Satellites are watching us all the time; they hold immense potential in unlocking the key to many innovations that benefit humanity.

Guneet Mutreja, our next pathbreaker, Doctoral Researcher at German Aerospace Center (DLR), focuses on building intelligent AI systems that can instantly  process and understand satellite images, based on un/self-supervised algorithms

Guneet talks to Shyam Krishnamurthy from The Interview Portal about the moment when he realised that Geospatial technologies and space data aren’t just about pixels and, code but also about understanding human behaviour, societal needs, and governance.

For students, be the Bridge: The most unique and valuable careers today happen at the intersection of different fields.

Guneet, can you share your background with  our young readers?  

My name is Guneet Mutreja. I am currently a  doctoral researcher at the German Aerospace  Center (DLR) in Munich, which is like Germany’s  version of NASA.  

I grew up with a science background and was  always fascinated by computers, which led me to  pursue a formal education in computer applications.  In school and college, I was like many other  students, thinking that a career in computers meant becoming a software developer in a big IT  company. My path seemed straightforward, but a surprise that was waiting for me that would  change everything.  

What did you do for graduation/post graduation?  

I completed my Bachelor’s in Computer Applications (BCA)  from JIMS college in Delhi, followed by a Master’s  in Computer Applications from SASTRA University  in Thanjavur.  

Think of these degrees as learning the language of  computers. We learned how to build software,  create applications, and solve problems using code.  At that time, I was convinced my future was in the mainstream IT industry, building applications or  managing software for big clients. My education gave me a strong technical foundation, but my real  career was about to begin in a field I didn’t even know existed. 

What were some of the influences that led you  to a career in Deep Tech, Satellite based Remote  Sensing?  

Honestly, I didn’t choose this career at first; it chose  me! It was a series of fortunate events, driven by a fantastic mentor and some fascinating problems that turned me into a detective.  

The most important person was Dr. Raman  Srinivasan, the director of the TCS Ignite labs where I started as a trainee in 2016. Instead of  just pushing me down the typical software developer path, he saw a spark of curiosity in me.  

One day, Dr. Srinivasan showed me a tool called  Google Earth Engine. Imagine a search engine, but instead of searching for text, you can search our entire planet through decades of satellite images.  He simply said, “Try this out.” That was the turning  point. The domain of Remote Sensing  (understanding the Earth from space) was completely new to me. It took me months to  produce even a small result, but I was hooked. This  led to some incredible “detective” projects. For  instance:  

a. The Case of the Red Rivers: Dr. Srinivasan  shared a memory of flying over Dhaka,  

Bangladesh, and seeing the city’s flooded roads looking strangely red. Years later, he asked me  to investigate. I became a digital detective, scrolling through satellite images from the date he gave me. The answer was fascinating: a few days before the flood, the festival of Eid had taken place, where people sacrificed goats on the streets. When it rained heavily, the water mixed with the remains, colouring the streets red. My investigation also revealed a societal  problem: there were too few government –  provided slaughterhouses, leaving people with no choice.  

b. The River Diversion Mystery: He also came to  me with a major concern about the Tsangpo river  (which becomes the Brahmaputra in India). There were reports that China might be planning to divert this massive river. My task was to use satellite data to calculate the water flow and understand what the  impact would be downstream in India. Working on  real-world puzzles like these felt more exciting than any software development job I could imagine. I started teaching this topic to hundreds of other trainees. Winning a few challenges organised by Google further fuelled my passion. This journey took  me from TCS to Esri, the world’s leader in mapping  software, where I even got to work on a use case  for NASA scientists. It was related to grounding line detection for glaciers and satellite images using deep learning and AI. It was NASA’s project to quantify melting ice in glaciers because of climate change.  

That’s when I decided I wanted  to go deeper and truly become a scientist myself.  

How did you make a transition to a new career?  Tell us about your career path 

My career path wasn’t a straight line; it was a series  of stepping stones, each one leading me to a more interesting place.  

My main approach was to stay curious and say  “yes” to challenges that seemed impossible or  strange. Instead of having a rigid five-year plan, I  focused on learning the next interesting thing right in front of me.  

TCS Ignite (My “Accidental” University) was where I  transitioned from a computer science graduate to a  geospatial enthusiast. My job was not just to work but to learn and then teach others. This forced me  to understand the subject deeply.  

TCS offers science graduates an opportunity to pursue MCA  from SASTRA university while being employed full time through their Ignite program. 

Moving to ESRI was like going from a university lab to a Formula 1 team. ESRI is a US based GIS software company around 56 years old. It’s flagship product include ArcGIS  Pro, CityEngine used by 90% of Fortune 500  companies. It is by far the top GIS company globally.  

Here, I worked with the  best tools in the world and solved real problems  for major clients, including NASA. It  professionalised my self-taught skills.  

I also did a post graduate diploma from IITM in Applied Data Science and Machine Intelligence to  upskill myself with Machine Learning. The course was pretty extensive and helped me a lot with  understanding the AI domain.  

After working in the industry, I realised I had a lot of  practical knowledge but lacked the deep scientific understanding. I wanted to move from being a user of science to a creator of science. That’s why I chose to pursue a PhD. It’s my way of earning a formal degree in the field I fell in love with by accident.  

I am at Remote Sensing Technology Institute at the  German Aerospace Center. My department includes Scientists from remote sensing domain. There are multiple institutes at DLR in different domains. I applied through DLR-DAAD fellowship program which had an open position for PhD for one of the topics I was interested in (Unsupervised learning). 

So, I applied and got interviewed which I cleared.  The process was pretty smooth and did not include any exam, only a couple interviews. This DLR DAAD fellowship program can be considered as an industry PhD program full time at DLR. However, as DLR is not an academic institution but a research  institution, I had to register in a university of my choice in Germany towards the end of my PhD to defend my work and get an academic degree. So I chose Osnabrueck university.  

How did you get your first break?  

My first break wasn’t a job offer or a promotion. It was that simple moment when my mentor, Dr.  Srinivasan, showed me Google Earth Engine and  trusted a fresh trainee with a completely new and  unconventional path. That single act of trust was the  “break” that opened up this entire world for me.  

What were some of the challenges you  faced? How did you address them?  

Coming from a different background meant  my journey had its share of challenges, but  each one was a learning opportunity.  

Challenge 1: The Knowledge Gap: My degrees  were in computer applications, not geography or remote sensing. When I started sitting in meetings with Earth scientists, I often felt like an outsider because I didn’t know their vocabulary or basic  principles.  

How I addressed it: I became my own teacher. I  spent countless hours reading books, watching online courses, and treating it like I was doing a  second Bachelor’s degree all by myself. I was  driven by the fear of not being able to contribute and the desire to understand.  

Challenge 2: The Speed of Technology: I work at the intersection of three fast moving fields:  Computer Science, AI, and Remote Sensing.  There’s a new AI model or a new satellite launched  almost every few months! Staying up-to-date is a  huge challenge.  

How I addressed it: I accepted that I have to be a lifelong student. I dedicate time every week just to  reading new research papers and trying out new tools. You can’t just learn once and be done.  

Challenge 3: Being a “Translator”: Because I  understand both the computer science world and  the Earth science world, a big challenge is translating between them. Sometimes scientists don’t know what’s possible with AI, and sometimes AI experts don’t understand the scientific problem.  

How I addressed it: I learned to use analogies  and simple explanations. I see myself as a bridge  between these two worlds, and communication is  the most important skill to build that bridge.  

Where do you work now? What problems do  you solve?  

I am a doctoral researcher at the German  Aerospace Center (DLR).  

What problems do you solve? 

Every day, thousands of satellites capture  petabytes of images of our planet. The problem is,  this is too much data for humans to look through. I  am working on building a smart assistant, almost like a “ChatGPT for satellite images.” The goal is to  create a system ;where a user, like a farmer or a  disaster manager, can upload a satellite image and  simply ask questions in plain language, like: “How  much of this forest has been lost to fire?” or “Are the  crops in this field healthy?” My work is to build an AI  that can understand both the question and the  image to give a useful answer.  

What skills are needed for the job? How did  you acquire them?  

1. Computer Programming: The foundation from my  Bachelor’s and Master’s.  

2. AI and Machine Learning: Mostly self-taught,  driven by curiosity, and now being formalised during my PhD.  

3. Remote Sensing Knowledge: Learned through years of self-study and hands-on project work.  

4. Curiosity and Problem-Solving: This is the most important skill, and it comes from the “detective” mindset I developed early on.  

What’s a typical day like?  

It’s a mix of being a student, a detective, and an inventor. A part of my day is spent reading the  latest scientific papers. Another part is spent  programming and running experiments, trying to  teach my AI models to understand satellite images. And the best part is collaborating with other scientists, discussing ideas, and tackling big problems together.  

What is it you love about this job?  

I love the “Aha!” moment. It’s the feeling you get when you’ve been working on a complex problem for weeks, and suddenly, your code works, and an  image from space reveals a secret about our  planet. It’s the thrill of discovery and the knowledge that our work could help us better understand and  protect our world.  

How does your work benefit society?  

My work is focused on making the knowledge  hidden in satellite images accessible to everyone,  fast. Think about the biggest challenges facing the  world today: climate change, natural disasters (like  floods and fires), and feeding a growing population.  

Satellites are constantly monitoring all these issues,  but the data is often too technical or too massive for  the average person or local official to use quickly.  

By building intelligent AI systems that can instantly  process and understand satellite images, we are  providing crucial tools for society:  

Disaster Response: If a flood happens, my AI can  quickly map the extent of the damage, showing  rescue teams exactly which areas are worst hit.  

Environmental Monitoring: Governments and  scientists can track deforestation or monitor water pollution changes in real-time, helping enforce  environmental laws.  

Sustainable Farming: Farmers can use this  technology to check the health of their crops,  optimizing water and fertilizer use, which is  essential for global food security.  

Essentially, I am helping turn mountains of complex  space data into immediate, actionable insights that can save lives, protect the environment, and build a  more sustainable future.  

Tell us an example of a specific memorable work  you did that is very close to you!  

The memorable work that I often return to is the “Red Roads of Dhaka” story that I mentioned  earlier. It wasn’t just a technical challenge; it was a  deeply human one.  

When I started the investigation, it was just a  technical puzzle: Why is the water red? Using the  satellite images, I confirmed the time, the area, and  the connection to the holiday sacrifice. But what made it memorable was the realization that the red  water was a symptom of a larger social issue—the  lack of accessible municipal facilities for the  community.  

It showed me that my work, using advanced  technology and space data, wasn’t just about pixels  and code. It was about understanding human behavior, societal needs, and governance. It was  the first time I felt like a true investigator who wasn’t  just solving a math problem, but uncovering a truth that had real-world implications for thousands of  people.That experience solidified in me the belief  that geospatial science is truly a powerful field for social good.  

Your advice to students based on your  experience?  

If I could give three pieces of advice to young students from 8th grade to graduation, they would be:  

1 . Don’t Chase the Trend , Chase the Problem: Everyone will tell you to choose the “hottest” career—the latest AI job or the best engineering stream. Forget the labels! Instead, find a problem that genuinely fascinates you, a puzzle you can’t stop thinking about (whether it’s about space, oceans, poverty, or healthcare). My own career path appeared only because I chased fascinating problems (like the red roads) rather than chasing a specific job title (like “software developer”).  

2. Be the Bridge: The most unique and valuable careers today happen at the intersection of different fields. If you are good at science and writing, you become a science communicator. If you are good at computers and geography, you can become a geospatial scientist (like me!). Don’t discard any of your interests, even if they seem unrelated. Learn to connect them—that’s where innovation happens.  

3. The Degree is the Start, Curiosity is the Engine:  Your formal education (your BTech, your MSc) is  your license to drive, but your curiosity is the fuel.  My formal education was in computers, but I taught myself remote sensing and AI because I needed those skills to solve the problems I cared about.  Never stop being a student, and understand that today, you can learn anything online if you are determined enough.  

Future Plans?  

My immediate plan is to successfully complete my  doctoral research, pushing the boundaries of how AI can interact with Earth observation data.  

Looking further ahead, I see myself continuing to work at the cutting edge of science and technology. I want to develop my conversational  AI system into a widely adopted tool that  governments, NGOs, and researchers worldwide can use instantly to address global challenges.  

Ultimately, I want to bridge the gap between  complex science and practical application.  Whether that’s through a startup, working in a  global organization like the UN, or continuing research, my goal is to ensure that the secrets  hidden in satellite images are unlocked for the  benefit of humanity. I want to build systems that  help us make smarter decisions about our one and  only home, Planet Earth.