Dr. Shruti Sharma on Helping Deep Tech Founders Turn Strong Science Into a Clearer Path Forward

The materials scientist and innovation ecosystem builder works with early-stage ventures on the practical decisions that help complex technologies move toward customers, partners, pilots, and funding.

Deep tech founders often know their science better than anyone in the room. They can explain the mechanism, the data, the prototype, and the technical promise with precision. The harder part begins when someone outside the research environment asks a different set of questions.

Who is the first customer? What problem is urgent enough to drive adoption? What has been validated outside controlled conditions? What would make an investor, public agency, utility, industry partner, or customer take the next step?

Dr. Shruti Sharma has spent years working with founders at that point of translation. As a materials scientist, technology commercialization professional, and innovation ecosystem builder, she helps science-based ventures move from technical promise to a clearer commercial path. Her work has supported more than 100 deep tech startups and founders across energy, life sciences, engineering, advanced materials, and AI-enabled technologies.

In this conversation, Sharma discusses the gap between invention and adoption, the questions deep tech founders need to answer sooner, and why commercialization requires more than enthusiasm for a promising idea.

Many founders assume that if the technology is strong enough, the path forward will become obvious. That is rarely how it works. A strong technical explanation does not always answer what a customer, investor, or partner needs to know.

A founder may be able to explain why the science works, but the person on the other side of the table may be asking, “Why should we adopt this now? What risk are we taking on? What changes for us if this succeeds? What evidence do we still need?”

That is where a lot of teams get stuck. They are not lacking intelligence or commitment. They are too close to the technology to see where a new person enters the conversation.

It often begins after the research has shown promise, but before the market has given a clear response. That stage can be difficult because the technology feels real to the team, but the commercial path may still be undefined.

I help founders step back and ask practical questions. What has actually been proven? What still needs to be tested? Who is the first user? Is the problem urgent or simply interesting? Is the right next step a company, a pilot, a grant, a licensing opportunity, a partnership, or more development?

Those questions can be uncomfortable, but they are necessary. Commercialization is not the same as cheering for an idea. You have to care enough about the technology to ask the hard questions before the market asks them for you.

At the Long Island High Technology Incubator, I helped design and launch venture development programs that evaluated and supported emerging technologies. Within the first few months of one such program, more than two dozen technologies and startups were reviewed.

That work moved very quickly from broad potential to sharper questions about readiness, market direction, customer need, and commercialization strategy. Some teams needed to rethink their first market. Some needed a clearer use case. Others needed help separating what had already been validated from what they still hoped would be true.

The lesson was that early support needs structure. It is not enough to tell founders their technology is exciting. They need a process that helps them identify risk, test assumptions, and decide where to focus next.

Deep tech rarely follows a simple route. An energy technology may need utility partners or demonstration sites. A materials company may have to prove performance at scale. A life sciences venture may need a specific validation path. An AI-enabled technology may need a narrower first customer before it can make a convincing case for growth.

The timelines can be longer. The technical risk can be higher. The stakeholders can be more varied. A team might need to speak to investors, customers, public agencies, institutional partners, and technical reviewers, and each group may define progress differently.

That is why deep tech founders need more than a polished pitch. They need to understand what kind of uncertainty they are asking someone else to accept.

I graduated from the Indian Institute of Technology Bombay and later became the first-generation woman in my family to earn a Ph.D. in materials science and engineering in the United States. That training still shapes how I listen.

I am not only listening for the story around the technology. I am listening to the technical foundation underneath it. What works in controlled conditions? What might change outside that setting? What has been measured? What has been assumed? Where could performance, cost, scale, or reliability become an issue?

That scientific lens matters because commercialization should not flatten the science. The goal is not to make complex work sound simple in a way that becomes misleading. The goal is to preserve the depth while making the opportunity easier for others to evaluate.

They may lead with the wrong information. A founder might describe performance gains, while a customer wants to know how difficult adoption will be. A researcher might focus on novelty, while an investor wants to understand timing, scalability, and risk. A public-sector partner might care about economic development, sustainability, or infrastructure impact.

None of those questions means the technology is not important. It means the founder has to understand the person they are speaking to.

Part of my work is helping teams hear all of those questions without losing the technical center of the idea. You do not want to oversimplify the technology, but you also cannot expect every stakeholder to enter through the scientific details first. You have to give people a way into the problem.

Those groups often support innovation in theory, but they do not always measure progress in the same way. Researchers may think in terms of technical validation. Investors may look at risk, timing, market size, and growth. Public agencies may care about deployment, economic development, sustainability, or infrastructure impact. Customers may care most about adoption cost, reliability, and whether the solution fits their existing workflow.

Because I have worked across technical evaluation, commercialization planning, venture development, and innovation programs, I can help founders prepare for those different conversations before they are already deep into a pitch or partnership process.

My work has extended into federally supported technology commercialization initiatives, including Department of Energy-funded programs focused on energy innovation and technology transfer. In those efforts, I contributed to proposal development, partnership-building, program structure, and evaluation metrics designed to help research-based technologies move closer to practical deployment.

Those program details can sound administrative from the outside, but they matter. For early-stage technologies, the structure around the founder can change the trajectory. The right evaluation process can surface risk earlier. The right partnership can open a pilot opportunity. The right commercialization program can help a research team stop circling assumptions and start testing the ones that matter.

I have served as a mentor and evaluator for national innovation programs, including NSF I-Corps, and as a reviewer or judge for initiatives connected to NSF, DOE, ASME, and AAAS. Across those settings, the technologies change, but the pressure points often repeat.

Teams need to know who their first users might be. They need to test whether the problem is urgent. They need to understand who has decision-making power. They need to know what evidence would make a partner or customer move forward. They also need to know when enthusiasm is hiding a weak assumption.

The earlier founders face those questions, the better.

Do not treat commercialization as a separate phase that begins only after the technology is finished. Start learning from the market early, even if the product is not ready.

That does not mean abandoning the science. It means building a better understanding of the path around the science. Who has the problem? How do they experience it? What are they doing now? What would make them change? What proof would they need? What would make adoption too difficult?

A founder may start by thinking the main task is to explain the invention. Over time, the stronger task becomes explaining the case for action.

It answers why this problem matters, why this user matters, why this moment matters, and why this path makes sense. It connects the technology to a decision someone else can make.

That shift changes the pitch. It also changes how the founder understands the venture. The founder stops only describing what has been built and starts explaining what should happen next.

Not every promising technology should become a startup immediately. Not every technical breakthrough has the same commercial future. Some technologies may be better suited for licensing, partnership, pilots, grants, or further development before a company is built around them.

My work is to help founders see those distinctions before time, funding, and momentum are spent in the wrong direction.

Clarity can be the difference between a smart idea and a serious venture. It changes how founders speak to customers, how they plan pilots, how they approach investors, and how they decide what to build next.

I am not trying to make complex science sound simple. I am helping founders explain the business case with the same care they brought to the technical work.