Forward-thinking problem-solving research | NYU Tandon School of Engineering

Forward-thinking problem-solving research

Our research doesn’t just result in new technology; it results in a better world because we’re focused on solving tomorrow’s problems today.

Andre Taylor with students in lab

Whether we’re pushing the boundaries of AI and robotics, using big data to better understand the challenges facing society, making mobile networks more powerful, keeping cyber-systems safer, exploring the possibilities of augmented and virtual reality, partnering with medical clinicians for a healthier populace, addressing vital issues of sustainability, or making an impact on all things urban, Tandon researchers are on it.

Keeping nanomagnetic computing cool

Logic and memory devices, such as the hard drives in computers, now use nanomagnetic mechanisms to store and manipulate information. Unlike silicon transistors, which have fundamental efficiency limitations, they require no energy to maintain their magnetic state: Energy is needed only for reading and writing information. One method of controlling magnetism uses electrical current that transports spin to write information, but this usually involves flowing charge. Because this generates heat and energy loss, the costs can be enormous, particularly in the case of large server farms or in applications like artificial intelligence, which require massive amounts of memory. Spin, however, can be transported without a charge with the use of a topological insulator — a material whose interior is insulating but that can support the flow of electrons on its surface.

In a recent Physical Review Applied paper, Shaloo Rakheja, an assistant professor of electrical and computer engineering, and her team introduce a voltage-controlled topological spin switch (vTOPSS) that requires only electric fields, rather than currents, to switch between two Boolean logic states, greatly reducing the heat generated and energy used.

There’s a simple analogy to explain the impact of switching between two states more effectively: Imagine if you were preparing a recipe and had to go into a different room anytime you needed an ingredient before returning to the kitchen to add it. It’s just as inefficient when the portions of computing hardware needed to do a calculation and the portions needed to store it are not well integrated.

Fishing for solutions to invasive species

Soaring mosquitofish populations have decimated native fish and amphibian populations, and attempts to control the species through toxicants or trapping often fail or cause harm to local wildlife. Maurizio Porfiri, a professor of mechanical and aerospace engineering at NYU Tandon, and his collaborators revealed insights that could lead to a novel solution: use robotic fish to make mosquitofish too stressed to reproduce.

Porfiri led an interdisciplinary team at NYU Tandon and the University of Western Australia that demonstrated how robotic fish can be deployed against this species, which has spread from Spain to the rest of Europe.

In brief, the team has discovered that robotic fish predators can quickly stress invasive fish species to curb their reproduction. The research is published as the cover story in the Royal Society journal Interface.

 Prof. Maurizio Porfiri in his lab
Prof. Maurizio Porfiri in his lab

No fooling!

Determining whether a photo or video is authentic is becoming increasingly problematic. Sophisticated techniques for making misleading alterations have become so accessible that so-called “deepfakes” — AI-manipulated photos or videos that are remarkably convincing and often include celebrities or political figures — have become commonplace.

Pawel Korus, a research assistant professor in the Department of Computer Science and Engineering, pioneered an approach that replaces the typical photo development pipeline with a neural network — one form of AI — that introduces carefully crafted artifacts directly into the image at the moment of image acquisition. These artifacts, akin to “digital watermarks,” increase the chances of detecting manipulation from approximately 45% to over 90% without sacrificing image quality.

Shedding light on political advertising

A team led by Computer Science and Engineering Assistant Professor Damon McCoy and Ph.D. student Laura Edelson created easy-to-use tools to collect, archive, and analyze political advertising data — an increasingly important development as November 2020 approaches.

Although Facebook became the first major social media company to launch a searchable archive of political advertising, for both Facebook and Instagram, in 2018, it was difficult to use and required time-consuming manual searches. The team applied versions of the data scraping techniques McCoy had previously deployed against criminals such as human traffickers advertising on the more shadowy realms of the Internet. The new tools give voters the ability to understand who is advertising, what they are pushing, who they are targeting, and how much is being spent to influence votes.

Protecting printing from piracy

The worldwide market for 3D-printed parts is a $5 billion business with a global supply chain involving the Internet, email, and the cloud — creating a number of opportunities for counterfeiting and intellectual property theft. Flawed parts printed from stolen design files could produce dire results: experts predict that by 2021, 75% of new commercial and military aircraft will fly with 3D-printed components, and the use of 3D printing in the production of medical implants will grow by 20% per year over the next decade.

A team that includes Nikhil Gupta, a professor of mechanical engineering, and his doctoral student Fei Chen (‘19) have found a way to prove the provenance of a part by employing QR (Quick Response) codes in an innovative way for unique device identification. Their method involves converting QR codes, bar codes, and other passive tags into three-dimensional features hidden in such a way that they neither compromise the part’s integrity nor announce themselves to counterfeiters who have the means to reverse engineer the part.

 Ph.D. student Fei Chen and Prof. Nikhil Gupta in the lab
Ph.D. student Fei Chen and Prof. Nikhil Gupta

Better solar cells

It’s no wonder that the market for organic solar cells is expected to grow more than 20% between 2017 and 2020. These super-flexible cells can be mass produced, use renewable materials and green chemistry, and can be semitransparent and therefore less visually intrusive. But they are also highly vulnerable to moisture, oxygen, and sunlight itself. Researchers led by André Taylor, an associate professor in the Department of Chemical and Biomolecular Engineering, have discovered a remarkable means of making organic solar panels more robust, including conferring resistance to oxygen, water, and light, all by removing a layer of material instead of adding one, which is the traditional, more costly approach.

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