 So it's my pleasure for the special Purdue Engineering Distinguished Lecture Series today to introduce our Dean of Engineering, Arvin Rahman, the John A. Edison Dean of Purdue's University College of Engineering, and the Robert V. Adams Professor of Mechanical Engineering. Arvin. Good afternoon, good afternoon. I'm really delighted to welcome all of you who could be here in person for this Purdue Engineering Distinguished Lecture, and a welcome to all those who are joining us today online as we livestream this event. The Purdue Engineering Distinguished Lecture Series started in 2019, really is a way to bring to Purdue to our campus some of the thought leaders from the field of engineering, both in academia and in the world of practice, to really come here, engage with their faculty, students and staff, and really talk about some of the grand challenges of our times. For this Purdue Engineering Distinguished Lecture today, which is the first one of the spring 2024 semester, on this perhaps slightly gray and damp day in West Lafayette, Indiana, it is truly an honor to welcome from sunny Southern California, Dean Yannis Yortzos. Let me tell you a little bit about Dean Yannis Yortzos. He is the Capralian Chair of Engineering, the Dean of Engineering at the USC Viterbi School of Engineering. He's been there for a while. He is a renowned scholar in viscous flow, in porous media. He is an international leader in engineering education. And he is a humanitarian, as you will see. And he's been honored with many recognitions worldwide. He's an associate member of the Academy of Athens. He's a member of the American Academy of Advancement of Science. He was a co-winner of the Gordon Prize from the National Academy of Engineering, as one of the co-founders of the Global Grand Challenge Scholars Program that we at Purdue have been looking at a lot over the years. And he's a member of the National Academy of Engineering. Without further ado, will you please join me in welcoming Dean Yannis Yortzos. Thank you very much. Thank you very much, Arvind. It's a great, great pleasure to be here. It was mentioned that I'm coming from South California, which was sunny. However, it was not sunny yesterday, actually it was raining. And those of you who follow the weather realize that I understand that San Diego got for in a couple of days the equivalent of one month's total of rain. So clearly, I didn't bring to you all this big rain there. But thank you for inviting me. The last time I was here at Purdue was very long time ago when I was a graduate student. I think I came here to interview. And some things never change. For example, Ramkey is still here, a professor. And the weather hasn't changed very much since then. But I have strong feelings about that. And when I remember my interview at that time, Nick Peppers, some of you know him, was a professor here at the time, Elias Frances, where is he? He's right there. He's another Greek who was here, and they welcomed me very, very much. And a lot of the good people they know sang and I were, well, did not overlap at Caltech. I may have been his TA when he was at Caltech. I don't know, sang maybe yes or no, I'm not sure. But I've been a TA of a number of important chemical engineering figures like Peter Kilpatrick, who is now the president of the Catholic University of America, Eric Taylor, who is the president of the University of Minnesota. So my students, if I can say so, have had tremendous careers. And I have been very honored to know our very good colleague here, Leah Jameson, who was the former dean of engineering here, a wonderful presence and a national leader. So thank you very much for being here, Leah. And Arvain, thank you for your wonderful introduction. I have been torn about what to present here. I know this is a distinguished lecture. I hate to know if I were to be invited to a non-distinguished lecture. So I'm really happy to have that distinction. But at the same time, I'm a little bit intimidated by making sure that I will rise to the level of a distinguished lecture. And the reason I am saying this is because I wanted to figure out whether this is going to be a dean's talk or a chemical engineering talk. And I was a little bit confused. Do I speak, you know, give a dean's type of thing or a chemical engineering thing? And so I decided to create a melange of this and hopefully be able to put it together in a way that actually reflects this connection. I will also show you that I've been the dean for 19 years. So my research activity has been, let's say, compromised through that period of time. However, COVID came in 2019, 2020. And that saved me in some sense because it forced me to try to understand how COVID works and what's the epidemics. And then I made an analogy of a model in COVID as a chemical reaction engineering problem. So I said, voila, this is what I'm going to do. I'm going to go from one end to another and then put together all this intertwining of engineering and social phenomenon. So I have a thing here, so I have to keep going down. So that's my talk today. And as I mentioned before in engineering, I will also have some examples from chemical engineering given the fact that this is also the home department that I have been, the home school that I have fallen here. So I'm more than happy to show you some examples of that. So here are the concepts of the talk. And these are the three things that I hope you take out of this talk. And so the first one is I'm trying to ask the question, what is the future engineer of 2020? Now, the engineer of 2020 was a seminal report that the National Academy came out in 2004, 2005 to try to predict what should be the characteristics of the engineer of 2020. Now, the engineer of 2020 has graduated some time ago. And so the question is what should be the characteristics of the future engineer of 2020, which I hope the Academy will come up and figure out a particular, you know, have studied to decide that. And I think one of the characteristics of the future engineer of 2020 will be trust and purpose because I think if you look at what has been described as the attributes of the engineer of 2020 is a lot of competence, but not a lot of character perhaps or purpose. And I would like to make the case that this is something that is needed in today's world. Then I will make some arguments that social phenomena desperately need a chemical description or a chemical reaction engineer description. Why do I say that? First of all, as a chemical engineer, I have a chemical engineer in Hummer. So everything else that I see is a nail, so I hit it. And therefore I hit everything with a chemical engineer in Hummer. But I can tell you that my position on this is that I look at a lot of description of social phenomena. People use typically physical methods for that, random walks, many other things as well. They do not use if most fundamental thing that happens between humans, which is actually a chemical reaction. And this chemical reaction is very characteristic of behavior, the way we argue, the way we negotiate, the way we transact. And I think this is needed and hopefully someone may already have done it by the way I want to put a disclaimer here that I don't know the entire literature. As I said, I'm the dean and I haven't really done a lot of work in this area, but I don't believe this has been done before. And finally, I will go to one more more sophisticated step and I give you a chemical engineering description of contagion. And this came out because of the 2020 pandemic. And I think that's something that hopefully you will realize that I have not lost my touch of differential equations and waves and stuff like that. So I wanted to sort of prove to you that I am not a wasted talent in sort of a dean's office, but I still have the ability to do something in there. So that is actually my excuse to be able to show that I can still be your colleague, given the fact that you do so many things in your own thesis as well. Okay, so here's my view of engineering. And this also leads to what I call engineering plus. So this is something that I have paraphrased from Brian Arthur. Brian Arthur is an economist, wrote in 2008 something called the nature of technology. So the definition that I use for engineering is very simple. Leveraging phenomena for useful purposes. Leveraging phenomena for useful purposes, so when I talk to parents and prospective students, they tell me, what am I going to do to engineer? I said, you will leverage phenomena for useful purposes. What are these phenomena? You have physical phenomena, I don't know if I can show that, maybe, oops, sorry. Okay, I'll stop here. Chemical, geological, maybe planetary if you wish, and biological. These are the types of phenomena that we typically use in engineering. In terms of increasing complexity, you go from physical down to biological. Now, physicists among you will say nonsense, everything is physics, so forget everything else. So because we are not physicists, we will basically say, no, actually in terms of complexity, probably go that way. And I think that's probably a better way to describe the complexity. And also there's a convergence. By the way, phenomena could also be systems, devices, and tools, and combinations thereof. And for useful purposes, that includes also the discovery of new phenomena. So discovering new phenomena is a useful purpose. Now, when you look at this definition, leverage phenomena for useful purposes, you realize that there are two significant elements there. The technical part, which is the competent part, how you leverage phenomena. And then the moral or ethical part, which is a useful purpose. And I think the social part and the technical part are already part of this description here. And useful purposes obviously sometimes lead to unintended consequences. So this is already part of this description here. And unintended consequences happen every day. Well, I don't want to mention AI, because we know about AI and the unintended consequences that can come from that. But more important than that, I claim that engineers are going to not only take advantage of physical, chemical, geological, and biological phenomena, but also social and behavioral phenomena. So I'm making a statement here that it goes a little bit further than what we usually do in engineering. And I'm saying that engineers in the future, and this is this engineering plus mindset, we are also going to talk about social phenomena and behavioral phenomena. And I believe that AI, with the ability to use, utilize so many data and extract insights from them, will be able to give us very significant insights on social phenomena and behavioral phenomena. Now, if you're a lawyer or a businessman or someone in a different school, you say, you're overstretching it. I think that I believe very strongly that engineering and the techniques and mindsets and all that is going to penetrate these areas. Because remember, every company is really a technology company. And every company, which essentially a lot of social and behavioral, essentially is a technology company as well. So think about it. So I think the future of engineering in a bigger way includes all these phenomena as well. So that's my first big statement I'm making here. Now, I will also give you a Maslow hierarchy view of engineering focus. Now, Maslow is a psychologist and created all this called Maslow hierarchy. I will say that any one of us here in engineering, whatever our major is, does four of the following buckets. One, sustainability. Sustainability could be energy, water, climate, food, agriculture, materials, ecosystems, natural resources. This is the most important part of what we do and we'll be doing for the foreseeable future given all the impact on the planet. Second is health. By engineering and medicine, health and technology are converging as never before. Engineers are going to play a huge role in advancing health in many, many different ways. Third is enriching life. How do we enrich life? Mostly through advances in computing or digitization. And the fact that we are able to reach many people through globalization, through communication, through controls and all that. Exploration and discovery, these are all driven by enriching life and a lot of it comes through computing. And the fourth in one is security. Security with a cyber, national security, infrastructure, electronic supply chains. These are part, so no matter what you do in your majors, I can challenge you to tell me that they are not part of these four buckets. And to me, this is a Maslow hierarchy description. Because in a Maslow hierarchy, you have, this is for the individual, physiological, safety. And then you have love, belonging, and esteem, and self-actualization, which I go under enriching life. I put them under this category as well. So this is another sort of analogy that I pursue. This is not mine. It was inspired by the National Academy of Engineering Grand Challenges 2008, in which they essentially classify the grand challenges in these buckets. I don't know if this has been associated a lot with the mindset of engineers. But I think this is very much something to keep in mind. And so when you want to describe to your friends or to your parents what you do can say, well, I do sustainability or I do health. Whether you do mechanical or you do chemical or anything else. Or enriching life or security. Again, this is part of what I call engineering plus. And there's an engineering impact on society that also has the unintended consequences. So let's go back to my original question about the engineer of 2020. The engineer of 2020, which was a report of 2004. And by the way, this, as I mentioned, has been already, folks are already out, has a description of a lot of technical competence. Skills, ingenuity, creativity, communication, management, high ethical standards in the sense of making sure that people that deal with building something, they don't cut corners, for instance. This type, I think, of high ethical standards. Professionalism, leadership, agility, lifelong learners. But I think what is missing, this is mostly competence. But what is missing, I think, an attributory missing are purpose, character, and trustworthiness. Why do I talk about trustworthiness? Because the world today is desperately needing trustworthiness. You can read it in the newspapers every day. There is an abundant lack of trust in pretty much anything we do. I'm not saying that engineers are not trustworthy. But I think a lot of the work that many of us are doing is because, is inspired by solving some big challenge, some big problem. Whether it's sustainability, whether it's the climate, whether it's something else. And I think the generation of new students is very much attracted by purpose. And I believe that this should be part of what we are going to be looking at as we move forward in the description of the engineer of the future. And this is all part of what I call a convergence. So I call it engineering plus x. This plus here is an undefined operator between engineering plus x. I also said that engineering and x can be vectors. So just such to be a little geeky about this to make sure that you don't corner me and say, well, what about this? And it's increasingly human centric. And I say x is anything. Now, the former, the late former provost at USC, Beth Garrett, used to kid me and tell other people that in my mind, in my own mind, the x is the rest of the university to engineering. And I said, yeah, that's probably true. And so I wanted to make sure for them to understand that we believe in the centricity of engineering in this sense about everything. And I have some pathways in which e empowers x, engineering empowers x. I think we see this all the times through technologies and methods. There is also a place where x empowers e in the x-mimetic thing, biomimetic thing. Sometimes we take advantage of nature on how we look at how to develop new engineering things. I think there's a common element of that. But more importantly, I think u, e, and x are commingling. There is a union between them. And this commingling is something that usually comes with exponential technologies, but also, let's say, when x is human and humanity driven. And this is where it affects ethics. So actually, my position on AI is that humanity and AI, when AI becomes very strong, will be a double helix in which we will iterate between the two. And hopefully, at the end, humans are going to win this iteration, but I think it's going to be this double helix going on again and again and again until, and I do believe that humans will be able to extract insights from the way AI works to be able to advance our knowledge and understanding of many other things. It requires, just like Newton, discover the calculus and figure out ways by which we can do differential equations and describe nature in different ways and understand turbulence or understand many other things. I think the future will be such that we, some smart person, maybe in this audience here, will be able to come up with a way by which we can understand how come AI was able to figure out something that humans were not able to do. And I think we'll be able to get ahead of that and then essentially beat AI in its own game. And I think that's my expectation and hope for the future for that. Okay. Now, we live in an era of exponentials and I want to understand actually even more than exponentials and the importance of trust. So here, I'm plotting a technology versus time curve. You can see this kind of an exponential one. By the way, a student observer has noticed that I have no units on technology or time because I wanted to make sure that nobody corners me in any particular case. This is completely dimensionless numbers. I won't tell you how I made them dimensionless. And if you have a fixed mindset, then clearly there's a gap between the technology as it moves and the projection of technology. This gap exists all the time when you come to policy, government, even in academia. If we're not agile enough to adapt and change, then this trust gap is going to exist. So my suggestion is there is the only reason for us to be able to follow the evolution of technology is to have a trust worthiness that allow us to not have this gap so that because this gap is the tax we pay when trust is absent or mindsets are fixed. So that's something to keep in mind in this characteristic of the fact that technology is moving at a faster pace than ever before. And our ability to think forward is usually a straight line extrapolation from our past experience. And I drew a tangent there to illustrate that. So trust is a, so I use Steve Kovic's definition of trust, Steve wrote a book on definition of trust, and trust is competence and character. And so there are four cores of credibility. In the case of competence, capabilities, talent, attitude, skills, knowledge, and results, performance, past, current, and anticipated. This is what engineering schools have been doing forever. How do we get people to have outstanding technical competence, places like Purdue to do it extraordinary well, and other places as well? What I'm trying to say, however, is that in addition to this, in today's world, we also need character. The character will create integrity, humility, courage, and congruence, and intent. And this is where the purpose comes in, motive, agenda, and behavior. So I think that in the future, again because trustworthiness is something that is becoming absent in this exponential world, has to be complimented by not only the outstanding technical competence, but also have outstanding character. I give an example, you're not going to be on an airplane where the pilot has outstanding competence, but zero character, you don't wanna do that. You also don't wanna be in a plane where the pilot is the best person ever. However, the technical competence is pretty poor. So I think this is where trustworthiness comes in, and I think that's something that we need to be able to perhaps include in how we train our engineering students and the impact of engineering to society through this. Now, I know character comes into the question of ethics, perhaps religion, perhaps the upbringing of people, perhaps values. So people basically talk about the fact that AI and all that are going to diminish humanities and the values, I beg to differ. In fact, I think values and humanity will be more important as we deal with fundamental issues with technology and AI, and I think this is something to keep in mind. And setting the pursuit of goals is an ethical imperative, and that includes trust and purpose. Now, why technology ethics? Most of the time when we make, let's say we start an adventure, let's say a startup, we'd like to have a decision to be smart, ethical and legal. Clearly, these are three things that we have to have. By the way, we follow politics in the news, provide to me please some examples of people that make decisions on this intersection or the Venn diagram. I'm just kidding you here, but decision making should be there, right? And so ideally you want to be in that switch spot because you like to have a, let's say a startup that is based on smart, ethical and legal situation. However, there always be unintended consequences. And as this moves up, then there will be created branches that actually are unintended consequences branches that need to be cut and that's how regulation comes in. Now, how do I know that there are going to be unintended consequences? Well, if I look at dynamical systems, we deal with, let's say humans. Humans are, first of all, we have multiple degrees of freedom because you have many people and the interaction between humans is nonlinear. So those of you who have taken nonlinear dynamics know that you have chaotic behavior if you go that way. So I'm almost 100% sure that whatever you do, particularly the most more powerful the technology is, the more powerful will be the unintended consequences and there will always be there. So these are the, as time evolves, let's say from a time from one level to another from the smart, legal and ethical, you may end up to something that it is only smart and avoids the ethical and legal that actually is an unintended consequence. You like to be able to keep the core going and then prune off the unintended consequences and that's actually where policy and the regulations come in the so-called guardrails that we see very much a point of concern for AI today on how you make sure we avoid these unintended consequences. So I'm sure what I say here is nothing that you don't know about but I think I wanted to sort of put it in a schematic here. By the way, all this art was made by me and you can tell that it is very poor art as we can see here but at least I hope you get the point on what I'm trying to say here. So let me conclude this particular part of my talk that the mantra of innovation will change. The all-ideo model was business, technology, design, deserability, viability and feasibility. I think today we also have to ask the question, is this innovation also ethical, human-centric, grand challenge-like? I think that's something we may have to start thinking as we develop a new idea, a new startup, a new application or something. Does it solve a big purpose? Does it solve, for example, one of the sustainable development goals? Does it solve the grand challenges of engineering which, by the way, need to be re-refraised? It started in 2008, I think now it's 2024. The 2008 grand challenge for engineering did not include the word AI, believe it or not. The 2024 or 25 grand challenges, I'm sure, will have the word AI in it in a big way. So I'm calling for our colleagues at the academy to actually take a look at that. So as part of all this, the grand challenges called as program that I mentioned emphasizes, I think, both these concepts of competence. And I have used some sort of a different wording. I call it hack the exponential. In other words, be able to do the technical part. Engineering plus, to change the conversation about engineering. And then to have a character in terms of understanding the culture of other people and also the impact of engineering to society. So I use some sort of a wording of mine here to illustrate that. But I think that this grand challenges program we started back in 2008, I think characterizes a bit of that. I should tell you also that as a result of this, we have been able to attract at USC at least an increasing number of women in engineering. I think there are more and also other minoritized groups in engineering. I think there are more perhaps in tune to the ability of engineering to solve big grand challenge type of problems. So I can tell you that since 2019 and for five years in a row, the entering class at the undergraduate level at USC in engineering is gender balance. It's 50-50. So I think we were very excited to see. And I attribute this to the fact that we try to promote an engineering version which actually includes this part. And we're very happy to see the impact that it has. As Alvin mentioned, this won the Gordon Prize in 2022. People that participated in this award was Rick Miller, former president of All-In College. Tom Catruller was the former president of the University of Connecticut, Jenna Campbell Carpenter. She was the ASWE director last year. And they all participated in this. So we're very pleased to see the award of that. I should mention a final thing about the impact of this Grand Challenge Scholars Program. Tom Catruller at the Gordon Prize acceptance speech says that this actually can be the blueprint for a liberal arts education for the 21st century in which you go from a triangle of mindsets, knowledge, and skills, which actually should be part of what we want to do in a Grand Challenge Scholars Program to something that includes identity, agency, and purpose. So make the connection between these three things. And it doesn't apply only to engineers but can apply to higher education at large. You know that a higher education has been criticized for not providing what is needed to our current graduates, whether students, whether they are in engineering or other place. So this sort of analogy can provide identity, agency, and purpose. Perhaps that's a blueprint for doing that. And Rick Miller and others are putting together something called Life Transforming Education, which I think is an important activity. We'll see how this is going to play out. So here's my future of engineering of 2020, which talks about all the things that I discussed, including looking at how we address big Grand Challenge-like problems. I was at the COP28 conference because I need to advertise this. The COP28 president was my former student. He invited me to be there as his guest. So I was able to hobnob with the heads of state. Of course, I didn't introduce myself. Yanis George was dean of engineering with Macron or Modi. I just was there in awe of these people as they were moving around. Not in awe really, but you know what I'm saying. Celebrity awe, if you know what I mean. And it opened my eyes on the importance of the problem for climate. The time is ticking. And I think as engineers, we have to step up and try to solve this problem. There's no question about that. We see this every day. I think we are underestimating the impact that this program, this issue, has. And it's a complex problem because it involves politics, involves policy. But an engineering solution, which is actually amenable and acceptable to many, will resolve this problem once and for all. And I think that's something we need to pay more attention to. OK, my next part of my conversation was to do about the case for a chemical engineering description on social phenomena. Now, why I say that? Currently, there is something called econophysics. How do you use physics to solve economics problem? Use statistical physics to explain economics. It's all great. I love it. You can do random walks, condensed matter, spins, and so on and so forth. Or agent-based models, right? Discrete entities interact through rule-based interactions. You do many interesting stuff there. However, at the fundamental unit, single human level, all social phenomena fundamentally are biochemical. There is no question about that. And behavior responses often mimic this biochemical thing. So if we're interested in the aggregate, there's no way we can do real good predictions without taking into account chemical kinetics. And I think that's the point I'm trying to make. Those of you who are chemical engineers, I'm sure you agree with me 100%, those of you who are in mechanical engineering may say, eh, you know, I'm not sure. Topol is, I think, even more unconvinced for that. But as I said, a chemical engineer, I have the chemical engineer hammer. This is what I'm going to do. And let me give you an example. Let's consider the case of I look at things as a chemical reaction. Now, do not ask me about stoichiometry. Do not ask me about things that are moving between things. I know that you say, well, what is this guy doing here? What's the stoichiometry? This is wrong. Culture. What is culture? Let's say culture is you have A that has a star and interacts with B. And then the B gets a star, right? So there is sort of a contagion going on there. Process of sales. Ah, process of sales, I think, is very transactional, is a very much a chemical reaction engineering. Why? Because A, let's say, has dollars. B has a car. Then A gets the car. And B gets the dollars. So this is very much an exchange of electrons between A and B. And this is what happens. And transformative experience are very much a chemical reaction engineering. So if I plot contentment, the contentment goes, increases in the direction going down, as you can see, versus the extent of the reaction or the interaction, you're going to get a curve like this. You can see there is a resistance, right? There's always an activation energy barrier. And let's say you want to go and buy a car. You always say, I don't want to buy this car. Is it good? Maybe do the money. So you have to go through this activation energy barrier. Then you go down, sale done, pay the money. Everything is done. This type of thing, I think, should be taught to all the people who do communications and marketing and say, this is what you need to worry about. Do this and figure out the kinetics of this particular reaction, including the activation energy barrier. I'm sure they do it intuitively, but I think there's a different way to move it this way. Finally, requires definition of species, reactance, products. This could be demographic. Random walks and collision, potentially. Activation energy barrier, definition of complexes. And as I said, this may help model, understand, and possibly control phenomenon. Again, caveat. I am not sure that this has not been done before. I have presented this in sort of informal presentations. Maybe I put it someplace. And maybe this has been taken and by other people as well, which would be great if it has. So I don't want to be accused of plagiarism because I know that plagiarism is not a good thing in recent years. And so I just want to make sure this is not an in-depth account of the literature. But let me give you evolution of technology. Evolves through ideas, possibly random walks or random excursions. I think we can simulate it as an irreversible chemical reaction. Very simple. Let's say A provides A. It's almost like a autocatalytic reaction. So A gives you A. Well, if you do a chemical reaction model on this, what are you going to get? Oh, could be also a bimolecular reaction. Or A goes to B. B can be biotechnology or other things as well. So by the way, do not pay attention to my stoichiometry again. So let's talk about a first order reaction for innovation. Let's say autocatalytic. That is actually a simple equation, slinner. The kinetics are simple than what you get. You get an exponential. Are you familiar with exponential? It's called Morse law. So I presume for you Morse law in a single equation, which is an innovation that's actually a linear reaction. So Gordon Moore, if he sees that, will probably be very unhappy with me. However, this isn't one way to describe it. More importantly, let's assume you have a second order reaction. And then you have a bimolecular reaction like this. And do the kinetics. Well, if you do the kinetics, you get a singularity. And this singularity is like 1 over T star minus T. You can do the math here. It's easy. Well, that is a singularity. Ray Kurzweil has said some time ago that we have possibility of a singularity. In other words, technology is not going exponentially fast, but even faster than that. Is AI today going through a singularity? Many people say it may very well be. And let me give you an example for that. I use a courtesy of Prem Natarajan on Capital One. This is petaflop houses, computing power, to train our system as function of time. You can see a faster than exponential growth. You can see this is not simple. It's almost like a hockey stick. Look at the number of data points to train notable artificial intelligence system. A singularity may very well be. So are we approaching a situation where you have a singularity and Ray Kurzweil's sort of theory is applicable? Now, I'm not saying this is going to go forever. Perhaps there is a point at which this stops, and there is an inflection point, and stops. But there is no question that we are pushing the limits in which it's not simply exponential, but faster than that. And then the question becomes, what are we going to do in a situation in which things are singular to the extent that we cannot predict the future with accuracy? And I think that is a fundamental question for us. And same thing in AI, publications in chemistry and chemical engineering. You see this very sharp increase also approaching a singularity state. And that's, I'm going to show you, if you use sort of a simple chemical reaction things, you can actually obtain some insights that you probably won't be able to obtain before. Finally, I want to, I think I have only five minutes left, so I'm just going to run through my approach to a chemical reaction engineering approach to contagion. This happened in 2020. I remember it. It was a Memorial Day, a vacation break. By that time, I have learned how pandemics work. They use the so-called SIR model. The SIR model, if you look at the epidemics, includes SINR as numbers of people. Now, we are chemical engineers. We understand that things don't work with numbers, but they work with concentrations. That's the most important thing. So instead of defining numbers, what if we define concentrations, how many people per, not volume, but per square meter, per area? Because we are not flooding in air to have volume, but we walk around. So this is the spirit. So based on this, I said maybe we use a chemical reaction analogy to this. So important variables should be number per unit area, because key to infection is proximity. And therefore, the more people we have per unit area, the more likely for the infection to be faster. And need to model the rates by which this population convert to one another. So this is the two equations that you use. This is a chemical reaction. S, this is now a species. This is susceptible. Interactive with J, J is infected person. And the result of this is 2J, because the S becomes J. And the other is J recovers, becomes R, or perished. And so this is a very simple model. Now sophisticated models have people who perished, don't perish, they go to the hospital and everything. But fundamentally, that's the whole thing I do. So if you use this and you use a chemical reaction engineering methodology, you can rise differential equations. And you can use reaction diffusion equations. These are mean field theories. So I'm not suggesting that they are as simple as I will describe them, and one can actually take them at a higher level. But the analogy with chemical reaction processes is the following. This subpopulation becomes a chemical species. The number densities, people per area, become molecular concentrations. Infection rates are chemical reaction rates. And mobility is a defective transfer and diffusive or dispersive fluxes. OK, all of you chemical engineers say, duh, sure, that's what it is. Well, I can tell you that epidemiologists have not done that or they are not doing that, or maybe they don't understand it, or maybe they do and they found something that it is not useful. I find this to be actually very useful. So here is my very fearless formulation of the problem. Diffusion reaction and advection. I put here at velocity everything in there. Mass action kinetics, infection rates, recovery rates, everything together. You make things dimensionless. You include inverse times and everything. And lo and behold, you get information about what is the so-called reproduction factor R0, which has been the sort of a holy grail of contagion. The reproduction factor less than 1 does not give you contagion. Reproduction factor greater than 1, all of a sudden you have contagion. And here is my definition. Sorry for all these details here. Look at the bottom here. R0 is K0 over lambda times rho. And kappa is a dimensionless parameter. K0 depends on biology. It depends on, let's say, wearing a mask, or maybe you have immunity of your own, or things of that type. Lambda is the time by which you recover, the recovery time. And rho is the density. So this definition includes a definition for R0 that I have not seen before. And it comes with a very simple numerical sort of dimensional analysis over these equations here. So we have this number here. And we play with some of the reproduction factor. It depends on parameters, density, and the extent of contagion. And you can do all kinds of things. I mentioned that infection grows exponentially if this number is greater than 1 or decays if it is less than 1. These are all simple to do. And I'm sorry that I have to go fast with this. But what we find is an expression for R0. Now, is life so simple? The answer is not. Because I made a lot of assumptions here, some sort of a homogeneity, some sort of a spatial equality of some sort. And clearly, these are not part of this necessarily part of everything in life as well. Here are some definitions. These are the infection curves. You can predict herd immunity. You can predict, this is for the typical, sorry, the typical bat's reaction problem. You can find what the herd immunity, maximum infection problem, and the duration of epidemics. Interestingly enough, duration of epidemics is longer at lower infection rates. So you can have the lower infection rate, the longer the epidemic lasts. If you have a high infection rate, it's actually shorter. This happened in 2001, or 2002. I forget when was this variant that was very, very aggressive. And I remember at the university, we had to ask the question, shall we postpone the beginning of the spring semester because of this epidemic? And I made the suggestion that if it is so intense, it will not last very long. And by Martin Luther King Day, it will be OK to do. Well, people said, eh, I don't believe you. I said, why don't you try it? And so, lo and behold, by Martin Luther King Day, things were not that bad. The university opened, everything was great. Now, let's assume you put diffusion. Now, if you put diffusion, remember, this is a chemical reaction which is not linear. Those of you experts in chemical reaction kinetics know that this problem admits a solution at constant velocity. In other words, you have waves at constant velocity, which is not characteristic of diffusion when you have linear problems, right? Because everything decays and there is no, it goes like a square root of time. So all of a sudden, you get velocities that are characteristic of these interactions. Again, I apologize for going fast on this, but you can calculate this velocity. It's given by this function here. In dimensional form, it's proportional to the diffusion coefficient that you have there and depends also on R0. So what I'm trying to say is that all this methodology and allows you to say that the nonlinear reaction rate leads to wave propagations at constant velocity and the dimension, how the velocity increases. I have one thing to show you, which is how epidemic moves here. So I have to push a button here. There is a way by which if you can push on the button there at the last infection wave, the last panel, it's a simulation. I don't know if this will show or not, and I don't know how to do it with my control here. Anyway, this shows how the wave moves forward. Or you can see it from the left panels from time t equal to 0 all the way to the end. And this shows you how the infection wave propagates in different areas. And here's another example in which I separated the in four quadrants, which have different R0. Let's say the northeast and the southwest have higher R0, meaning high intensity. The northwest and the southeast have low, let's say 2. And then we start an infection process on northeast, let's say in New York. And you can see how this is moving. Nothing's happening across the other domains. Then it goes down to the southwest part. And then you can see how infection spreads into the other domains as well. Anyway, this is not something that it is unexpected. However, you can see models of this type can give you simple explanations of infection. And here, just for those of you who are curious about what happens if you put advection only, then we created the Divergent Free Velocity field generated from Gaussian process. And you can see, as you can expect, that because of this, the propagation of waves is not as good as simple as the case of the diffusion, but actually has a lot more complication given the fact that the velocity is not uniform, but you have all this thing as well. Anyway, my time is up. I had two more slides to show, but I'll stop here. We have extended this to show that in real cases, the exponential decay that's predicted by the SIR model actually fails because social phenomena allow you the tendency of people is to relax their precautions as the infection wanes. As a result of the fact, this R0 goes up. And as a result of this, then you have an algebraic decay as a function of time. And we prove this by looking at actual data. And so there is so much interest and wealth in this area. We talk about reinfection. And I talk also about what is the R0 in superspreader events. I cannot wait to show you that. I have to show you that. So I have, if you are in a superspreader event, what happens is it's a short duration. You create infectious individuals, but they cannot infect others. They can be infected. So I call this G. So this is an example in which you have S plus i does not give you 2i, but gives you G. That G cannot infect immediately. It affects later on. I mean, let's assume I have a COVID right now. And this is a superspreader event. Let's say I, he's getting my thumbs. You're a G. You're not going to infect anybody else during the COVID event, the superspreader event. You don't have enough time to do that. So most of all the people that get this, therefore, are inactive. That makes easy to solve this problem. And you do all this math there. And then there is something called the traditional probability. There's a well-frighted, well-known phenomenon. Long story short, I can give you an R0 for superspreader events. So people were asking, what is the R0 in superspreader events? Here is the answer. R0, this is the blue description there, is proportional to two parameters, d over di. And d over di is the exposure. And di is a characteristic of inhalation and biological. And that is the final expression that I have. R0 is a function of biology-dependent parameters and operation-dependent parameters. How often you circulate the air, how tall is the building, and how packed it is. And lo and behold, this R0 is of the order of 100. So it's actually a very large number. And so when I show all this to my epidemiology friends, they said, this looks great, but too much math. So they were not happy with the math. And I said, I took a very elitist view. Unfortunately, I said, well, you cannot understand the math. Well, too bad. I should have used better communication skills, but I was kind of fended to that. And I said, OK. You don't deserve my attention anymore. Anyway, I finished this by summarizing, I think engineering, mindsets, and methods, particularly chemical engineering, can find increasing application social phenomena. I showed you some sort of hand-waving arguments for innovation, but specific, discreet, published papers with respect to contagion that essentially takes human-related stuff and make it actually doable in a different way. I very much believe that we can do a lot more of that. And second, increasing intertwining between technology society will require increased awareness, both competence and character, for engineering graduates as we are facing a world of change and of tremendous global challenges. So that's my address. Thank you so much for inviting me. It was a real pleasure for me to be here. And I hope that next, I promise next time I come, I'll bring some. So thank you very much. What's next? We have microphones in the audience. I think we have a question at the back. Oh, oh. Welcome, Professor Giorgos. I'm Lefteris Goulas. Oh, Lefteris, how are you? Very nice to have you here and congratulations. And really, thank you so much for this most inspiring talk. I just want to congratulate you for the isomorphisms between engineering and social phenomena, particularly chemical engineering. And to support what you said, to second what you said, I wanted to tell you that most of the intellectual tools we have in nuclear engineering come from chemical engineering, like diffusion theory. And particularly at Purdue, nuclear engineering was born out of chemical engineering. So thank you very much. A little bit of empirical evidence in support of the connection between chemical engineering and the rest of us. Thank you. Well, I appreciate that. I didn't know this connection, but more than happy to share it with my chemical engineering colleagues here. They are proud of this association. Thank you for your talk. I'm Nira Jane. I'm an associate professor in mechanical engineering. I wanted to ask you a little bit about your comment on the role of technology solutions and tackling something like climate. I think increasingly, as you showed, the pace of the technology development is maybe more than exponential. And I was wondering if you could comment on how engineers or scientists can either play a bigger role in trying to translate some of those solutions or how can or should we be playing a role on the policy side? Yeah. So as I mentioned, when I went to Dubai for the COP 28, I was a proponent of, obviously, sustainability and in a way that most of us are. It's an important problem, so when you go there, you realize that the problem is a lot more urgent than it is, than we require. And I think we need to accelerate whatever possibility of solution we have. I am a very strong proponent that engineering can provide the solution to that. However, it requires a mobilization in order to do that. I mean, I'm not saying this should be a Manhattan project, but there should be something really serious about how to do it. I don't think societies have come up to that same conclusion. And you can understand that there is all kinds of different opinions in there, including in this country. But the whole concept of consumption, I mean, think about consumption today and sustainability today and fast forward 100 years from now. Your kids, your grandkids, my kids, my grandkids, my grandkids, and so on and so forth. What kind of society and planet will live them? So I think this is something we need to start worrying significantly. And I don't think we are doing enough in that respect. And I think we have to give kudos to places like Stanford that realize this and created the sustainability school for that. In many of the National Academy of Engineering sessions on sustainability, it is very obvious that the clock is ticking. And we have to mobilize to do that. It's probably the overarching problem of our times. But at the same time, when you look at geopolitics, political developments across the world, they can take you down a little bit, because we can see people are looking at the wrong things. I have a solution to this. Every single politician who is in a capacity of making decisions should be shot to outer space on a capsule like this one here. Stay there maybe for a month. Look down at the earth. And then I think when they come down, they will have a very different view of their role in the world. And if you do them, then we realize that maybe there's something here worth saving. And so that's my solution. It's a little expensive. And I don't know if they will be willing to do that, but I think that's a possible solution to this problem. In all seriousness, I think there has been some movement in positive moments in COP28. However, there is also resistance. There is a significant north-south issue that has to be resolved. The so-called global south feels that they are being under, not underappreciated, they put the position. We did not result into a lot of emissions. Why are you penalizing us? And I think that is a fundamental injustice issue that has to be addressed. And the developed world has to come to terms with that and say, we've got to solve the problem. So there's a finance issue associated with that. And getting the right politicians who believe in it, I think, is going to be a positive thing. John Kerry, who I think has been a good advocate for the climate, is stepped down. So I don't know who's going to replace it in the United States. But we do need strong voices to articulate that. And I can tell you, people like John Holdren, he spoke a couple of years ago at the National Academy meeting. He was very, very compelling in his presentation. And it's available, I think, on the web. And so did the meeting that was last year with Aaron Mazumdar from Stanford and others, who talked about this very important problem as well. I think there is an urgency. I think there was a question over here. So you talked about how, in the future engineer of 2020, having the values and the type of problems that need to be solved is something that should be added. And you spoke about how you've addressed that at USC and it's had an impact. What techniques were you able to use to emphasize that as part of a college education and attract people and grow that trait? So the Grand National Scholars Program is not a curriculum program. It's outside the curriculum. So we try to, every year, we have about, graduate about 50 students. So not everyone graduates, I mean, goes to the program and requires for them to develop these five sort of competences, mindsets, if you wish, across their stay at the university. And we give them enough research problems or research ideas, or they come up with their own. And at the end of their stay at the university, then they have to prove that they have satisfied these conditions and then they graduate with that. During the COVID in 2020, we came together around last late March, actually the first year, to put together a call to action for the National Academy, actually, through the Grand Challenges Scholars Program. John Anderson, who was the president of the Academy, at the time said, why don't we make it a National Academy of Engineering-wide initiative, which we did. And it created a lot of interest and a lot of students got very motivated and interested in doing that. But I think that if we accept the fact that, as engineers, because now I'm not saying here, this is we are super people here, but I do believe that, in some different way. Having this ability to solve big problems, if we focus enough on that, I think this is characteristic of this group. There are people that will do, OK, they say, well, that's a little policy here, or maybe somebody will say, well, that's a little bit of science. As I said, leveraging phenomena for useful purposes to solve big problems, I think is characteristic to ours. And I think I am very optimistic that we can do that. And so we have a number of universities that participate in this effort. I think that the National Academy should, or an organization like this, should identify important goals for the future. Now, these goals can be valid for the next 10 years, maybe, or 15. You need some sort of a map to help you move in that direction. I'm not saying that this will be only done centrally. It can be also developed individually and on an individual basis. I think that it's time to revamp this and see where we're going. And I think there is energy for this. In the past, all this was funded by the National Science Foundation. And I'm sure the National Science Foundation will not be opposed to do that. And if anybody from the National Science Foundation listens to, punch, then maybe go ahead. Last question before we go to the panel, go ahead. So we need to create some programs in the school for that. So at USC, we're creating a program called Engineering in Society, which essentially tries to tell students of the duty and responsibility they have to make sure that they develop technologies that are useful for solving big problems and the impact they have in technology. And so I think the more we do this, the more we will create a cadre of students who really can get their reputation and the trustworthiness move up in society. I don't know whether the latest statistics have been on trustworthiness of professions. I know nurses get one of the highest. Firefighters, I think, are up there. I don't know where engineers are. Teachers, I think, maybe I'm not sure nowadays. But it will be important for us to actually elevate that statute and not be considered, you read the papers. Many of us are called tech brothers. The people that have this kind of like, it's all male oriented techies. They only care about making money or creating something. They don't have any interest in the society. I mean, they're all models that you see sometimes are questionable. I don't know the names, but you know what I'm talking about. And we've got to change the narrative. I can't see how we can tell, you know. And also be able to inject more diverse voices in this. More women for sure, more minority groups that got affected, possibly globally as well. When I was in India last week, the week before, and I can tell you that I was impressed with the effort that India is making in terms of renewable technology and the fact that they are willing to do the important things that they need to do in order to address this problem. And so if every country moves in that direction, I think we'll be able to do something good. Okay, let's, Joe will join me in saying.