By: Michelle Cheon, Yale College '28

Dr. Jaehong Kim, Henry P. Becton Sr. Professor of Chemical & Environmental Engineering, is working to rethink how fundamental research can move beyond the lab and into everyday use. Trained in materials science and sensing technologies, his work centers on translating electrochemical systems into technically rigorous yet practical devices. That philosophy comes through in the Canary Sensor, a water quality monitoring device designed with an emphasis on affordability and real-world integration in mind.

Kim’s projects focus on technologies that can work in real-world settings. His systems are designed to be practical for everyday households—flexible enough to be affordable and responsive to the limitations people actually face.

Outside of his research, Kim has also taken on a leadership role within Yale University. He was recently appointed Head of Berkeley College, one of Yale’s undergraduate residential colleges where faculty leaders help guide student life and community programming. Last year, he was also named a recipient of a Roberts Innovation Fund award, which awards accelerator funding to support ten faculty-led inventions across AI, environmental technology, and healthcare.

We asked Dr. Kim about the development of the Canary Sensor, the challenges of bringing sensing technologies into the home, and how he approaches the transition from lab-based research to technologies designed for everyday life.
 

What problems did you see in existing household water purification systems that led your team to develop the Canary Sensor, and how does this technology change what users can reliably monitor at home?

Many household water purification systems do a good job at cleaning water, but they often feel like a “black box” to the user. People install them and assume everything is fine, yet most, if not all, systems do not have an integrated way to tell the users, day to day, whether the filter is still doing what it is supposed to do. The challenge is not only purification, but confidence: when performance gradually declines, a typical homeowner has no simple way to know when it is time to replace or service the filter.

That is the gap my team and I are trying to address with the Canary Sensor. The idea is to provide a simple warning signal tied to filter saturation and replacement timing. Conceptually, it is similar to the “canary in the coal mine” story: rather than asking users to run complicated tests, the sensor provides an early, practical indication that the system may be approaching the point where it needs attention. Our goal is to make water purification feel less like guesswork and more like something a household can monitor and manage confidently.

When you think about the Canary Sensor not just as a research project but as a potential product, what design choices were most important for making it attractive to industry partners and viable in the household water market?

When I think about a sensor becoming a real household product, I start with a simple question: will this be easy for a company to integrate and easy for a family to live with? That pushed us toward a design that is very low cost, very small, and very low power. The electrochemical sensing element is intended to be single-use but environmentally benign, and we estimate the replaceable component could be below $1 per sensor, which makes a subscription-style replacement model realistic. The device is also designed to be about the size of a thumb, so it can be incorporated into existing systems without requiring a major redesign. Another important design choice is electricity consumption. We wanted something that can run off the electronics already present in many under-sink systems, or even a coin battery for faucet-mounted units. Finally, we care a lot about adaptability. Different settings care about different water quality targets, so we aim for a platform where the sensor surface can be modified for different monitoring needs over time, including beyond household drinking water.

You’ve helped build pathways for Yale technologies to move from the lab into real-world deployment. How do you think about entrepreneurship as part of engineering practice—especially when designing solutions for communities with very different constraints?

Entrepreneurship is simply the continuation of engineering with real-world constraints turned on. In the lab, you can optimize performance under controlled conditions. In the world, you have to ask whether the solution fits how people actually use it, maintain it, pay for it, and trust it. That is why early engagement matters so much. Through NSF I-Corps, I learned firsthand that it is very hard to correctly identify the best target market from the beginning. Our view of the “right” first application and beach-head market changed substantially after extensive customer discovery and many conversations with potential users and stakeholders.

That process is even more important when you think about communities with very different constraints. The technical approach may be similar, but what determines success can shift: affordability, maintenance burden, replacement logistics, and even how information is communicated can matter as much as the sensor itself. So I try to approach entrepreneurship as a structured listening exercise—learn the constraints early, then design so the technology can realistically work within them.

As director of KCITY (Korea–Center for Industrial Technology–Yale), you lead partnerships between Yale Engineering and Korean industry. KCITY has already enabled collaborations between Yale researchers and Korean companies. What role do you see KCITY playing in moving these kinds of technologies toward commercialization and broader impact?

From my perspective, KCITY’s most important role is that it encourages industry-focused research and supports long-term relationships that make translation more likely. Many academic projects only begin thinking seriously about commercialization late in the process. KCITY shifts that starting point earlier, because the projects are built around meaningful engagement with industry partners from the beginning. That does not mean the research becomes “development work,” but it does mean researchers are more likely to choose problems and milestones that connect to real deployment pathways.

I also think KCITY helps with a practical challenge I see all the time: aligning the scientific frontier in academia with the technology frontier in industry. Yale Engineering faculty are doing a lot of work that companies are genuinely excited about, but it can be surprisingly hard to find the right match in timing, goals, and language. KCITY aims to create a structure where matchmaking is part of the mission, and relationships can grow over multiple projects rather than being one-off interactions.

Overall, how have the resources and collaborations at Yale shaped your ability to develop and translate technologies like the Canary Sensor?

Roberts Innovation Fund has been especially helpful at the stage when an idea is exciting and plausible, but still too early for most external funders. Internal support like this gives researchers room to pursue “blue-sky” concepts long enough to generate the first solid evidence and build initial prototypes. That matters because high-risk, high-return work often does not fit neatly into traditional grant categories, even when the potential impact is clear.

For the Canary Sensor, that flexibility helped me move from a back-of-the-envelope idea to a more concrete technology concept. It enabled iterative testing, practical design refinements, and the kind of learning you only get by building and troubleshooting real prototypes. The sensor is still at an embryonic stage, and there is more work ahead, but the Yale ecosystem has helped us take steps that make translation realistic.