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Where did you grow up?

I was born and raised as the fourth of five children in West Berlin, an island within East Germany surrounded by the Berlin Wall until 1989. As my mother was walking to the hospital on my birthday, she walked down Gregor Mendel Street, named after the Austrian monk and biologist who laid the foundation for the laws of genetic inheritance, and the name stuck with her, being an agricultural researcher married to my microbiologist and physician father.

I attended the Technical University of Berlin to study energy and process engineering, the same institution as Albert Einstein, though it was referred to as Royal Technical Academy of Berlin then. My later years at university were a time of great historical disruption, while during my undergraduate studies I had opportunities to pursue industrial internships at Siemens Energy (where I helped assemble an 80 MW gas turbine) and Ems Chemie in Switzerland (developing heat recovery solutions for thermally intensive polymer production). In my final year I received a Fulbright Scholarship, following in the footsteps of my brother, allowing me to study in the United States. Only ten days after I found out about my Fulbright selection, the Berlin Wall fell, and history forever changed.

What was your experience as a Fulbright Scholar?

The Fulbright Commission’s selection has had a significant impact on my life and one that I am forever grateful for. I chose Oregon State University where I completed my MS in mechanical and nuclear engineering. My experience gathered in internships during my undergraduate nudged me more toward the mechanical and energy engineering side rather than chemical engineering. My time in Oregon was personally remarkable as I met my wife Martha and explored some of the natural splendor of the American West; it was a pivotal life experience. Towards the end of my time in Oregon we took a road trip east, and that was the first time I set foot on the campus of ���Ҵ�ý�ƽ������. Walking around the campus in Boulder on a glorious August day, I decided that this was where I had to do my PhD. I applied and was accepted to the mechanical engineering department the following year, but when I arrived none of the opportunities spoke to me, instead I was attracted to research going on in the Civil, Environmental and Architectural Engineering, focused on improving the demand side of the energy equation. With the help of my mentor, professor, and now friend Prof. em. Michael Brandemuehl I switched departments, and I got hooked on this subject.��

How did you start your research career?

After completing my PhD, I went into industry, working for Johnson Controls as an energy engineering manager, where I oversaw the energy analysis of large building portfolios, developing so-called energy savings performance contracts for buildings throughout central Europe. I worked with a small, motivated team solving interesting and challenging real-world problems, but after four years I was tempted back into academia for a deeper look at energy problems. I was approached by the University of Nebraska-Lincoln with an exciting opportunity, to be part of a team to setup a new school, a new undergraduate degree, and a new graduate program. That is what led me to become a founding member of the Durham School of Architectural Engineering and Construction (DSAEC). Standing up this school and these programs was both a challenging and fulfilling time for me, and I learnt much, not just about being a professor, but also about building academic programs and community.

After nine years at the DSAEC, in 2008, I was approached by ���Ҵ�ý�ƽ������, and one of the big draws for coming - in fact returning after 13 years away - to Colorado was the emerging relationship between NREL and CU and the opportunity to become involved in the creation of RASEI. I was drawn to the chance of building something new and to work on a wide range of energy challenges with colleagues from NREL and CU.

Can you sum up your current research in one sentence?

Improving building-to-grid integration through advanced control approaches and decarbonizing urban energy systems through electrification and community heat management.

Explain a little more about what that means

I have had the great fortune to be involved in a number of rich research areas over the years, but recently I have been drawn to explore different ways in which we can connect portfolios of buildings together so that they can work synergistically to drive down energy costs.

Architectural engineers have historically explored strategies for improving energy efficiency at the level of individual buildings, looking at ways to optimize energy use and drive down waste, developing best practices like the LEED certification, net zero energy building design, advanced controls, passive cooling, and natural ventilation, that led to individually more efficient buildings. This work grew and evolved but recently led us to the conclusion that we were missing an opportunity, namely, how buildings could collaborate.

Buildings consume ~ 40% of the total energy and ~75% of the electricity used nationwide. That is split about 45:55 between commercial and residential buildings. There is a vast untapped potential of nationwide savings if we can impact commercial building energy use at scale. If we eliminate the use of gas to heat buildings and move to electrically-driven heat pumps, we would make huge strides to wean ourselves from fossil fuels, increase energy efficiency, and operate buildings more affordably. In existing urban contexts, this includes the question of how to best select and then interconnect buildings together.

A timely tangent is datacenters. Their deployment is and will continue to rise because of AI, so how can we better use them? The large number of servers in a datacenter are essentially electric heaters. Yes, they are crunching data to power our AI chats, but they are also heating the environment and a great deal of downstream work is required for cooling. What if we tap into this resource by connecting a datacenter to other buildings that need heat, so we make use of what would otherwise be considered waste?

Our work shows that interconnected buildings can be more resilient and more reliable, i.e., being interconnected provides a host of benefits. Urban systems, in particular commercial buildings using heat pumps can be very efficient. When you have a group of nearby buildings, they commonly have diverse thermal demands, one building needs to be heated, and one needs to be cooled, and these can work together. We can assemble an ensemble of buildings that maximally benefit from each other. Then, we think about the topology of the building network, how best to connect them together, how to minimize the pipes and infrastructure that connects them together. Once you have collected a network of buildings, each node in the network is more resilient, if one goes down there is redundancy built into the shared system.

A research area that has recently emerged is called thermal energy networks, or TENs, which involve a shared network of water-filled pipes that transfer heat in and out of buildings. These neighborhood-scale systems allow buildings to exchange heat with several energy sources, such as lakes and rivers, energy-intensive buildings, data centers, wastewater systems, or the stable temperature of the earth.��Further, TENs��use shallow geothermal boreholes to harness the relatively constant thermal energy within the earth, then transfer that to all buildings on the network. These boreholes can capture and store excess heat underground for use days or months later, using the earth as a thermal battery and flattening peak electricity demand.

Instead of high-pressure steam and chilled water being separately circulated around a campus, one can instead circulate near-ambient water in a TEN. In each building, in place of all the heating and cooling hardware required, you only need a small energy transfer station and a few heat pumps. It is far more energy efficient and takes up less space. We can model how the pieces all fit together, what the different needs are for heating and cooling across the network, and how the resources can best be shared.

We have an interesting project currently that investigates how this can be applied, exploring how one could best place a datacenter in the urban fabric of Chicago. We are building a model of how the waste heat from the datacenter could be used to heat commercial and residential buildings in the community. This is an opportune way of getting the most mileage out of the electricity we use, instead of just exhausting waste heat into the environment, we can harness it for use in other buildings.

Another area that my team is looking at is energy flexibility. In a power grid, supply must always meet demand. Conventional fossil-based power systems are considered demand-following, where powerplants can be turned up when the demand increases. We are in the process of transforming our electric grid system to behave in a source-following fashion. Wind and solar are intermittent and uncertain, so how do you design a grid so that energy can be used in different ways, i.e., to be responsive to such a source-following model. How we approach these questions has been some of the work that has for the last four years connected me to the International Energy Agency (IEA).

Say a little more about your approach to international collaboration.

I always strive to find diversity in my work to keep engaged and passionate, and I have found this in several different forms, from startup companies to international sabbaticals. I have had the opportunity to work with different teams in countries across the world, and the current work I am doing with the IEA is a highlight. For the last four years, I have been involved in two international working groups, specifically, Annex 82 and 96. Annex 82, titled Energy Flexible Buildings Towards Resilient Low Carbon Energy System, for which we recently published a major report, has been a great deal of fun! With the help of common exercises I designed, I was able to engage with teams from all over the world, and together we were able to analyze a wide range of building portfolios, in different locations and environments, and explore the benefits and limitations of energy flexibility in these different scenarios. Energy flexibility, previously explored through model predictive and reinforcement learning control approaches, is a cheaper alternative to large-scale deployment of electrical energy storage to keep the lights on in a renewables-dominated electric grid. This was a significant undertaking, but one that was made possible by multinational collaboration, and one that proved to be personally rewarding. IEA Annex 96, titled Grid Integrated Control of Buildings, is the follow-on working group I am involved in. The effort aims at enabling buildings to participate as flexible demand assets in energy systems and to enable trustworthy, automated, cost-effective trading of flexibility resources from buildings, at scale.

Since 2005 I have made a point of seeking opportunities for international collaboration in how I have approached sabbaticals. I have spent extended time periods working at research organizations and companies such as the Fraunhofer Institute for Solar Energy Systems (in Freiburg, Germany), Siemens Building Technologies (in Zug, Switzerland), and Eurac Research (in Italy), and I collaborated with the department of electrical engineering at the Universidad de Sevilla in Spain, and another fantastic research stay at the CSIRO Energy Center in Australia. The position in CSIRO brought me back to the Fulbright Commission 30 years after my exchange from Berlin to Oregon, since I was awarded the Fulbright Distinguished Chair for Science and Technology award for that year. All these rewarding opportunities gave me a chance to connect with researchers from across the world, learn about new approaches, and share new and exciting ideas, which is one of the greatest gifts of being a professor. Lastly, I have hosted from and sent to Europe (Germany, Ireland, Italy, and Switzerland) many research assistants over the last quarter century, emulating the inspiration I gained from Senator James W. Fulbright.

You mentioned your entrepreneurship, could you say a little more about that?

This has added a new dimension to my life, and I am involved in three startup efforts. In 2008, I co-founded a company called QCoefficient together with a power systems engineer and industry veteran, which was at the forefront of so-called building-to-grid integration, maybe too far ahead of its time. At that time the power grid didn’t communicate with buildings in any substantive way, and buildings didn’t communicate well with the grid, that was the gap we planned to fill with continuous integration of HVAC system operation into the electric grid system to participate in a host of energy services that normally supply-side assets are responsible for. Our focus was, and still is, on a few large commercial buildings in grid-constrained urban cores continuously responding to real-time prices and demand response incentives, generating price relief and thus a community benefit. QCoefficient had crafted a unique joint collaborative research agreement with CU Venture Partners using a shared foundational patent, allowing students over the last 17 years to contribute to technology development while pursuing their graduate degrees.

A second startup I have been involved in as co-founder and scientific advisor since 2023 translates the technology and CU-held IP of a recently completed ARPA-E grant that I led to new application domains. Whisper Energy develops energy efficiency strategies enabled by wireless sensor networks and AI-based sensor fusion algorithms utilizing an ensemble of sensor nodes that estimate occupancy count, operational equipment efficiency in industrial facilities, and indoor environmental quality. This effort, funded by a CU Lab Venture Challenge grant, brings me together with a long-time collaborator from Rutgers University in NJ and is led by an energetic CEO based in Southern California. We are currently developing new hardware prototypes and demonstrating them at upcoming investor meetings to facilitate a first venture capital raise.

The third and most recent entrepreneurial venture started in 2025 and focuses on operational faults in buildings. Think about modern cars, we diagnose what is wrong with a car using standardized diagnostic protocols, going into the garage where they plug a computer in the car to diagnose the problem. What if we could do that with a building? Instead of trying to look at all the hardware for the problem, what if a suite of algorithms could give us an easy health check? This area is called automated fault detection and diagnosis, or AFDD.

Although it looks like an obvious opportunity, this has proved to be a hard nut to crack for several decades. One can use physically motivated fault rules to find faults in a building, but every commercial building is a unique, you may say, a snowflake. It has proven challenging and time intensive to translate a set of generalized fault logic rules to a specific building and create a bespoke rule set for it. A lot of AFDD fault rules have been found to be trigger happy, causing false positives, and frequently overwhelming building operators with a deluge of faults, not all of which are real. This causes skepticism for the technology. One still needs to have a person in the building to confirm the fault theory and address it. However, there is an inspiring upside potential for those who do solve this challenge, as there can be between 15-30% saving in operational energy and cost that could be achieved. Insidiously, often you don’t detect if something is wrong as the many interconnected building systems frequently compensate each other’s shortcomings, an effect we call the graceful degradation of buildings. So, it could seem like a building is fine, with no problems, but in fact they are hidden and causing the building to use far more energy than it would otherwise be if operating as designed.

Combining principles of AFDD with the power of generative AI, both large language models and emerging machine learning approaches is what we are working on with a new company called Clima Technologies, where I am serving as chief scientist, that aims to uncover operational faults and ensure energy efficiency. Taken together, I have enjoyed working with research teams in the entrepreneurial space, translating research into meaningful improvements for the built environment.

What advice would you give to someone interested in working in this area?

There are attractive opportunities for those considering going into building energy systems engineering, fault detection, and advanced controls. I foresee a large workforce gap coming, but one that could come with interesting opportunities. There are knowledgeable people working on building energy efficiency and in buildings controls, but not enough young people coming through to address the emerging workforce needs. I believe it will be an impactful and relevant application space for AI. AI alone could not work by itself, since diagnosis of an issue requires a field person to determine and verify an issue, but a combination of building operators enabled by a “building AI” could be an effective approach. Gathering and codifying the knowledge and experience from experienced operators who will soon leave the workforce to train and power such AI agents could prove a valuable resource for the next generation of building optimization.��