questions that--I mean, you're talking about job security for a mechanical engineer, but there's also kind of that ethical piece of where do we need the human beings involved? And how much control should we cede over to the machines? I mean, is that kind of a moving target and ongoing conversation about where that line is?
Fred Higgs 11:08
That's a great point. In the Rice Center for Engineering Leadership, we talk about looking at ethics as a constraint on design--technical, ethical education. So effectively, you can design a system, but you have to think, Okay, one of my constraints is the weight ratio, or the thrust-to-weight ratio; say, I'm doing something that's going to go to space. But also, ethics is a constraint--[for example], it must not give off this much greenhouse gas emissions. We want engineers to start to think during the design process, Where does ethics come into play? Now, one of the things about all this data coming back is that you're not going to be able to interpret it. So that coffee machine that's giving you all this data, if you have a million customers using it across the United States in different ways, a human doesn't know what to do with that. And so you need to have smart what I call interpreters of that data to tell you what's going on. That's why something like artificial intelligence, where it comes into play, because it can take this data, cluster it--depends on which type of learning you're looking at--and then all of a sudden, it can make these wide decisions there.
In doing that, you're right, a human's not in the loop as we have historically been. So as a result, it may say, Hey, optimizing means the hood--that's what I'm calling a depressed socioeconomic environment--the hood is not making any money off of these machines. So let's have not-so-great performance in a certain part; we're not seeing their usage as good for this particular product. So all of a sudden, that particular neighborhood stops buying. It's made an unethical decision, the algorithm that created a racial bias there. So we're talking a lot about this. I just had a meeting yesterday with one of my colleagues here at Rice, Professor Moshe Vardi in computer science, and he along with another postdoc whose kind of an emphasis [on this] created a course in the computer science department. And it looks at designing these problems that inherently can spiral in an unethical direction, and they're challenging the computer scientists to look and go, Wait a minute, this is bad. So how can I modify the algorithms so that's not possible? So we're really thinking a lot about the integration of ethics in engineering, having good technical, ethical thinking. And we want our engineers, we want all engineers to come out with ethics as a constraint on the products that they're trying to deploy.
Ted Fox 13:59
Right. I mentioned Industry 4.0 for additive manufacturing. Is saying additive manufacturing is 3D printing, is that oversimplifying it? Or is that accurate?
Fred Higgs 14:11
So that used to be a big debate, but in today's--yeah, they're pretty synonymous. So you may as well say 3D printing, yes.
Ted Fox 14:20
I think we all, anyone listening to this, we probably have a vague image in our heads of what 3D printing is. There's a machine, an operator inputs some sort of data, and rather than something printed on a piece of paper that comes out, out comes an actual three-dimensional object. But--and I'm laughing as I say this because clearly I am not an engineer--but can you tell us a little bit about how that three-dimensional object actually gets made? And my understanding from your talk is that it has to do with an area of science known as tribology.
Fred Higgs 14:53
So tribology is actually my expertise. So it's not--it's present as one of the phenomenological actions within the 3D printing process, but it's not essential to it.
Ted Fox 14:53
Okay.
Fred Higgs 14:55
So you basically asked the question about 3D printing being pretty synonymous with additive manufacturing. I just said that effectively, yes, because there are other things you can do to manufacture things by--it's all about the difference in subtractive manufacturing versus additive. Most of the things when you and I were growing up were made off of subtractive manufacturing; you have a big block of something and you cut it back into the final object. But you can imagine that has some design constraints, say, the interstitial cavities inside of a three-dimensional block that you're cutting away from. You know, you and I are made of certain types of material, of biological material, but within us, they're little tubes and veins that fluids go through. How do you do that? Now, if you think in principle, there are bio 3D printers, and we have people that work on--whole organ 3D printing is like the holy grail in the bio 3D printing world. But imagine that, in principle, if you don't do subtractive, you do additive, you start from the bottom up and add things layer by layer. And it might be good here if I go into the definition of additive manufacturing.
So you have a three-dimensional computer-aided design file of something that you are trying to print--CAD, the acronym is CAD. So you have a three-dimensional CAD file, it shows you Fred Higgs as a three-dimensional-rendered object. Well, now you can feed that object to a 3D printer program, and, depends on how it is, they all have the same basic functionality. They spread a layer--and the ones, the 3D printers I work with are powder-based 3D printers--they spread a layer of something like powder, and then they look at the CAD drawing and see, We're at the bottom, right? Where are his feet? Okay, they're size 13; let's solidify the powder in this area. And so they make a thin layer that shows the imprint of the bottom of my feet. And then the next layer goes up. Now it's a little bit of, you know, a percent, small percent of my shoe, and then it goes up--or I should say, let's stick with my body, it's the next layer of my foot. And it just goes up in slices. If you do that, there's no reason you can't have holes in the middle of it and make little tubular geometries inside of it, little veins and things like that, assuming that you had a printer that could do biological material, right? There's just no reason why you couldn't. So you could come up, and there's no limitation to the design complexity because it's additive. But you cannot get me from a single block unless you just dealt with the exterior of me like a sculpture, right?
Ted Fox 18:00
Right, right.
Fred Higgs 18:00
They could just cut back a block, but the inside is the block, right? The inside will not be a bunch of tubes and cavities that you're comprised of; you can only do that additive. So additive means you're bringing a CAD model of something, and the machine goes layer by layer, and it's doing the same processes. It's going layer by layer, and then it puts it all together or at the end, it's all together, you have a solid object.
Ted Fox 18:29
And when you talk about a CAD file being the basis for that 3D printed object, and I think I remember you saying this during the talk that, we're still still a way's away from the idea that it would ever be as simple as something like a Xerox machine where anyone could go up and be like, Oh, okay, I want this object. Is that something that is being worked toward? Or is it the kind of thing where it would always make sense that, you know, you're going to need a CAD file in order to produce this three-dimensional object?
Fred Higgs 18:57
That's awesome. I do believe that we will get to the point where there will be like a Xerox or Canon machine. Now if you come to my lab, we have a metal 3D printer; it's a binder jet 3D printer. And it looks like your Xerox machine, it looks like a Canon machine. So people get that impression like, Wow, I see you pushing buttons, I see things coming out, this is it!
Ted Fox 19:21
(laughing) This is it.
Fred Higgs 19:22
Exactly. Well, it's a powder bed 3D printer, we're powder mechanics experts. So when you bring in a new material and you want to spread it, it needs to be pretty smooth and uniform; we got a Ph.D. that's worked on that. And that Ph.D. has produced models, and that model has become--we have a software called Spreadify. And that software can take--you can put it in what's called a powder rheometer, a little sample of your powder, it characterizes the powder to get its properties, its spreading properties. Based off of that, it generates some settings to know, under what spreading parameters--like the speed at which you spread, the weight that's on the roller per se, the spinning rate of the roller, all these things in spreading it--it will tell you what they need to be set to for that printer to get a nice, uniform spread layer for that particular powder material. That right there was a Ph.D. that worked on that.
Ted Fox 20:28
(laughs) Right.
Fred Higgs 20:29
And there's another Ph.D. following that up. But that tool, Spreadify, literally a licensable tool, that tool, if a company were, say, to license that to put on their printer, it's one step towards making that automatic. But that's just one of the processes in a 3D printer. There are others that if you have a laser fusion or electron beam melting or centering type of system, they bring in--you have to bind the powders now. My printer uses a liquid binder, like a glue; wherever it goes down, it makes it solid where the CAD drawing says it should be solid. So other printers that are like the fusion-based ones, laser or electron beam--I call them beam-based, laser beam, electron beam--they come down, hit an energy source on the powder, and there it becomes solidified. But the point is that both of them look to solidify the powder on a particular slice, and then move up. There are Ph.D. students that are just trying to come up with predictive waves for different powders, looking at the beam energy, looking at the translational velocity of the beam as it's trying to solidify different parts. There are Ph.D.s that are just doing that. I have a Ph.D. that looks just at the fluid from a binder jet going down. I showed this in the Notre Dame seminar. The fluid goes down into the powder, and it pulls the particles together to form a solidified primitive, we call it. That's a Ph.D. that's working on that day and night, right? And getting that model to work, and then validating that with experiments, we would then say, Ahh, now we have a model. Then a company could come in, license that, and it's another process that has become a little bit more predictable. You get a bunch of models like that to guide the printers in what to do, you're getting closer to the conventional two-dimensional copy machines that we have from Xerox right now. Those machines have already been optimized. They know, we've got five inks, we're color, we understand the speed at which we do this, the settings aren't changing anymore. And so they're locked in. All of us are working with Ph.D. students to create these models to tell the machines what to do. And that's just from the additive process that's on there.
But the beautiful thing is that, remember, it started with a digital file, and it's driven by the data that's coming in from that file. So in principle, if that machine were sensing things, that machine is guided by digital data. And that's what Industry 4.0 is all about. That's why it's one of the key technologies that are on that because from data, you get three-dimensional objects that you and I could drive, or fly in, or sleep on. And that's a new paradigm shift. Because now you can produce things without actually having any human intervention, in principle. If you have a factory that's a full industry 4.0 factory, you may not have to have human intervention for a lot of parts there.
Ted Fox 23:42
So, and this was something that you did hit on, what are some of the practical applications you all are working on right now? I know you talked about something called Drillology a little bit and some hip implants. It seemed like there were some really cool things that you're already doing in looking at how additive manufacturing, 3D printing, might be able to better serve some of the needs of the world right now.
Fred Higgs 24:06
Once you realize that a CAD--which you could make a CAD file of any geometry; before 3D printing came out, they had CAD--if you could give that to the printer, and then the printer can print whatever that is, and it could do it at the same speed--maybe a little slower depending on the complexity, but it could do it at a really fast speed--all of a sudden you start going, Wait a minute, why am I mass manufacturing everything? Because mass manufacturing from Industry 2.0 was about making the same Model Ts. So wait a minute. Fred is six-four, Ted is--what's your height, Ted?
Ted Fox 24:48
Six feet.
Fred Higgs 24:48
Okay, that's not bad. (Ted laughs) So wait a minute. Fred wants an SUV that is suited just for him. So we can make that one, and then Ted could have one that's suited for him, no wasted room. Why are we doing mass manufacturing? We need to do mass customization. Because that's a tweak to the CAD file, which can happen automatically. So the whole point is that things become personalized. So what we're doing with it is, we're looking at personalized manufacturing. And it has different definitions for different industries. So if you're talking about geothermal, clean geothermal energy there, then you're talking about a special type of drill bit. And we say that we can personalize your drill bit to your geothermal rock that you have to drill. The rock's gonna have different lithology, different geomechanical properties there. And we will run some analysis on that rock, and then in our case, you talked about Drillogy, we made a code that actually runs through those properties of the rock, and then says, This is what your drill bit needs to do to have a good drilling rate. And it modifies the beginning CAD design. So now the winning CAD design is sent to the 3D printer. And now you make that particular drill bit. So that's a rock-specific drillbit; it's personalized for that rock.
Now you're talking about my father's artificial knee, right? My father got an artificial knee several years ago; one size fits many, I'm not gonna say it's one size fits all, it's one size fits many. (Ted laughs) Well, you know, my father is, you know, about 80. And he's--or, you know, just surpassed 80. And you know, he takes walks in the neighborhood and things like that. You know, he has this weight, he walks a certain way, he has certain gait motion. And all those variables can be taken into account to give him a custom knee. If all things being equal in the manufacturing process, then let's make one for my father. So it's a personalized knee that we're after.
The project that I showed at the Notre Dame Edison Lecture was for a personalized hip joint. Because we're working with a professor here at Rice, B.J. Fregly, who has a cancer project with our state. And it's with MD Anderson, one of the world-class cancer centers. Everything there becomes personalized, right? Because cancer affects people in different ways. So you have, once you bring on, say, an implant, like a hip, you know pelvetic implant, and the hip part is custom to a different patient, because the cancer affected them in different ways. Otherwise, if you treat them all, they're like three regions on the pelvis and depends on how much, you know, bone has been affected, you have to cut bones. So you're very conservative. But if you can be custom--like, no no no. Forget the type-one, type-two, type-three cut. What do we do if, you know, God forbid, a Fred-Higgs cut. And there we just say, Oh, here's the minimum that's needed. We've done the analysis on this guy, and we can do one that's personalized for him. When you can do that, and now you don't have to go and say, Hey, Can y'all build a new expensive mold at the manufacturer for it? It's a 3D printer, you just say, Hey, we've altered the CAD for this guy and now print him a custom hip joint. And we have models that for each project have the different modes of physics that govern the performance of that particular product you're trying to build. And we take that performance into account to do this analysis, we get a winning candidate, and then we print it out. So the pattern is constantly that. Whether it's a drill bit, or it's a, you know, orthopedic implant, whether it's a hip or a knee like what my father has, it comes down to getting patient-specific information, running some analysis that shows you which winning design is personalized for that patient, and now you can do it for a lot of people. You have mass customization, not mass manufacturing.
Ted Fox 29:14
Right. It's very cool. Just as we're wrapping up here, we've mentioned Rice, and our provost here at Notre Dame, Marie Lynn Miranda, she used to be provost at Rice, and she worked with you. And as I told you, she was very excited when she found out I was going to talk to you, and--you've already mentioned it, she'd said to make sure that I asked specifically about the Rice Center for Engineering Leadership, which you direct. And it's come up at a couple different points, but what is kind of the mission and the purpose of that center? What are you looking to instill in your engineers while you have them with you at the university level before they go out and start practicing engineering in the world?
Fred Higgs 29:58
That's a great point. And it is all about them practicing engineering in the real world beyond our ivory towers. So in a nutshell, it is to produce ethical leaders in technology and engineering. And that would be the concise statement. But the way in which we do that is kind of two-prong. We have arguably the most professors in the practice in a single unit on campus there--you know, so like a department-level unit, we have a lot of professors in the practice, and pretty much all of them were executives in industry. And so we bring them back, you know, some of them have Ph.D.s in engineering and an MBA, some have Ph.D.s engineering, and some have, you know, an engineering degree and maybe an MBA there, but they all reached the pinnacle at different corporations, and now they come back with that perspective. They put the industry lens on teaching and advising our students, but it's within a vision, and that vision is that you're going to get fundamental engineering, leadership training. And those are courses like--those teach the basic core competencies of communications, having vision, teamwork, followership, their ethics and values, being able to think quickly on your feet. But all those core fundamental engineering leadership skills is one prong. The second prong is, you must choose a career track under the acronym RIPE. So these students are pursuing this undergraduate engineering leadership certificate, and at the end, they must choose from the acronym RIPE; RIPE stands for research, industry, the P is a non-engineering pathway, and the E is for entrepreneurship. So they choose to take a class to apply the engineering leadership fundamental principles that I just talked about to one of those career tracks. So a young Fred Higgs, me 20 years ago, when I came out of school, I would--actually, 25 years ago, when I came out of school. Who's counting?
Ted Fox 32:18
(laughing) That's right. I don't like to count back, either. (both laugh)
Fred Higgs 32:21
Exactly. So when I came out of school, I would obviously be an R student, right? I was going on to pursue my Ph.D. and to build a research career. I would have chosen the R track. A lot of students choose the I track, which a lot of our professors in the practice are [geared] towards because they're going towards industry. I'll come back to the P. The last one is entrepreneurship. They're students who want to go on to be the next Jeff Bezos or, you know, get into understanding that's like a venture capitalist like a John Doerr and a lot of other famous engineering, innovative business people--Elon Musk, you know, engineers that go on to start companies. They would choose the E track, the entrepreneurship track.
But then that P is a little non-traditional. We recognize that people--the later generations because of social media, these students come in way more informed. So, you know, I was talking with an undergrad and I said, Hey, what do you want to do, and they said, I'm going to med school. I said, No, I mean, when you're finished, you're gonna work in industry and then you want to go to med school? No, I'm going to med school right after undergrad. What? You're never going to work in engineering? No, I was just using it as an enabling pathway. Because they know that engineering is a really good way to get into business school, law school, and med school. So they could just choose that pathway. And then going into, you know, one of those professional programs, if they stop short, they still have their engineering degree. They're now coming in sophisticated and choosing that with no plans to ever work, other than an internship, in engineering. So we call that the non-engineering pathway. And we have an instructor, George Webb, who has two degrees in engineering, electrical degrees, a bachelor's and a master's, and then he went to law school to become a patent attorney. And then we were able to bring him back, and now he teaches these students, Hey, there's some non-engineering pathways that your engineering is good for. We want analytical, objective-minded people running for president. And so we want to engage these students who have that passion to work outside of engineering.
Ted Fox 34:22
Just you saying that there at the end reminded me, I had Trish Culligan, the dean of our College of Engineering on a few episodes ago, and she talked about just needing more people in policy who were engineers and who had an engineering background to, you know, understand the things that they're making decisions about and how much more needed that is. And it happens in other countries, and we need more people like that running for office in the U.S., so ...
Fred Higgs 34:47
Indeed, indeed. And so there's an undergraduate engineering leadership certificate that focuses on fundamental engineering leadership, and then you have to choose to apply it to one of those four career directions.
Ted Fox 34:59
Fred Higgs, this has been really great. I do feel like I have a better understanding of some of these things now, so I really appreciate you taking the time to talk with us today.
Fred Higgs 35:07
Ted, I appreciated this opportunity. And thank you very much, and I look forward to hearing great things from the other parts of your podcast.
Ted Fox 35:16
(voiceover) With a Side of Knowledge is a production of the Office of the Provost at the University of Notre Dame. Our website is withasideofpod.nd.edu.