The new multi-organ chip has the size of a glass microscope slide and allows the culture of up to four human engineered tissues, whose location and number can be tailored to the question being asked. These tissues are connected by vascular flow, but the presence of a selectively permeable endothelial barrier maintains their tissue-specific niche. (Image: Kacey Ronaldson-Bouchard/Columbia Engineering)

Columbia University is a private Ivy League research university in New York City. Established in 1754 as King's College on the grounds of Trinity Church in Manhattan, Columbia, is the oldest institution of higher education in New York.

The Fu Foundation School of Engineering and Applied Science (popularly known as SEAS or Columbia Engineering; previously known as Columbia School of Mines) is the engineering and applied science school of Columbia University. It was founded as the School of Mines in 1863 and then the School of Mines, Engineering and Chemistry before becoming the School of Engineering and Applied Science.

Columbia Engineering is organized into nine departments including Applied Physics and Applied Mathematics; Biomedical Engineering; Chemical Engineering; Civil Engineering and Engineering Mechanics; Computer Science; Earth and Environmental Engineering; Electrical Engineering; Industrial Engineering and Operations Research; and Mechanical Engineering.

Research Areas

An actor robot runs on a playpen trying to catch the visible green food, while an observer machine learns to predict the actor robot's behavior purely through visual observations. Although the observer can always see the green foods, the actor, from its own perspective, cannot due to occlusions. (Image: Columbia Engineering)

From environmental sustainability and the human genome to infrastructure sensors, nanotechnology, and data sciences, Columbia Engineering is at the forefront of many strategic areas of research. Its major cross-disciplinary research is conducted at Data Science Institute, the Earth Institute, the Zuckerman Mind Brain Behavior Institute, as well as the Columbia Nano Initiative, and the Precision Medicine Initiative.

The many interdisciplinary institutes, centers, and initiatives at the school are equipped with the latest technology, tools, and equipment. These also include Artificial Intelligence at Columbia, Columbia-IBM Center for Blockchain and Data Transparency, Center for Financial Engineering, Center for Life Cycle Analysis, Center for Neuroengineering and Computation, Computational Optimization Research Center, Earth Engineering Center, EnHANTs Center, Industry/University Cooperative Research Center for Advanced Studies in Novel Surfactants, and Lenfest Center for Sustainable Energy.

Technology Development

The faculty and students at Columbia Engineering are doing pioneering research across departments and disciplines, governed by the school's vision — Columbia Engineering for Humanity — that sets a bold path for a sustainable, healthy, secure, connected, and creative humanity.

Columbia engineers recently created a robot that learns to visually predict how its partner robot will behave, displaying a glimmer of empathy. This “Robot Theory of Mind” could help robots get along with other robots — and humans — more intuitively. The study, conducted at Columbia Engineering's Creative Machines Lab led by Mechanical Engineering Professor Hod Lipson, is part of a broader effort to endow robots with the ability to understand and anticipate the goals of other robots, purely from visual observations.

The SIFTER system deployed at ColumbiaDoctors. (Image: Columbia Engineering)

Columbia Engineering researchers have developed a computer vision algorithm for predicting human interactions and body language in video, a capability that could have applications for assistive technology, autonomous vehicles, and collaborative robots. Their algorithm is a step toward machines being able to make better predictions about human behavior, and thus better coordinate their actions with humans.

The mathematical framework developed by the researchers enables machines to organize events by how predictable they are in the future. The technique could move computers closer to being able to size up a situation and make a nuanced decision, instead of a pre-programmed action, the researchers say. The algorithm is a critical step in building trust between humans and computers.

Engineered tissues have become a critical component for modeling diseases and testing the efficacy and safety of drugs in a human context. A major advance from Columbia Engineering team demonstrates first multi-organ chip made of engineered human tissues linked by vascular flow for improved modeling of systemic diseases like cancer.

A team of researchers from Columbia Engineering and Columbia University Irving Medical Center have developed a model of human physiology in the form of a multi-organ chip consisting of engineered human heart, bone, liver, and skin that are linked by vascular flow with circulating immune cells, to allow recapitulation of interdependent organ functions.

The researchers have essentially created a plug-and-play multi-organ chip, which is the size of a microscope slide, that can be customized to the patient. Because disease progression and responses to treatment vary greatly from one person to another, such a chip will eventually enable personalized optimization of therapy for each patient.

Scientists at Columbia University have developed a highspeed 3D microscope for diagnosis of cancers and other diseases that they say could eventually replace traditional biopsy and histology “with real-time imaging within the living body.”

Schematic of the bridging of the cold quantum world and high-temperature metal extraction with machine learning. (Image: Columbia Engineering)

The technology is designed to enable in situ tissue analysis. Known as MediSCAPE, the microscope is “capable of capturing images of tissue structures that could guide surgeons to navigate tumors and their boundaries without needing to remove tissues and wait for pathology results,” according to the research team.

The way that biopsy samples are processed hasn't changed in 100 years. The 3D microscope overcomes many of the limitations of prior approaches to enable visualization of cellular structures in tissues in the living body. It could give a doctor real-time feedback about what type of tissue they are looking at without the long wait.

Columbia Engineering researchers have developed a “cloaking” system that temporarily hides therapeutic bacteria from immune systems, enabling them to more effectively deliver drugs to tumors and kill cancer cells in mice. By manipulating the microbes’ DNA, they programmed gene circuits that control the bacteria surface, building a molecular “cloak” that encapsulates the bacteria.

According to the researchers, this system gives them the ability to regulate the time that bacteria survive in human blood, and increase the maximum tolerable dose of bacteria. The system also opens up a new bacteria delivery strategy in which they can inject bacteria to one accessible tumor, and have them controllably migrate to distal tumors such as metastases, cancer cells that spread to other parts of the body.

A new low-cost system developed by a team of Columbia researchers can continuously screen multiple people for fever with no human interaction, significantly lowering human labor cost of screening and social interaction.

The system, called SIFTER, can automatically take temperature readings of people walking by, going about their own business, up to three meters away — no one has to stand in front of a camera for a few seconds to take a measurement. And no one needs to be there to read the measurement and approve the person's entry.

SIFTER uses smaller numbers of low-cost sensors, can run continuously in different environmental conditions, and can screen multiple people simultaneously. The entire end-to-end system is fully automated, needing no one to manually take measurements or analyze the results. Its embedded software is open-source and the hardware costs less than $500 to set up and operate.

Engineers at Columbia have also invented a method that combines quantum mechanics with machine learning to accurately predict oxide reactions at high temperatures when no experimental data is available. It could be used to design clean carbon-neutral processes for steel production and metal recycling.

The new computation technique, through combining quantum mechanics and machine learning, can accurately predict the reduction temperature of metal oxides to their base metals. The team is now working on extending the approach to other temperature-dependent materials properties, such as solubility, conductivity, and melting, that are needed to design electrolytic metal extraction processes that are carbon-free and powered by clean electric energy.

Technology Transfer

Columbia Technology Ventures is the technology transfer office for Columbia University. For more information contact This email address is being protected from spambots. You need JavaScript enabled to view it. or call 212-854-8444.



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This article first appeared in the August, 2022 issue of Tech Briefs Magazine.

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