Quantum Computing, due to its superiority to Classical Computing, has immense potential for solving complex problems in healthcare, finance, drug discovery, and ML/Optimization—areas that directly impact people’s lives.

Utkarsh Singh, our next pathbreaker, is Senior Consultant and Quantum Machine Learning (QML) Lead at G2Q Computing, a company focused on advancing quantum technologies, while also pursuing a PhD in Quantum Machine Learning at the University of Ottawa.

Utkarsh talks to Shyam Krishnamurthy from The Interview Portal about his work on helping companies integrate quantum technologies seamlessly into their operations, which can lead to faster, more efficient solutions to complex real world problems.

For students, focus on building your skills and your confidence. Whether it’s learning online, working on personal projects, or seeking internships, keep improving yourself. Success comes from persistence, not perfection.

Utkarsh,  Your background?

I grew up in Patna, Bihar. Life wasn’t easy—my family struggled financially, and we were below the poverty line (BPL). Because of this, I studied at a government school until grade 12. Despite the challenges, I was lucky to have a great teacher at home—my dad! He has a master’s degree in geography from Patna University, and although he couldn’t get a permanent job due to the Indian reservation system, he loved teaching me math. His lessons made me fall in love with problem-solving and logical thinking.

When I was in grade 8, I qualified for a national scholarship called NMMSS-NTSE. It wasn’t a huge amount of money, but it made me realize the importance of working hard and staying determined. After grade 10, I chose Physics, Chemistry, and Math (PCM) as my main subjects because I was fascinated by how the world around us works. Physics, especially, always felt like it held the answers to nature’s secrets.

However, life taught me an important lesson early on—grades don’t define your potential. I scored only 69.8% in my 10th board exams, which disappointed many people around me, since I was always my school topper, but I learned to focus on the process of learning rather than just results. 

This mindset helped me when I faced challenges later, such as failing an important physics paper during my 2nd year of Bachelor’s in Physics. Instead of giving up, I cleared it, finished my degree on time, and kept moving forward.

What did you do for graduation/post graduation?

After finishing grade 12, I qualified for the JEE Main exam, which is for engineering colleges. While I could have joined some prestigious institute like NITs, I chose not to because I wasn’t interested in engineering. My passion was physics—understanding how the universe works at its core.

Thanks to my strong board exam scores, I was selected for the INSPIRE scholarship, which supports students in science. I joined Patna Science College for a Bachelor’s in Physics. 

After my Bachelor’s, I wanted to explore something entrepreneurial, so my friends and I started a small e-commerce company in Patna. It was an amazing learning experience, but my friends and I wanted to study more. In 2017, I appeared for the CUCET exam and joined the Central University of Jharkhand for a Master’s in Physics.

For my Master’s, I specialized in space physics because space has always fascinated me. I graduated with a 9 CGPA and decided to explore research opportunities. This led me to attend a summer school on quantum information and technology at IISER Kolkata. There, I met a professor who introduced me to the fascinating world of quantum computing. That experience set the foundation for my current career path.

What were some of the key influences that led you to such an offbeat, unconventional, and unique career in Quantum Computing?

The turning point in my career was my decision to attend the summer school in 2019 at IISER Kolkata. That single choice exposed me to a field I hadn’t explored before and set the foundation for everything I’m doing now. It’s a reminder that taking a chance on an opportunity can change your entire path.

It introduced me to quantum technology and its endless possibilities. Participating in hackathons and challenges, such as those organized by IBM Quantum, further fueled my interest. These events helped me realize how powerful and transformative quantum computing could be.

Two major influences stand out. First, my dad, who introduced me to the joy of learning, particularly in mathematics. His patience and passion for teaching inspired me to stay curious and persistent, even when life was challenging. Second, the people I met during the summer school at IISER Kolkata played a crucial role. The researchers and professors there opened my eyes to the world of quantum computing, which felt like a glimpse into the future.

I’ve been fortunate to have amazing mentors. The professor under whom I worked for eight months at IISER Kolkata not only taught me the fundamentals of quantum computing but also encouraged me to dive deeper into the subject. Later, during my PhD, my supervisor at the University of Ottawa gave me the freedom to explore my own ideas. His trust in my vision has been invaluable in shaping my research.

How did you plan the steps to get into the career you wanted? Or how did you make a transition to a new career? Tell us about your career path

Initially, I wanted to become a space physicist. My goal was to work for a space agency or conduct academic research focused on space. That’s why I chose space physics as my specialization during my master’s. My plan at that time was straightforward: complete internships related to space physics, pursue a PhD in the field, and eventually join a research center. However, my perspective shifted when I realized that much of space physics primarily revolves around data analysis rather than the hands-on exploration of nature I envisioned.

The turning point came during the summer school in 2019. It was there that I discovered the fascinating world of quantum computing. This field combined the mathematical beauty of quantum mechanics with cutting-edge technological applications. I found this much more engaging than my initial plans. Moreover, I had always been drawn to artificial intelligence, so Quantum Machine Learning (QML) became the perfect blend of my interests.

To make this transition, I started working on a quantum simulation project during my internship at IISER Kolkata. 

At IISER, I worked on a project involving the quantum simulation of ionic systems. Since it was my first exposure to quantum computing, I had to start from scratch. While I already had a physics background and understood quantum mechanics, I had no experience with the computing side of things. I took the initiative to learn Python and Qiskit, IBM’s quantum computing framework.

The project involved working on the Variational Quantum Eigensolver (VQE) algorithm, which is specifically designed for simulating quantum systems. VQE allowed us to approximate the ground state energy of a quantum system, such as ionic structures, by leveraging the principles of quantum mechanics. As I worked on this project, I became so proficient with Qiskit that my supervisor started referring other students to me whenever they needed help with quantum computing. This, although slightly delaying my project, gave me a lot of confidence in my skills and a deep understanding of quantum computing.

This experience was transformative. Not only did it teach me technical skills like programming and quantum algorithm development, but it also ignited my passion for quantum computing as a whole. 

The IISER project showed me the potential of quantum computing and gave me the foundation I needed to build a career in this field. It also taught me the importance of adaptability and learning new skills, which have continued to guide me in my journey.

My supervisor was impressed with my work and encouraged me to pursue a PhD in quantum computing outside of India. Following his advice, I applied to three institutions, and I was accepted into two of them. I chose the University of Ottawa because of the flexibility and support offered by my current supervisor, who allowed me to explore my own ideas. This was an ideal environment for someone like me, who wanted to explore his own ideas.

Unfortunately, COVID-19 disrupted many plans. I had to leave my project at IISER Kolkata unfinished and stay home for nearly nine months. During this time, I focused on preparing for my PhD, further developing my skills, and planning my career path in quantum computing. I also learned how to cook. 

My entrepreneurial mindset also played a significant role in shaping my approach to this field. From the very beginning of my PhD, I aimed to make QML closer to real-world applications. This practical perspective led to two patents and several awards during my PhD journey. Understanding the importance of industry connections, I worked on building a strong professional profile. I became certified as a Quantum Developer by IBM and later joined the Qiskit Advocate program, which allowed me to contribute actively to the quantum computing community. I participated in numerous hackathons, attended summer schools, and earned certifications to solidify my expertise in both quantum and machine learning.

After my internship at IISER Kolkata, I began my PhD in January 2021.

I chose the University of Ottawa for my PhD because of the flexibility offered by my supervisor. From the beginning, he allowed me to explore my own ideas, which was crucial for me as I wanted to work on real-world applications of quantum computing.

The problem statement for my PhD focuses on addressing the resource inefficiency in Quantum Machine Learning (QML), which is a major hurdle in making it practical for real-world applications. My research revolves around developing methods to make QML less resource-intensive while improving its flexibility and scalability.

For instance, my first work introduced a flexible way to implement Quantum Neural Networks (QNNs), allowing us to adapt resource usage based on the dataset type, significantly reducing overall resource requirements. My second work addresses one of the biggest challenges in QML—resource-intensive data encoding in quantum circuits. I developed a method that reduces this cost, making QML more accessible and closer to real-world adoption.

In parallel with my PhD, I gained valuable work experience. 

Six months later, I became a visiting research student at the National Research Council of Canada through a joint research program. I also worked as a teaching assistant at my university, which not only helped financially but also allowed me to improve my communication and teaching skills.

In 2022, I began working part-time with quantum startups, starting with a Bangalore-based company exploring QML for healthcare. Later, I joined G2Q Computing as a senior consultant, eventually becoming their Quantum Machine Learning lead and senior manager. This was a pivotal moment, as it allowed me to combine my research and entrepreneurial ambitions.

Throughout this journey, I maintained a strong focus on networking. LinkedIn became a crucial platform for connecting with professionals and companies in the quantum field. Attending conferences like Quantum Days Canada also helped me showcase my work, gain recognition, and collaborate with researchers. One of my posters presented at Quantum Days 2024 received significant attention, earning me an award and new collaborations.

Looking back, my career path has been shaped by curiosity, adaptability, and a willingness to take calculated risks. While I started in space physics, my decision to attend the IISER summer school opened doors to quantum computing, and I haven’t looked back since.

How did you get your first break?

For my PhD, the journey was already explained. It was a combination of hard work, a clear direction, and support from mentors that helped me secure the position at the University of Ottawa.

When it came to jobs, the key was consistently working on myself and building a strong profile. I focused on gaining expertise in my field, earning certifications, and contributing actively to the quantum computing community through hackathons, summer schools, and online platforms like LinkedIn. These efforts made me visible and credible in the industry, and as a result, companies began approaching me for roles.

I firmly believe that having confidence in your knowledge and abilities is just as important as the knowledge itself. Confidence played a significant role in helping me crack interviews and land all the positions I’ve held. My knowledge, combined with the assurance that I could deliver value, was what ultimately gave me my first breaks in both academia and industry.

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

Throughout my journey, I’ve faced several challenges, but they have shaped me into a more resilient and adaptive person. The biggest challenge for me has been managing multiple responsibilities simultaneously—pursuing my PhD, working with startups, participating in hackathons, and contributing to the quantum community. Instead of avoiding this challenge, I embraced it and developed strong time management skills. Over time, I became an efficient multitasker, which is one of my key strengths today.

In research, one common challenge I face is starting a project on an exciting idea, only to discover after a couple of months that someone else has already published similar work. While this can be disheartening, I’ve learned to adapt. My solutions are twofold: first, I look for ways to improve or extend the existing work; and second, I always prepare for the worst-case scenario. That’s why I make sure to work on multiple projects at once—if one doesn’t pan out, I can quickly shift my focus to another. This approach ensures I stay productive and motivated, even when setbacks occur.

In the industry, one specific challenge I’ve faced is convincing people to believe in quantum technology. Since the field is still in its early stages, some are hesitant to invest. My approach to tackling this challenge has been honesty—being upfront about the current limitations of quantum technology while also emphasizing its immense potential. Transparency builds trust, and I’ve found that being honest about where we stand is the best way to foster confidence in this revolutionary field.

Each of these challenges has taught me important lessons, from adaptability and persistence to the value of honesty and preparation.

Where do you work now? 

Currently, I wear multiple hats. I am a Senior Consultant, Senior Manager, and Quantum Machine Learning (QML) Lead at G2Q Computing, a company focused on advancing quantum technologies. Simultaneously, I am pursuing my PhD in Quantum Machine Learning at the University of Ottawa. On top of this, I am collaborating with 3-4 researchers on various projects and am currently on a three-month research visit at the University of Rostock in Germany. This visit, supported by the Mitacs Globalink Research Award, involves a collaborative project aimed at demonstrating quantum advantage by applying Boson sampling to machine learning tasks.

Additionally, I serve as a reviewer for the Quantum Journal, where I evaluate the quality and content of research papers submitted for publication. This role is an essential part of the research process, as it ensures that published work meets high scientific standards.

What problems do you solve?

In my PhD, my primary focus is on developing better algorithms for QML to bring it closer to real-world applications. I am also working on finishing my research papers and have started writing my thesis. My work often involves combining theory with practical implementations, finding ways to make quantum machine learning more efficient and applicable.

At the University of Rostock, I am working on a cutting-edge project to explore how Boson sampling, a fundamental quantum process, can be used for machine learning tasks. The goal is to showcase quantum advantage in this area.

In my role at G2Q Computing, I lead a team developing a platform for industry use. As the head of QML, I also provide strategic advisory to the company, helping clients integrate quantum technologies into their operations.

What are the skills needed in your role? How did you acquire them?

For my work, a combination of skills is essential. These include a solid understanding of quantum physics, linear algebra, and programming. Proficiency in tools like Python, Qiskit, Pennylane, and machine learning is critical. Beyond technical expertise, you need hands-on experience with real-world problems to develop intuition. I gained most of my skills through my PhD and by continually learning from online platforms like Coursera and IBM Learning. Most importantly, I’ve refined my abilities by doing what I love and staying persistent in my efforts.

What is a typical day like?

My day usually starts around 7 AM. After freshening up, I have breakfast while chatting with my family. On three mornings a week, I have meetings at 8:30 AM. Afterward, I head to my office to work on my research projects and respond to emails. I also use Slack to monitor the progress of my team at G2Q Computing.

In the afternoons, I often have meetings or fulfill my teaching assistant duties, depending on the day. I usually have lunch around 1 PM and wrap up my office work by 5 PM.

In the evenings, I head to the gym for two hours to unwind and stay healthy. Afterward, I cook dinner, relax by watching Netflix or playing video games, and talk to my family before going to bed around midnight.

What I Love About My Job?

The biggest thing I love about my work is the challenge and the thrill of working in a field as innovative and unpredictable as quantum computing. The combination of risk and opportunity excites me. I enjoy pushing my boundaries by taking on multiple responsibilities—it keeps me engaged, helps me grow, and ensures that no two days are ever the same.

How does your work benefit society? 

My work contributes to society by advancing quantum technologies, particularly in the field of Quantum Machine Learning (QML), which has the potential to revolutionize various industries. In my PhD, I focus on developing algorithms that bring QML closer to real-world applications. This research has implications for solving complex problems in healthcare, finance, drug discovery, and optimization—areas that directly impact people’s lives. For example, some of my work has shown promise in improving machine learning tasks related to Parkinson’s disease, potentially paving the way for more effective diagnostic tools.

At G2Q Computing, the platform my team and I are developing will help companies integrate quantum technologies seamlessly into their operations. This can lead to faster, more efficient solutions in industries ranging from logistics to healthcare, enabling breakthroughs that were previously unattainable with classical computing alone.

Additionally, through my collaborations and mentorship roles, I contribute to building a skilled quantum workforce. By sharing knowledge and guiding others in the field, I’m helping to shape a community that can tackle some of the world’s most pressing problems using quantum technologies.

Ultimately, my work is about pushing the boundaries of what technology can achieve and creating tools and solutions that have the potential to improve lives on a global scale.

Quantum computing involves both hardware and software, but my work is primarily algorithm (software)-based. The “quantum aspect” refers to the unique processors, called quantum processors or qubits, which are fundamentally different from classical processors. These quantum processors harness quantum properties like superposition and entanglement, making them capable of solving certain problems much faster than classical computers.

However, these processors, while powerful, are still in their early stages of development and are quite fragile, often prone to errors due to noise and environmental interference. My research focuses on the software side, where I develop and optimize algorithms to run efficiently on this hardware. Simply put, the hardware provides the quantum power, but the software I design determines how to harness that power effectively for tasks like machine learning, optimization, and data analysis. I ensure that QML algorithms are resource-efficient, making them suitable for today’s relatively small quantum processors. The ultimate goal is to prepare these algorithms for practical, real-world applications as quantum hardware continues to advance.

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

One of the most memorable works I did during my PhD ended up becoming my second patent. It was an idea born out of pure curiosity and a bit of “thinking outside the box,” which I love to do. I remember walking back and forth in my room one evening, a habit I have whenever I need to think faster. Suddenly, a simple yet powerful idea struck me, and I knew I had to test it immediately.

I began with some basic testing and was thrilled to see positive results. Encouraged by this, I decided to take it further and conduct rigorous tests to validate the idea. That’s when the real journey began. I started coding non-stop, fully immersed in the work. For four straight days, I worked without sleeping, pushing myself to the limit. By the end, my brain was so exhausted that I started feeling dizzy, seeing things in the wrong places, and behaving like someone who was super drunk.

Despite this, I managed to complete everything, got the results I needed, and finally fell asleep, utterly drained. The next day, I showed my work to my supervisor. His first reaction was, “We have to patent this.” That moment felt surreal—it was a combination of exhaustion, pride, and excitement. It reminded me that sometimes the best ideas come from taking risks and pushing boundaries, even when it means stepping outside your comfort zone.

Your advice to students based on your experience?

My advice to students is simple but heartfelt: be curious, resilient, and never give up. Life will throw challenges at you—some small, some life-changing—but how you respond to them will define your journey.

I’ve failed exams, seen poverty, been on the verge of giving up, watched my research overlap with others, and felt the sting of disappointment more times than I can count. Trust me, you will never grow or become someone extraordinary if everything always goes perfectly. You need to fail, because failure is the best teacher you’ll ever have. It pushes you to think differently, work harder, and come back stronger.

Growing up in poverty with limited resources was tough, but I didn’t let it stop me. I’ve been underestimated and faced moments when people were mean or dismissive. I’ve felt like everything was falling apart, that I wasn’t good enough. But during those times, I reminded myself of one important truth: there is no second version of you. The things you can do, no one else can. Your life is unique, and comparing it to someone else’s will only hold you back.

Never let a bad exam, a bad day, or even a bad phase define who you can be. Exams don’t measure your potential, and neither do other people’s opinions. You are capable of so much more than you think, but you must keep moving forward.

Focus on building your skills and your confidence. Whether it’s learning online, working on personal projects, or seeking internships, keep improving yourself. Success comes from persistence, not perfection. Take your own path, even if it’s different from what others expect—it’s your journey, not theirs.

Stay curious and think creatively. Some of my best ideas have come from pacing in my room, letting my mind wander, and asking, “What if?” Curiosity, combined with hard work, can take you places you never imagined.

Finally, never give up on yourself. The road will be tough, and you’ll face moments of doubt and despair. But remember: setbacks are part of the journey, not the end of it. Keep pushing forward, because your resilience and determination will shape your future. You are capable of achieving greatness—don’t let anyone, or anything, make you believe otherwise.

Future Plans?

My future plans revolve around contributing to industry, research, and entrepreneurship. I’m exploring a few paths right now. One option is to pursue a postdoctoral position after my PhD. This would allow me to deepen my expertise and attract more investment for my startups. Another exciting possibility is continuing my work at G2Q Computing while also launching a new startup through the University of Ottawa’s entrepreneurship program, which I’m already discussing with potential investors.

But here’s the truth: I don’t know exactly where life will take me—and that’s okay. What’s important is that I keep learning, improving, and staying curious. The key to planning your future is knowing that it’s okay to adapt and change as you grow.

For students, my advice is to dream big, but also be open to new opportunities. The path you take might not be what you expected, but as long as you’re passionate about what you do and committed to improving yourself, you’ll find your way. Your journey is unique—embrace it, and the future will hold exciting possibilities.

Thank You!