The Path To Professor

Gatley Stone 0:00
Welcome wonderful weather we're having everyone. I hope you enjoy joining me today, as we have the pleasure of learning about Professor Haikal. Last semester, I took Professor Haikal's class, CE 325, Structural Analysis. I enjoyed the class and getting to know her, and I'm excited to interview her. Okay, hi, Gatley,

Ghadir Haikal 0:22
thank you so much for having me. I'm definitely happy to be part of the podcast. I think that's a great idea, and thank you so much for inviting

Gatley Stone 0:29
me. Okay, so starting off with some background questions, what is your job title and where did you get your degrees?

Ghadir Haikal 0:39
I'm an associate professor in the department of civil construction Environmental Engineering. I am part of the Structural Engineering and Mechanics group here, also part of two other groups that relate to my research. My degree is in Civil Engineering from the University of Illinois, Urbana Champaign,

Gatley Stone 0:59
and you got, did you get both your undergraduate, graduate and PhD? There? Actually,

Ghadir Haikal 1:08
no. I'm originally from Syria. I did my undergraduate degree there at Tishreen University in Latakia, that's a coastal city in Syria. And then I came to the US for master's degree, which I did at the University of Illinois, and I followed up with a PhD degree at the same university. My original plan was to do a two year degree and go back home and work in the industry, but then I enjoyed the program so much, I stuck around for a PhD. And then here we go. Here we are today.

Gatley Stone 1:39
Final background question, how long have you been teaching at NC State?

Ghadir Haikal 1:43
This is my second year. Okay, so

Gatley Stone 1:45
I didn't realize you're brand new.

Ghadir Haikal 1:47
Yes, brand new started in Fall 2022

Gatley Stone 1:50
Okay, so, um, my next question is, when you were a child, what did you want to be when you grew up?

Ghadir Haikal 2:00
That's a that's a very good question. So I

Gatley Stone 2:03
think when I think about this, it's like, I would imagine most professors, they're not, they're not like, oh, I want to be a structural engineer when I grow up. It's pretty specific, yeah,

Ghadir Haikal 2:17
for me, civil engineering was a discovery that I made later, much later, in my career, before I got my high school degree, when I was a kid, I actually wanted to be an astronaut. That was my first thought. That

Gatley Stone 2:32
was pretty common. Still, science related, though science related.

Ghadir Haikal 2:39
There was a brief period of time where I actually wanted to be in business, and that I was influenced by my dad. My dad had an advertising company, and as I grew up and I learned a little bit more about what he did, I was intrigued, and I wanted to be part of it, as I guess, part of the family business. But I think what attracted me to that was similar to what attracted me to academia is just communication with people meeting and, you know, especially advertising is how do you promote your product? And but then that was also relatively short lived. I think, as I advanced in my high school, especially as I approached high school, I enjoyed math a lot, so that switched to I wanted to be a math teacher. And shortly afterwards, I was introduced to physics, which for me, was clinched the deal I want to be in something that had to do with math and physics. I wasn't quite sure what that looked like. But then, as I, you know, came to the end of my high school career, that's, that's when I landed on engineering, because that was, for me, the, you know, the field that balanced what I liked about math and physics with also some applications. Yeah, yeah,

Gatley Stone 4:00
yeah. I find that pretty much everything we do in engineering is like physics, one that like the intro class, but you just have find different applications and go more in depth on all those Exactly, exactly. Yeah. So the next question is, were you always set on going to college, or did you consider some alternatives?

Ghadir Haikal 4:29
No, it was always college for me. And

Gatley Stone 4:31
do, do both your parents have college degrees? Yes, they do. So I guess education was, was a big part of your household.

Ghadir Haikal 4:40
It was and my mom actually was one of very few people to get an undergraduate degree at her time in Syria, and my dad had a PhD in economics. So growing up, it was always education was important, and it was very important, you know that you. It well in school, and there was a lot of encouragement. Yeah.

Gatley Stone 5:08
So how did you ultimately, did you have trouble choosing which undergraduate degree you were going to get? Like, how did you decide to go with civil?

Ghadir Haikal 5:19
Civil? Well, it was a combination of two things. First of all, the academic program, or the academic admission process in Syria, is very different compared to the US. And what happens there is, you take this national level exam, and based on your score on that exam, it determines which area, which field you can

Gatley Stone 5:45
really, wow, that's interesting. It's

Ghadir Haikal 5:47
a very stressful exam, because 1.1 way or another, could change things quite a bit for you. Yeah. And as I mentioned, I knew I wanted something with math and physics, but I wasn't quite clear about what that was. And it was up to the year, my last year in high school, when I was preparing to take that exam, that I had to start thinking really seriously, okay, what is my college degree is going to look like? And at the time, if you were doing well in school, the general idea is that if you do well, then you're going to be a doctor, you're going to go into medicine. And for me, that was a big no, because biology is not my strongest suit. I definitely wasn't. Didn't do well there. I didn't enjoy it as much, and so I wanted to do something with again, math and physics, and I was intrigued by buildings and bridges, but in my very uninformed background, I thought that that was architecture. So I actually thought that I was going to apply to the architectural program. But then when I did that, you know, final, you know, national exam, and I was looking at the areas that I was able to get into when I saw civil engineering, and, well, okay, what is still engineering, and how is that different compared to architecture? And that's where I realized that this is where I wanted to be. So I guess I was looking for civil engineering. I just realized it was called civil engineering. Yeah,

Gatley Stone 7:23
I have a pretty similar story, like I wanted to be an architect when I was a kid. But, yeah, I did, also, I was very into the math side, so I thought civil was like a nice merger of the two. Yes, exactly.

Ghadir Haikal 7:37
You get to do the fun part, right? You get to make these beautiful structures work stand up.

Gatley Stone 7:45
Yeah, exactly. I love that, yeah, yeah. So when you went from undergraduate to graduate school, did you was it like a easy decision to get a civil engineering masters. Because I know some people they'll have, they have different masters in undergrad degrees, or where you just, you knew it was going to be civil

Ghadir Haikal 8:12
Yeah, it was, for me, it was I never, I don't think I ever considered doing a different master's degree, because at the time, I was, what was driving me for graduate school was structure analysis. And I was, I wanted to understand how structures behave, how you can predict that. And I guess was focused primarily on structures. Yeah. Now that said, I realized as I went down the line that whatever we learned for structural engineering can apply to other areas as well. But yeah, my focus was always on structures.

Gatley Stone 8:46
And how did you So you went to undergraduate school in Syria, yeah. And how did you choose to study in the US versus staying in Syria or perhaps going to like England or France or somewhere, yeah, did you apply to other options?

Ghadir Haikal 9:04
I did. So after I finished my undergraduate degree, I actually signed up for a master's degree in Syria. That said it's at public universities in Syria, there is not much opportunities for funding, for research, for projects that were externally funded. So the options for what you could work on were relatively limited, and that, you know, prompted my decision to start looking into study abroad. So how I landed on the US is a bit of an interesting story. It was, for me, it was always the top destination as far as where I would, you know, this would be my number one choice. Is where I would love to go.

Gatley Stone 9:50
Is that because of funding, or you just want to live in the US? No,

Ghadir Haikal 9:54
just the appeal of the programs in the US, like their

Gatley Stone 9:58
rankings and things. Yeah, and the

Ghadir Haikal 10:02
variety of courses that you could take, if you look at European institutions, there isn't as much focus on course taking in your master's degree or your PhD degree in some places at all, yeah, but I really wanted to be in the US, because, you know, again, best universities, very diverse programs. There's a lot of different things that you could do. And however, I was restricted by funding, so I didn't have any means to support myself for a graduate program, and therefore I was looking for scholarships now in Syria, the professors that were teaching me at my university were professors that got their degrees, mostly in Europe. I didn't have a single professor who had their degree in the US. And therefore I was initially a little bit more oriented towards Europe, because asking around people were giving me suggestions for places I could apply for scholarships. And I, you know, didn't hear of any option to apply to come to the US. What happened, again, bit of a long story, but I was at the British Council, basically the British culture center in Damascus, asking for scholarships to the UK. And there was one that I could have applied to, and they said that required a TOEFL exam, that's a proficiency English, English proficiency exam for international students. And there was another exam that you could take called the IELTS exam, which is the British version. Now, I had heard of TOEFL, I hadn't heard of IELTS, so I asked where could I potentially look into taking the TOEFL exam? And they directed me to the American Cultural Center, and that's where I saw an announcement for a Fulbright scholarship. So I hadn't I didn't have any knowledge of that full scholarship ahead of time, but I I saw that that day, the deadline was in a month or so, so I scrambled to put the application together, but, yeah, that ended up working well. So I got the scholarship, and that's how I ended up coming to the US.

Gatley Stone 12:18
And so with that scholarship were that could be used at any university that you got accepted to. Well,

Ghadir Haikal 12:29
not quite so you had to, because the Fulbright Program was funding your study, they had a role in selecting the programs that you end up going to. That changes from country to country. Fulbright is an international scholarship that supports students from different countries to come to the US, but it also supports students from the US to go study abroad. So the process for Syria was that you gave them your preferences in terms of universities, and they end up deciding which one you end up going to, and that had a lot to do with how much funding is going to be required, and big part of it is if you receive any funding offers from the university itself.

Gatley Stone 13:11
So who does the applying to the University? Is it you or Okay, yeah,

Ghadir Haikal 13:17
they helped definitely with putting together the application and everything. But for me, I had four choices. University of Illinois was my top choice. And it worked out well because I ended up getting a tuition waiver from the University of Illinois, which made it, you know, so that it was very easy to provide to support me going there. And

Gatley Stone 13:41
so when, if you don't have to pay tuition, is that Fulbright scholarship going to like housing or yes, yeah,

Ghadir Haikal 13:48
yes. So they would pay you a monthly allowance that will cover your housing and any other like maintenance, like living expenses, and they pay for books and things like that. So, okay, yeah, interesting.

Gatley Stone 14:08
So after you went through your master's program, and then you went to PhD. So going into your PhD, were you, were you had you already decided that you wanted to become a professor. Were you considering going into the industry?

Ghadir Haikal 14:24
I was still undecided. When I started my PhD. I wasn't I had the preference. I was starting to develop a preference towards academia, because I was enjoying research. Yeah, but I still had in mind that I would apply to all possible potential jobs, including industry. That said, when I was in my PhD program, I was a teaching assistant for a big part of the duration of my program. And for me, that was what finalized things for me, because I really enjoyed the teaching. In, obviously the interaction with students, and by the end of my PhD program, I was 100% sure that that's what I wanted to do.

Gatley Stone 15:07
And where did you work after you got your PhD, where was the first job that you were hired?

Ghadir Haikal 15:15
I was at Purdue University as a professor for about 10 years,

Gatley Stone 15:20
yeah. And is you start off as a assistant professor? Right? Yes. And how, how were those first couple of years? Was it hard to transition? Or what was the if you're an Assistant, do you have like, different levels of research, like the amount of, I guess research funding increases as your title increases.

Ghadir Haikal 15:48
That's a that's a very good question. So when you're hired in any academic position, you get some initial funding from the university. They call it a startup package, but the goal of that is startup being many meaning just to get you started in hiring, you know, students and getting some research work going, but ultimately, you are responsible for bringing in funding from outside sources. So that's the same regardless of what level you're at. So Assistant, associate or full professor, you are still applying to get your funding from sources like National Science Foundation or department transportation or there are varying places where you can apply depending on your research focus. So going back to your question about whether the transition was hard. That was, for me, the steepest learning curve

Gatley Stone 16:45
for between undergrad, graduate and professor, yeah, and PhD. That was the steepest. That was the steepest going from PhD. I wouldn't have expected that. So what was more difficult about it?

Ghadir Haikal 16:58
So there were a few things. First of the first one was, I went directly from a PhD to an assistant professor position, which was great, but it's not what happens often, often you get a year or two as a postdoctoral associate. So with postdoctoral associates, you get some experience in writing your own research grant applications, you get a little bit more autonomy on your research program. So there's a, you know, it's considered a training period for being a professor. Now, in my case, I was very lucky that I got a position right away out of grad school, but also that made it a challenge, because I had no experience whatsoever in writing grants, all of that. So I had to learn that basically on the job. And it was, it was definitely a challenge. So if you know, for anyone who is considering doing a PhD and getting into accounting acquisition, my recommendation is at least ask your advisor to get some role in writing grant proposals before you graduate, because that's an experience that would have been very helpful to me if I had that. And then there's the sudden shift from one day you're the student and you are helping, maybe teach, but you're not the main instructor of the course to you are now responsible for everything. So as a TA, you get to play the good guy, right? Because you're helping your but you're not responsible for the content. But then, as the instructor, you are the one who's responsible for making sure that you know everything goes well in terms of, you know, planning and delivery and logistics and all of that. So there was a bit of an adjustment period there, and especially in your first year or two, as you're preparing your material, your class notes and all of that, that takes quite a lot of time, especially the first time you do it. But it's fun. It was a fun challenge, and part of it was discovering what works and what does not work. And it's definitely something that you know was, was it was it was, was a fun challenge for me.

Gatley Stone 19:13
So like currently, how would you say you split your time between between teaching and planning for classes and research and then writing grant proposals, how, what? What would you give like a proportion of your time?

Ghadir Haikal 19:34
That varies, but I think on average, I say maybe a third of my time goes to teaching, and that's in my second year. In my first year, that portion was a lot higher, because you're preparing your class notes and all of that. So now that I have material that I can use again from last year, that is about 30% and then I think the rest of it is split between. By writing grants, and you know other responsibilities, like your meeting with your graduate students. You know meetings in the department, service activities and other things that just come up, I guess, as part of your dealer, but that, I think, is about on average. Now there are times when you're close to Grant deadline applications. For example, grant application deadlines, then that shift goes much higher on the grant side. And there are things where times when you're teaching and there's an exam coming up and you need to grade, so again, that takes more time on your teaching side, yeah,

Gatley Stone 20:39
okay, shifting more into the research questions. So what is still unknown in your field and what owns what unknowns do you personally most want to know the answers to

Ghadir Haikal 20:53
that's a very wide open question, and I love that I'm in a field that has been so interesting to discover, and at the same time, it has opened a lot of doors for discovery in the future. So my work is in the field that we call computational mechanics. And the idea is we want to be able to build computer models for systems like structures that we cannot necessarily fully test in the lab. So if you think about like a large building, high rise building under seismic loading, you cannot go into the lab and test it at full scale. We can test pieces of it, but so being able to translate that very complex, three dimensional behavior of a structure to something that you can model on your computer is a very interesting combination of mathematics, some programming, and obviously a lot of physics, but that involves making a lot of assumptions about how you're going to model that system. So the structure analysis class that we had was looking at some of these methods for, skeletal skeletal structures like frames and beams, right? But obviously, if you move into three dimensional structures, that becomes a lot more complex. Now, my focus in particular is on problems that that involve interfaces. So anytime you have two domains that interact through a surface. If you think, for example, of materials like reinforced concrete, right? You have the steel and the concrete that have to talk to each other through that interface. You have materials that are composite materials in general, or even larger scale interfaces, like how the structure talks to the soil. I know we are in structures. We don't really think too much of the soil, but ultimately that has to get transfer the load right through that interface. So it turns out that there's a lot of problems with modeling these types of problems there. The methods that we have right now don't work very well for these types of interfaces, and we lose a lot of accuracy in doing so, which is an issue, because interfaces is where we look for failure mechanisms and where we rely on the interface to transfer the load. So it's very important to model that properly, and therefore that's where my work has been. How do you improve models for problems that involve interfaces. How do you leverage that to design new materials, new composites, composites that use different types of components that are maybe more sustainable or that are maybe better optimized for behavior in a specific way, and how do you use that knowledge to prevent against maybe these natural disasters. If you can model a soil structure interaction problem under seismic loading, that will help you much prepare much better for designing the structure on the extreme loading events. So so it's a field that, again, that has still a lot of unanswered questions. We are still working on different methods that potentially help solve these problems, but this is a field that also sets the stage for a lot of very nice discoveries for new materials and new types of structures in the future.

Gatley Stone 24:15
On a related note, I think this is a good question if you had an unlimited budget for to produce one paper. What experiment or research or models would you try and create? How would you use that unlimited budget?

Ghadir Haikal 24:35
I would definitely want to develop a universal computational model for all types of interfaces at different scales. So if you think about, you know, materials that have scales that at the Nano scale, for example, versus the mesoscale, as you go up into the structural level, if we can you. To develop a model that can incorporate all of these scales at the same time. I think we have a powerful tool that we can use to design all types of structures for all types of applications. So that would be kind of what I would love to be able to do. There's a lot of similarities in different types of interface problems, I think tend themselves to these types of approaches, but I don't think we have quite figured it out yet, and there's a lot of focus these days about machine learning and all of that. So I am still exploring machine learning. I'm still not 100% convinced that this is the answer to everything, because I don't think anybody is, but, you know, these are things that could potentially be we can look into leveraging more and in order to again, achieve a better design and also explore new concepts, like, I don't know, design of structures in space. I mean, I've seen a lot of projects on, okay, what happens if we want to live on Mars or right? So these are not things that we can really test in the lab, and therefore simulation can be very helpful in that regard.

Gatley Stone 26:10
Yeah, that actually combining the different scales that reminds me of in the movie Moana, the Disney movie, yes, they had, well, they had prior to that movie, they had to, they had two good models for, like, simulating water. They had, like a sort of an open ocean, one where it was like big scale, and they had like a model for, sort of, like splashing water, yeah, like it was very small scale. And one of the innovations in that movie is that they combined them exactly a more realistic scenario

Ghadir Haikal 26:45
Exactly.

Gatley Stone 26:46
I'm interested to hear your more about the AI, I think especially in the last two years. Well, probably in the last 10 years, a lot of people have been talking about AI, but has it has been, really, it's been more intangible up until the last two years, yes, and then we, we've really seen those like things that just blow your mind, like, how is this possible? So I'm curious what you think about how AI is going to change research. And also, do you think that AI will? I'm not sure what's the best word to use, but do you think it will like replace a lot of either the work or jobs in, I guess, engineering as a whole,

Ghadir Haikal 27:42
that's a that's a very interesting question too. And you have, there's different angles where you can think about that. First of all, I think the methods behind AI and machine learning, for example, is one of them have been around for a while, so I don't think we have made any discoveries in terms of, okay, now we can use this new approach to solve this problem. The methods have been there for a while. It's just that we didn't have the computational power to leverage them, and we didn't have the data to leverage them. So AI is or machine learning in general. And these are two terms that are different, but I think we think of machine learning as how we train a machine to learn what we could potentially be available through data sets. And now that we have so much data in some fields, then we can train those algorithms to recognize trends, and therefore to model things that are way too complex for the methods that we currently know. So I guess the shift has happened because there's a lot of data, and it's data that's collected through different sources, if you think, like weather data, information data, right? There's a lot of things that are now, collection devices right now, that said we have to be very careful. So I draw some similarities between the big boom in AI right now and the boom that happened in computational mechanics in my field. If you go back like 50 years ago, when computers start to become more easily accessible, and computer power becomes, you know, became more accessible, and now we can model things, rather than have to go back in the lab and test them or use some, you know, very simplified analytical methods To solve them. And what happened there is computational methods didn't replace testing. They didn't replace analytical methods. They complemented them. So now you have this additional powerful tool that you can use, if you use properly, and if you you have to be careful with how you use it, because computational methods. Are dependent on how you model the structure, how you build them. What are the assumptions that you make in making that model so? Similarly with machine learning, if you have the right data, if you have high quality data, then you're going to get a very nice machine learning model that you can use to maybe speed up your calculations, as opposed to having to go through the traditional path that said, garbage in, garbage out right. So if you don't have the right model, then you're not going to have good results. And therefore, I don't think AI is going to replace existing especially in engineering, it's kind of complemented. It's just an additional tool that if we know how to use it, and we know how to use it in a you know, informed way, then it could be very powerful, because, yes, it can help save us some complexity and some analysis tools. Maybe that may not be possible before. Now, in terms of jobs. I think it's important for, you know, the generation that's graduating now, and especially for those that are already in the workforce, and they evolve, you know, as they evolve in your their careers, to be familiar with these tools, because again, they're going to be there for you to use them. And I think the job market is not necessarily going to shift to eliminating jobs. It's just going to be more leveraging people who can use these tools better. So yeah, I don't think it's going to replace anything, per se. It's not going to eliminate anything. It's just going to be a change in how we approach solutions to certain problems. I'll give you an example of how, by limited exploration of AI or machine learning went so I was, before I joined here, I was at Southwest Research Institute in Texas for three years, and we there was a lot of interest in machine learning methods, obviously, because in industry, the appeal of having something that computes your solution very quickly is very, very attractive, right? But the problem for us in engineering is we don't have a lot of data, right? So if you think about how much data we get in terms of, you know, structural behavior, we get that from experiments in the lab, but those are very expensive, and the results are very limited, so we don't have a lot of data that we can use to train a machine learning algorithm properly. And even with the data that we have, if we train that, that algorithm has no idea about the physics behind the problem? Yeah. So in some fields, maybe that may not necessarily be an issue, but for us, we are tied by the laws of physics. So if you predict stress and strain in a specific structure, those two have to be related to each other in a specific way, and if they're not, then that's not a valid prediction. Yeah. So that we tried using AI machine learning methods, it turned out you can really easily trick it to give you very bad results, and therefore you have to be very careful in how you approach this problem. I ended up doing something that's called physics informed machine learning, meaning we basically built in the physics knowledge into the machine learning algorithm, which helped tremendously. But that means that you cannot just completely replace what we know I was our physics based models with the AI models

Gatley Stone 33:35
about the data. So for like researchers or like structural engineers around the world, do they have? Is there, like a database of data for, you know, perhaps building failures or experimental failures, and is is that like easy to access and like useful data?

Ghadir Haikal 33:56
Unfortunately, not. So there is a lot of data around the world, but it's not organized in a centralized location that everybody can access to, and that's one of the main challenges in research that you you know, you go into, you know, literature, you find a paper, you may potentially be able to contact the authors and Ask for the source data. And sometimes people are helpful and they give you that information, but not that's not necessarily always the case. There is not a single place where you can go and access everything. Now journals have have been trying to address that. So now you know some journals will require you to submit your source data your article, but that's still not organized in a way that is, you know, across the board, so you get different data structures in different formats, and that's not going to be conducive to any kind of search or anything like that. So unfortunately, it's not as organized as it could have been.

Gatley Stone 34:57
Okay, we're getting a little. It long. So I'd like to close out with some more, I guess, easy going questions, yeah, so how do you enjoy spending your time outside of being a professor?

Ghadir Haikal 35:14
Well, there's a few things that I do for fun, so I'm getting back into cycling, biking. So that's something that I used to do at Champaign Urbana when I was a student. I stopped doing it for a few years, but now I'm trying to get back into it. And there's the obvious challenge that we're not in Champaign Urbana. I don't know if you're familiar with Champaign Urbana, it's not very flat. So there's an obvious challenge here with, you know, the hills, and that's been definitely a learning curve. But yeah, mostly like, you know, exercise, a little bit. I like to do yoga, and a lot of Netflix, and

Gatley Stone 35:57
you have any favorite series or movies,

Ghadir Haikal 36:00
ooh, series I am currently watching. This is a relatively older series that I don't know if you're familiar with it. It's called monk. It's a detective. Heard of it, yeah, so that's, that's the one that I'm currently watching. I'm almost like, halfway through, and I'm enjoying it quite a bit. It has a bit of this detective approach. I mean, obviously it's, it's a fun show too, and he has a very like, distinct personality that can, yeah, it's a fun series to to watch. That's the one that I'm currently watching. Yeah, yeah. I enjoy quite a variety of, you know, movies and shows and

Gatley Stone 36:42
so we'll just end with this one. When you're not working, how often are you thinking about your field of research?

Ghadir Haikal 36:53
I try not to too much. It's sometimes it just, it's important to disconnect, right? So you want to make sure that you have that time where you're disconnecting from your work. That said, because my work is kind of my own business, in a way. So there is this constant thinking about, Okay, what was going to be the next step? What am I going to do with this part or that part? So there's, there's a bit of that that kind of infiltrates my free time. But it's also good to do that when you're more relaxed and you're kind of some of the best ideas come to you at a, you know, very unexpected time. So I try not to, you know, limit it too much. But also I don't want, I want to make sure that I get my time to disconnect from work, because that's important.

Gatley Stone 37:41
Yeah, I definitely agree. Actually, I think I will like to, I'd like to end with a more useful question. Well, not that that wasn't useful, but if you had to give some advice to an undergraduate student that's considering getting either a master's degree or a PhD and becoming a professor. Yes, what? What pieces of advice would you give them?

Ghadir Haikal 38:08
Make use of your graduate program as much as possible. You want to make sure that you find the graduate program that's the best fit for you and for your interests, and keep in mind that your interests may evolve. When I started my master's degree, I thought I was going to do earthwork engineering. And the more you learn, the more you realize that maybe not, maybe not this, maybe that. So keep an open mind, but definitely look for a graduate program that seems like a good fit to your interests. Now, being in a good program is important, but it's even more important that you have the right fit in terms of interest. So especially as you go forward with the PhD, and this is going to be a topic that's going you're going to be working on for years. So if it's not something that you're passionate about, it's not going to work out. So follow your heart, make sure that it's something that you're really passionate about, and if you are, it's something that's going to be very rewarding, because for me, it's not a job anymore, and that stopped being a job a long time ago. It's something that I enjoy. It's something that I am, you know, I take very much pride in and that also involves, you know, teaching that to my students and making sure so that they are on the right track. So you want to make sure, again, that you have this right fit with a potential advisor and that you're happy with, you know, the whole setup. So I highly recommend it. I would say at least a master's degree. Because, I mean, bachelor's is great, and I understand, you know, the maybe the wanting to get into the job market as soon as possible, but I think a master's degree gives you a much wider education and gives you a little bit more insight into, you know, talk. Mix that maybe will very helpful to you as you go down the line. But if you do decide to do a PhD and go into academia, make sure that you follow your passion, something that you are very you know enjoy doing, and that you care about very much.

Gatley Stone 40:15
Okay, that's I think that that was good.

Ghadir Haikal 40:18
Thank you. Thank you. That was fun. Yeah.

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