By Lancelot Okafor

Oluwatobi Lasisi’s journey is a testament to the power of curiosity, resilience, and human-centered thinking. From her early days as a business analyst in Nigeria’s banking sector to earning a PhD in Computer Science and Engineering in the United States, Lasisi has consistently sought to bridge the gap between technology and real human needs.

Now a UX Researcher at IBM Quantum, she works at the cutting edge of an emerging field, shaping tools that make the complex world of quantum computing more accessible and meaningful. In this interview, Lasisi reflects on the pivotal moments that shaped her path, the challenges of designing for frontier technologies, and why empathy remains her most powerful tool in both research and leadership.

Can you walk us through your journey from studying Computer Science in Nigeria to earning a PhD in the U.S.? What inspired this path?

My journey began at Ladoke Akintola University of Technology in Nigeria, where I earned a bachelor’s degree in Computer Science. At the time, I didn’t fully understand the direction I would go in, but I was drawn to technology as a tool for problem-solving. My early career took me into the banking sector, where I worked as a business analyst. It was during that time that I realized I was most excited when trying to understand people’s needs and translate them into usable solutions. That realization was the basis of my passion for UX research.

A few years later, I made the bold decision to pursue graduate studies in the U.S., starting with a master’s and eventually earning a PhD in Computer Science and Engineering from Mississippi State University. My research focus was in human-computer interaction (HCI), an area that allowed me to combine technical rigor with a deep understanding of user behavior and needs. The journey wasn’t always smooth, especially navigating a new academic culture as an international student. But those experiences shaped me; they helped me develop a research voice rooted in curiosity and resilience.

Your dissertation focuses on user-centered evaluation in requirements engineering. What drew you to that area of research, and how did it shape your broader interest in HCI?

While working as a business analyst in the bank, I witnessed firsthand how often there can be a disconnect between users’ actual needs and the solutions that were eventually developed. Requirements engineering is meant to help bridge that gap. As I delved deeper into the field during my graduate studies, I became interested in how recommender systems were being explored to support decision-making within requirements engineering. However, I noticed a clear gap; while many of these systems were evaluated for technical accuracy, essentially, how well they predicted the “right” requirements, there was little consideration for whether they were actually useful or usable from a human perspective. That observation sparked a key question: beyond accuracy, could users interpret the recommendations? Did the system genuinely support their decision-making, or did it introduce more complexity? Was it transparent and trustworthy enough for teams to adopt and rely on in high-stakes planning?

My dissertation took a user-centered approach to these questions. I moved beyond performance metrics and focused on the human perspective. That experience shaped my broader research philosophy. It reinforced the idea that the success of any tool, especially in complex or technical domains, depends not just on how smart it is but also on how well it fits into the user’s mental model, workflow, and decision-making context. That mindset continues to guide my work today, particularly in areas like quantum computing, where technology is still evolving, and the need for human-centered design is more critical than ever.

How did your time at the STaRS Lab at Mississippi State influence your research philosophy?

My time at the STaRS Lab was transformative. My experience marked a turning point in how I understood the role of technology in human-centered design. It was where I began to see research not just as a tool for discovery but as a responsibility to ask better questions, challenge assumptions, and design solutions that respond to real human needs. Under the mentorship of my advisor and in collaboration with peers from diverse backgrounds, I learned how to structure research questions that matter, how to collect data rigorously, and how to extract insights that resonate with both academic and industry audiences. I also gained hands-on experience working with real users, conducting studies, and iterating on prototypes, skills that became essential in my transition to industry research.

That experience taught me that meaningful research isn’t about following a rigid path; it’s about dynamically navigating the space between the problem space, user needs, and technological possibilities. That mindset has stayed with me, especially now that I’m in a space like Quantum where users often push the limits of what’s possible.

 Quantum computing is a highly complex and emerging field. What challenges and opportunities have you encountered while conducting UX research in this space at IBM?

UX research in quantum computing is both incredibly challenging and incredibly rewarding. You’re often working at the cutting edge of science and engineering, supporting users who are pioneers themselves. One of the first things I realised was that traditional UX methods don’t always map neatly onto this space. Our users are physicists, researchers, developers, and educators, and they often have very specialized workflows. Understanding those workflows requires not just asking questions but asking the right questions in the right language.

A major challenge has been learning how to distill complex quantum concepts into mental models that guide interface design, terminology, and user flow. Many of our users are navigating experimental tools that are still evolving. That means we’re not just studying usability. We’re often defining it as we go. On the flip side, the opportunity is immense. Quantum computing is still in its formative stages, so the design decisions we make today will shape the norms, expectations, and best practices of tomorrow. Being part of that is both humbling and exciting. It’s one of the few places where UX research isn’t just supporting innovation; it’s driving it.

You led the development of the IBM Quantum Feedback Program. What motivated this initiative, and what impact has it had on product development?

The Feedback Program emerged out of necessity. We had brilliant design and engineering teams building advanced tools, but we needed a more streamlined way to hear directly from our users frequently and efficiently. I led the design of the IBM Quantum Feedback Program to reduce the barriers to user recruitment and engagement. We built a panel of quantum users, developers, researchers, and educators who opted in to participate in user studies. By centralizing participant recruitment and building structured processes for engagement, we reduced recruitment time by over 60%, significantly accelerating our research and iteration cycles.

Insights from these user studies have directly influenced product design and development; perhaps most importantly, it has created a culture where user feedback isn’t an afterthought; it’s integrated into our process.

You have a strong background in business analysis from your time at GTBank. How has that experience influenced your approach to user experience research?

My background in business analysis has been one of my biggest assets as a UX researcher. In business analysis, I was trained to listen and ask not just what the user wants but also why. I learned how to navigate stakeholder priorities, align user needs with business goals, and communicate insights clearly to diverse audiences. These are all core skills in UX research.

Working in a high-stakes environment like banking taught me to be both analytical and empathetic. I had to understand workflows, pain points, and constraints across multiple teams. That helped me build a holistic perspective, one that I bring into every research project. Whether I’m talking to a quantum developer or a product manager, I’m constantly thinking about context, value, and clarity.

What key lessons did you carry with you from leading business teams in the banking sector into the tech and research environments?

One key lesson is that leadership isn’t just about giving direction; it’s about creating clarity and trust. In banking, I led teams through product rollouts and tight timelines. I learned to manage ambiguity, navigate conflict, and motivate teams by connecting their work to a shared purpose.

Those lessons translated beautifully into tech and research. In UX, you often work cross-functionally with design, engineering, and product teams. Being able to guide conversations, align priorities, and bring people together around user insights has been essential.

I also learned the power of humility, recognizing that you don’t always have the answer, but you can create the conditions for the right answers to emerge through collaboration.

What was the biggest mindset shift you experienced transitioning from industry in Nigeria to academia and tech in the U.S.?

One of my biggest mindset shifts was learning to sit with uncertainty and ask deeper questions. In Nigeria, especially in banking, the focus was often on efficiency, quick turnarounds, and clearly measurable outcomes. There was a strong culture of delivery; you needed to show results fast, and success was often tied to tangible outputs. Transitioning into academia in the U.S. flipped that script for me. I had to unlearn the idea that speed equals success. Research, I learned, thrives in ambiguity. It requires you to pause, explore different perspectives, and be comfortable with the fact that sometimes, the outcome isn’t a solution; it’s a better question.

Another shift was embracing a more collaborative and interdisciplinary approach to problem-solving. In academia, especially within HCI, collaboration across psychology, design, engineering, and computer science is not only welcome, it’s essential. That perspective prepared me well for tech environments where working across functions is the norm.

Lastly, coming into the U.S. academic system as an international student added another layer of adjustment. I had to navigate cultural differences, academic expectations, and even communication styles. In doing so, I built resilience, confidence, and a unique voice that blends global experience with deep technical and human-centered knowledge.

You’re certified in Enterprise Design Thinking and various UX methodologies. How do you adapt your research strategies when working on highly technical products like quantum tools?

I’ve learned from working on quantum products that the stakes are high, and the learning curve is steep for both users and researchers. Adapting my research strategy starts with understanding the problem domain and users’ mental models. These users are deeply technical and often work in experimental or evolving environments. Consequently, what would typically be straightforward usability questions become far more nuanced in this context.

My training in Enterprise Design Thinking helps me ground even the most technical work projects in user needs and experiences. I often begin with stakeholder alignment workshops to define goals, then follow with generative research like contextual inquiries, interviews, and diary studies. These approaches help surface not just pain points but opportunities for improvement.

Participatory design is particularly effective in technical domains. I sometimes co-create sketches and mockups with users to get feedback and understand their thought processes. I also adapt testing methods. For example, I might combine a usability test with a think-aloud protocol while also validating mental model alignment through card sorting or flow mapping, all depending on the problem space. Ultimately, my approach is flexible, layered, and iterative.

Could you share a story where a usability study significantly altered the direction of a product or feature?

Absolutely, one that stands out is the work we did on a feature for local testing within our Quantum Platform that allows developers to simulate quantum programs locally before deploying them to the cloud. When we initially launched the early access version, we noticed that while users were excited about the idea, they struggled to get started. Many weren’t activating the feature, and others misunderstood what it actually did. That raised red flags.

So, I led a series of remote usability studies with quantum developers to understand what was happening. What we found was eye-opening: the messaging around the feature was unclear, the activation process was buried in documentation, and there was a lot of confusion about what “local” testing really meant in a quantum context. Even seasoned users had trouble understanding how it fits into their workflow.

These insights sparked several design and documentation changes. We clarified the language, added inline guidance, and restructured the onboarding flow. We even updated the help content to align better with users’ terminology and mental models.

The impact was immediate. Feature activation rates improved, support tickets decreased, and feedback became more positive. But more than that, the study shifted our internal understanding of how critical messaging and onboarding are, especially in highly technical tools. It reinforced the idea that the most powerful features mean little if users can’t access or understand them.

When working with emerging technologies, how do you ensure your research remains inclusive and accessible?

Inclusion and accessibility are not afterthoughts; they’re foundational for building equitable technology. When working with something as complex and niche as quantum computing, the challenge is two-fold: first, ensuring that diverse users can access and understand the tools, and second, actively involving those users in shaping the tools themselves.

To keep research inclusive, I start with recruitment. I consciously try to involve participants from varied backgrounds, academic institutions, industries, different geographies, and different levels of experience.

For accessibility, I advocate for clear, plain language in UI and documentation, even when the concepts are technical. I work with designers to ensure we’re building interfaces that are not just functional but intuitive, and I push for testing that includes novice users, educators, and others who might be new to quantum.

Beyond methods, it’s also about mindset. I regularly challenge teams to ask: Who might we be excluding with this design? What assumptions are we making about our users’ skills, tools, or access? The answers often spark more inclusive thinking and better outcomes.

You’ve received multiple scholarships and awards including the Grace Hopper and Tapia conferences. How have these communities supported your growth and visibility in tech?

Communities like Grace Hopper and Tapia have been incredibly affirming for me. As someone who didn’t always see people who looked like me in advanced tech roles, being in those spaces reminded me that I belong and that my perspective matters. Receiving a GHC Student Scholarship and participating in the Tapia Conference opened doors to invaluable networking, mentorship, and even collaborations. More importantly, these experiences offered visibility and a sense of belonging. They allowed me to learn from others, build confidence, and see firsthand what’s possible when diversity is placed at the center of conversations about the future of tech.

These communities have also fueled my commitment to paying it forward. They’re a big reason I mentor, create content, and try to demystify UX research for others because I know firsthand how powerful it is to be seen, supported, and celebrated.

As someone with a strong presence in both technical and leadership spaces, how do you mentor or support other women and underrepresented groups entering tech and research?

Mentorship has always been personal for me because I know how transformative it can be. I didn’t always have access to mentors in UX or quantum computing when I started, so I’m intentional about being that resource for others.

I mentor through formal programs but also informally, whether it’s reviewing a portfolio, preparing someone for an interview, or just having honest conversations about career pivots and imposter syndrome. I also share insights openly through social media, breaking down complex topics into accessible content for aspiring researchers.

One of the things I focus on in mentorship is helping people see the value in their non-traditional paths. Whether someone is coming from psychology, business, education, or the arts, I help them frame their experiences as strengths. Diversity of thought is what makes tech more human and more impactful.

Where do you see the future of HCI and UX research in fields like quantum computing or AI?

I believe the future of HCI in quantum and AI is going to be shaped by two core needs: explainability and trust. These technologies are powerful, but their complexity can be intimidating and opaque. That’s where UX research comes in, not just to make them usable but to make them understandable, responsible, and empowering.

In quantum, we’ll see a shift toward designing tools that abstract away unnecessary complexity while still honoring the mental models of highly technical users. We’ll need interfaces that support experimentation, collaboration, and education grounded in human-centered design.

In AI, the conversation is expanding from usability to ethics. As researchers, we’ll need to understand how bias, automation, and data transparency impact user trust. We’ll also need to advocate for inclusive datasets and human oversight in design loops.

Overall, HCI is moving from a focus on efficiency to a focus on impact, ensuring that technology elevates human potential rather than replacing or confusing it. That’s where I want to continue playing a role.

Lastly, what advice would you give to aspiring UX researchers who want to make an impact in cutting-edge tech?

Start where you are, and don’t let the complexity of emerging tech intimidate you. You don’t have to be an expert in quantum computing or AI to ask the right questions. What you need is curiosity, empathy, and a willingness to learn.

Focus on developing your core research skills and then learn enough about the technology to speak your users’ language. Don’t be afraid to bring your unique perspective to the table. In fact, some of the most impactful innovations emerge from people who bring fresh perspectives and challenge the “usual way of doing things.”

Also, find your people. Join communities, seek mentors, and share your journey, whether that’s through writing, speaking, or creating content. Your voice has power, and visibility matters.

And finally, be patient with yourself. UX research is a journey, both a craft and a mindset. Keep honing both. Your impact may not always be immediate, but the long-term impact will be undeniable.