Hey there! Welcome to the Marketer Of The Month blog!
We recently interviewed Asteris Apostolidis for our monthly podcast – ‘Marketer of the Month’! We had some amazing insightful conversations with Asteris and here’s what we discussed about-
1. Significance of balancing innovation with operational demands.
2. Emerging technologies in aviation.
3. The complexity of certifying AI-based technologies in aviation and building trust in autonomous systems.
4. AI’s pivotal contribution to realizing sustainability objectives within the aviation industry.
5. Obstacles associated with expanding the scope of electric and hydrogen aviation.
6. The vital role of Digital twins and simulation methods in aviation operations.
About our host:
Dr. Saksham Sharda is the Chief Information Officer at Outgrow.co. He specializes in data collection, analysis, filtering, and transfer by means of widgets and applets. Interactive, cultural, and trending widgets designed by him have been featured on TrendHunter, Alibaba, ProductHunt, New York Marketing Association, FactoryBerlin, Digimarcon Silicon Valley, and at The European Affiliate Summit.
About our guest:
Asteris Apostolidis is a Technical Innovation Lead at KLM Royal Dutch Airlines, where he oversees the implementation of cutting-edge technologies like AI and Digital Twins across various company departments. His aero expertise comes from roles at academic institutions, airlines, and aircraft manufacturers across four nations.
EPISODE 142: AI Takes Flight: Royal Dutch Airlines’ Tech Innovation Lead Asteris Apostolidis on Aviation Tech
Table of Contents
Saksham Sharda: Hi, everyone. Welcome to another episode of Outgrow’s Marketer of the Month. I’m your host, Dr. Saksham Sharda, and I’m the creative director at Outgrow. co. And for this month we are going to interview Asteris Apostolidis who is a Lead for Technical Innovation at KLM Royal Dutch Airlines.
Asteris Apostolidis: Great to be here. Thank you.
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Or you can just listen to it on Spotify!
The Rapid Fire Round!
Saksham Sharda: So let’s start with the rapid-fire round.
Asteris Apostolidis: Sure.
Saksham Sharda: At what age do you want to retire?
Asteris Apostolidis: 65.
Saksham Sharda: How long does it take you to get ready in the mornings?
Asteris Apostolidis: Oh, ages, because I do prepare my three kids.
Saksham Sharda: Most embarrassing moment of your life?
Asteris Apostolidis: Oh, a lot of them.
Saksham Sharda: You can always pass. Favorite color?
Asteris Apostolidis: Blue.
Saksham Sharda: What time of day are you most inspired?
Asteris Apostolidis: Late at night.
Saksham Sharda: How many hours of sleep can you survive on?
Asteris Apostolidis: I can survive on six hours.
Saksham Sharda: Okay. fill in the blank. An upcoming aviation trend is ______.
Asteris Apostolidis: Sustainability.
Saksham Sharda: The city in which the best kiss of your life happened?
Asteris Apostolidis: Tulus, France.
Saksham Sharda: Pick one- Mark Zuckerberg or Elon Musk?
Asteris Apostolidis: None of the two.
Saksham Sharda: The biggest mistake of your career?
Asteris Apostolidis: Pass.
Saksham Sharda: How do you relax?
Asteris Apostolidis: Listening to music.
Saksham Sharda: How many cups of coffee do you drink per day?
Asteris Apostolidis: None.
Saksham Sharda: A habit of yours that you hate?
Asteris Apostolidis: Overthinking.
Saksham Sharda: The most valuable skill you’ve learned in life?
Asteris Apostolidis: To be agile.
Saksham Sharda: Your favorite Netflix show?
Asteris Apostolidis: Breaking Bad.
Saksham Sharda: One-word description of your leadership style.
Asteris Apostolidis: Relaxed.
Saksham Sharda: A top priority in your daily schedule.
Asteris Apostolidis: Connect with people.
Saksham Sharda: Memorable career milestone.
Asteris Apostolidis: Completing my PhD.
Saksham Sharda: A recent business innovation that caught your eye.
Asteris Apostolidis: For personal disruption stimulation.
The Big Questions!
Saksham Sharda: Alright, so that was the end of the rapid fire. And the rest of the questions you can answer with as much time and ease as you like. Did you save for your most valuable skill? It was learning how to be like a baby.
Asteris Apostolidis: Agile.
Saksham Sharda: Alright. So, question one, the long-form questions. You have a diverse background with experience in both academia and the aviation industry. Can you share some key insights from your journey, including how your academic experience in computational aero thermodynamics has influenced your role in leading technical innovation at Dutch Airlines?
Asteris Apostolidis: Yes. So a quick story. I started mechanical and through this journey. I love the dynamics. So I started thinking about the next step. There was a moment in time when I decided that I wanna follow a career in aerospace or aviation, you know, like traveling, flying. It’s like something that I like, gives me this kind of sense of freedom. So, well, I did a PhD after my first degree in computational aerothermodynamics. Back in the day, I thought that I would follow carrying an aerospace manufacturing show, like working with the plane manufacturers. However, life had other plans for me, and I switched to aviation at some point. However, the skills I learned during my Ph.D. and my studies well, I consider them very valuable. Why? Knowing how systems are designed makes you also understand how systems operate. So I entered this kind of AI and data science space with the paramount knowledge of systems to tell something that I find very visual daily in fact working with those systems. And from an AI perspective, it means that you have to build with the way you work. And I had this paramount, this kind of power career taught me a lot. However, I haven’t decided yet whatsoever, like more academia or the industry. I let them both equally and that’s why I keep switching, or at least I always keep a part of the two during my career. So, well, I currently also work as a visiting academic at the same time as my industry career.
Saksham Sharda: So how do you balance the need for innovation with the operational demands of a large airline like KLM? And what strategies have you found effective in driving innovation within such a complex organization?
Asteris Apostolidis: That’s a very good question. Companies like KLM have all kinds of different departments under the same roof. So think about the company building passenger and commercial operations flight operations, basically fly ground operations. They need to be serviced on ground catering maintenance. I can keep going. And so to show the basics in this kind of setting it’s, you know, you can get inspired a lot, but you can also get distracted usually. So you need to somehow isolate yourself from this kind of very fast-paced operating environment and try to think, well, you know what? I could improve in this kind of environment because you see that in professional environments there are all kinds of deficiencies here and there. I mean, like, you know, things always go the wrong way and then you need to react to that. And I think the biggest innovations will come from the space where you can improve this kind of operational coordination between different departments and within the departments. And that’s also something that’s a practice that has sustainability because, well, whatever deficiency you have when it comes to the way that plane flies, the way that place is maintained, the way that planes are handled on the ground that usually means extra time, extra resources, extra missions, and so on. So basically optimizing aviation and airlines is specifically defined as non non-practice of handling.
Saksham Sharda: So could you give us some examples of the most exciting emerging technologies in aviation that you’ve been involved with and how they’re impacting the industry?
Asteris Apostolidis: Yeah, so lots of things are happening in innovation these days, and again, there’s a lot of discussion about how to be more sustainable. So in that sense, AI plays like people in making a more sustainable, for example, plane supply for let’s say, well decades now, but the way we optimize the route in the sky or the way practice flying, like fuel consumption can, for example, improve and optimizing AI, that’s very interesting space. Also, you can use a set of different technologies that work with data. So have this kind of real-time data feed. And then on top of that you have layers that can be predictive, that can be like monitoring different parts of the organization, assets, and so on. And those layers, like I’m talking about IP things like that. So developing these means can help you monitor your operations and even predict disruptions, predict things that might happen in the future. Because again, things can always go wrong. It’s a very sophisticated environment in this kind of setting. That’s a very interesting technology. And the last example, technology is what is happening right now with all those new energies, new energy source aircraft talking about hydrogen or sustainable waste fuels, biofuel. I’m talking about electric or hydroelectric aircraft and so on. And that is a space where, well, things are moving. This is solely because this kind of transition is very difficult because of its method that it’s worth doing. And I think we’re gonna see the results of this effort in the coming decade.
Saksham Sharda: So what’s the future of electric?
Asteris Apostolidis: Well, electric has a specific particularity and batteries are heavy, so we see a lot of applications for electric, but I expect to see electric planes flying in regional settings. So in shortfall but already like an improvement.
Saksham Sharda: So to pivot a little, you co-chair the data management and machine learning design subgroups of the SAE G-34 / EUROCAE WG-114, the joint international committee for the certification of artificial intelligence-based technologies in aviation. Could you tell us more about the challenges and considerations when it comes to certifying AI-based technologies for aviation and how this impacts the safety and reliability of aviation systems?
Asteris Apostolidis: Right. I’m gonna start with the question. Let’s say that we board an aircraft and fly somewhere and then the captain makes an announcement. The captain says, well, good morning, welcome to apply to x, Y, and z. Today a plane is not inspected by a human operator inspected by an algorithm. My question to you is, would you, this plane, and would you fly with a plane that no human operator can inspect? It’s different mechanicals, sure, well, that summarizes the work we do there. But what we try to do there is develop the standards, practices, and mechanisms that can assure that AI can be implemented in critical aviation systems in a way that tracks working and can be certified. I’m talking about mechanisms, aircraft management, and ions, for example, replacing one pipe with some kind of algorithm-based example. That’s a very thorough job because of that from the manufacturers, people coming from airlines, people coming from academia, people coming from the regulators. We have worked for four years now, and hopefully next year the standard will be out and the standard can be adopted by the regulators. So we will be able to certify AI in a way that we can trust. Of course, the first steps might not be that the first application might be some small maintenance applications, but in that case, those applications will be running autonomously without any human intervention. And of course, by building trust ourselves to the standard and also the public to the algorithms. We can proceed because one thing is the trust and the standard itself and how we develop it, but also the public needs to understand and feel comfortable with both technologies and craft technologies, their lives of technologies. That’s the big question here.
Saksham Sharda: That sounds highly complex. Can you share any insights into the collaboration and coordination efforts required between industry stakeholders, regulators, and technology developers to create certification standards for AI-based technologies in aviation?
Asteris Apostolidis: Yeah, it’s a very complex process. The work group involves 500 people from all around the globe. And we have worked like four years so far, and we have at least one year before we have the standard. So you can imagine that involves lots of coordination. Also, meetings were times of the day because everyone needed to be present. But I think it’s worth the effort. So we organized into different subgroups their scope and I was very lucky to have co-chaired the data management subgroup and the machine learning group. In those meetings, we have regular meetings with the people there where we like to bring up topics for discussion. And based on those discussions, we form some kind of opinions and some kinds of practices that we think are the ones that we need to follow. And then we put those discussions into papers. So basically we like to write down what we discuss and now we think it’s like the way to go. And this then it’s up for debate, up for discussion. This document has been discussed for a long time. We make the right amendments and show on, and at some point, we adopt the document paragraph by paragraph. So this is the way we work. And then it takes time and effort. Alright. Yes. And well, on top of what I just described, basically we need people coming from all kinds of different sides of the industry. So when people come from the operational side, airlines come from the design side, so aircraft factories and also AI experts. So it’s a complex work with a lot of stakeholders, but yeah, well, I’m very optimistic that in the end, we’ll have very good standards for the industry.
Saksham Sharda: So pivoting to sustainability a little, sustainability is a significant focus in the aviation industry. How do you see the role of innovation and AI in achieving sustainability goals? And what are some specific initiatives or strategies that you’ve been involved in to promote sustainability?
Asteris Apostolidis: Yes, sustainability, right now it’s well, I can say the number one objective for the aviation industry. The aviation industry is a very difficult industry to carbonize. For one reason, planes need to fly in place to live enough to fly. So in that sense well the best thing we have right now in terms of energy density, fuel, and of course fuel is apart from the environment. So on the one hand we need to reduce and at the same, in the end, eliminate fuel consumption and also make sure that the planes are light enough to fly. So if you replace something, different planes need to be light enough. So AI can play a very important role in this kind of discussion. First, because using AI can optimize our practices, and our operations, so can use AI, optimize use at operations, you can understand and get all kinds of insights about the way that fuel is consumed onboard the aircraft and optimize here and there all kinds of small operational practices and like, have somewhat quite good improvements in fuel consumption. And of course, AI these days is used in a very extensive way in designing aircraft. And, in the past, we used to have more traditional methods. We used to have physics-based methods. We still have some extent, but AI right now is at the core of the design methods for aircraft. The aircraft that are being designed right now are the next-generation aircraft that can work with different fields, work with sustainability, and so on. So AI is first of all part of the operational improvement process, but also in the design processes and products.
Saksham Sharda: And what role do innovations like electric aviation play in this context of sustainability?
Asteris Apostolidis: Yes. Well, electric aviation, or hydrogen, can be used in different ways like direct combustion or with fuel cells, which is also electric aviation. It’s, you know, I think we all are very important in carbonizing locations. We won’t have results tomorrow. I expect to have results in the next decade for both electric and hydrogen. But yes, I think the most important challenge here is how we can scale up the production of hydrogen, how we can reduce the weight of batteries, and how we can make those systems fit within the vehicle itself. Second, those aircraft fit in the existing operational requirements that the airports like etc.
Saksham Sharda: Speaking of this in extension simulation methods and digital twins are integral in aircraft design and maintenance. Can you elaborate on the importance of simulation methods and digital twins in the aviation industry as a whole, and how they contribute to efficiency and safety?
Asteris Apostolidis: Yes, that’s a very good question. Well if you see an airline microscopically, like you know, from above, it’s a huge optimization, you need to optimize everything and at the same time provide scheduling. Things need to come together. And right now, the way that we approach that kind of is that we optimize like independent innovation in general, but don’t optimize. So in that sense, by developing these areas, combine different parts of the organization and at the same time visualize the impact of this kind of, for example, some kind of operational destruction. You can have, because first of all, people can see how, what is the operational status of an organization. Second, by using AI in the digital twin can predict different scenarios about how the operations, this direction they can take or simulate all kinds of different scenarios about what can happen if we have some kind of disruption in this way, we can improve possible experience.
Asteris Apostolidis: Because you can imagine that if your flight is canceled, well you’re frustrated, then we can, we need to act quickly on that. And at the same time, of course by bringing together all kinds of different operational parts of the organization, like of an airline or the industry sometimes. So think about the traffic management, you know, like combined operations things like that. We’ll be able to optimize the waste. We also work to make sure that people understand what is the situation, the status of specific operational parts and you know, like take the right action.
Saksham Sharda: So what are the key challenges that aviation faces in adopting these digital twins more widely and how can these challenges be overcome?
Asteris Apostolidis: Well, yes, digital twins are very up-and-coming and very nice technology. But of course, there are always challenges. First of all, I’ll start with the fundamentals of this data. So data is something that needs to be there. It needs to be available and it needs to be also curated in a way that those trees can consume. And that’s not always in place because we see not just in our lives, but in general, again, innovation data are coming from all kinds of different directions. So data correction is very important and data quality is very important. So I think that’s one of the best challenges. How you can use and like source data in a good way. That’s one thing. Also, data is protected by, well most of the time, all kinds of property rules and laws and like agreements. Data can also be protected by agreements with the gaps, personal data, pilot data, and those kinds of things are present. So if we start with fundamentals, I think bringing together data in a way that can facilitate the development of these is a very important step. That’s step number one. Then of course you need some, let’s say algorithms and some methods that can provide data and that can provide prediction capabilities. If we talk about prediction. And that’s the second step. And of course, I talked before about combining different parts of the operations, and those operations are not always run by the same organization. Think about airlines and traffic management. So bringing together different organizations and developing together, we are talking with different parties and stakeholders right now and how to collaborate, and coordinate on developing this kind of simulation. It takes time, but I see the value and I think everyone sees the value showing, again, not optimistic. An organization that can come together and bring operational efficiency and at the same time sustainability and at the same time disruptions that are fortunate by developing a variety of topics.
Saksham Sharda: So the last question for you is of a personal kind. What would you be doing in your life, if not this right now?
Asteris Apostolidis: Frankly, I’m very passionate about what I do now. So, well, for me, what I do is work and if not, I think it is not a vision space. I like space and I follow all the developments in the space domain as a hobbyist.
Saksham Sharda: Thanks, everyone for joining us for this month’s episode of Outgrow’s Marketer of the Month. That was Asteris Apostolidis who is a Lead for Technical Innovation at KLM Royal Dutch Airlines.
Asteris Apostolidis: Pleasure. Thanks for having me.
Saksham Sharda: Check out the website for more details and we’ll see you once again next month with another marketer of the month.