The future of computing at Tandon

NYU Tandon is no stranger to pioneering advances in computing. In the early 20th century, Tandon alum Charles Flint founded what is now known as IBM and Tandon alum and Silicon Valley pioneer Eugene Kleiner founded Fairchild Semiconductor, sparking a computing revolution. Now, NYU Tandon researchers are shaping the future of computing and communication by exploring new frontiers in materials, computational design, and quantum technologies. 

In the past decade, quantum technology — the use of quantum mechanics to create new devices, algorithms, and applications — has demonstrated remarkable promise with its ability to significantly enhance computing power, enable secure communication, and advance precision measurement. 

Preparing a generation of quantum-ready engineers

We are now at what some may call the real dawn of the quantum era, with the race to develop new hardware and software already going at full speed – a race that needs well-equipped, well-trained engineers to help advance new technologies, adapt old ones, and realize quantum’s potential in healthcare, cybersecurity, sustainability, national defense, and other key aspects of life. 

The problem is that the field is moving so fast, higher ed hasn’t kept up with demand, and there aren’t yet many predefined paths to follow into a career in quantum technologies. Tandon is partnering with industry to give students a unique opportunity to gain skills in a cutting-edge and rapidly developing field while helping companies develop promising talent, beginning with a new quantum technologies minor launched in Spring 2024 through the Department of Applied Physics.

The new minor stemmed from a collaboration between NYU Tandon and SandboxAQ, an enterprise SaaS company providing solutions at the nexus of AI and Quantum technology, with a jointly-organized workshop during which Tandon faculty joined SandboxAQ leaders and residents — graduate students and postdocs working on AI and quantum projects at the company — to begin designing a curriculum that provides a practical foundation for careers in the quantum industry.

In September as a lead-up to the minor launch, NYU Tandon worked with SandboxAQ to host a tremendously well-attended hackathon — called Tandon hAQathon — to introduce NYU students to quantum technology and provide them hands-on experience in quantum programming. Tandon also welcomed Rupak Chatterjee as an Industry Assistant Professor this year, who will bring his expertise in quantum machine learning to courses for the minor.

Chatterjee joins a number of Tandon faculty and alumni who are working on quantum computing. His research into the pure physics behind quantum machine learning is illuminating the potential (and limits) of quantum computing as it currently exists while developing algorithms necessary to harness quantum’s unique abilities beyond the realm of classical computing.

Dean Emeritus Katepalli R. Sreenivasan has been working on the potential for quantum computing to improve computational fluid dynamics (CFD), the use of classical- and non-classical computing to understand how liquids act when force is applied to them. Quantum computers may be leveraged to simulate classical fluids, a domain traditionally relegated to classical computational paradigms. While quantum computing is useful at the molecular scale, Sreenivasan’s work is interrogating whether it will really be more effective at modeling fluid dynamics at a larger scale, or if traditional computing is simply a better fit. In 2023, he  introduced an in-house quantum simulator for computational fluid dynamics, and highlighted the limitations of quantum computing while preserving the quantum advantage in speed and efficiency.

One of the reasons that quantum computing is currently catching the eyes of government officials is its potential to upend cybersecurity practices. Certain encryption algorithms that would take thousands of years of brute-force calculations by traditional computers could be broken by quantum computers in a matter of hours because of their unique abilities. NYU’s Center for Cybersecurity, led by co-founder and co-chair Ramesh Karri, has been researching what a post-quantum world will look like for people protecting data and systems from attack. Their work looks at how to design, build, and understand new types of cryptography that are resistant to attacks from quantum computers. The authors study various algorithms recommended by NIST and examine how they perform in terms of speed, security, and efficiency when implemented on specialized computer hardware, and look at the trade-offs between power usage, performance, space needed, and security features in these designs. Brandon Reagen recently won a CAREER Award for his work on hardware accelerators and applications for privacy-preserving computation to create more efficient ways to process big data while protecting individual privacy, which quantum computing will help to further hasten.

NYU Tandon double-alum Noel Goddard, the CEO of the secure quantum networking company Qunnect, is also proving out the real-world potential and benefits of a more secure quantum internet — Qunnect recently partnered with NYU to complete an industry-first successful test of a quantum networking link between the Brooklyn Navy Yard and Manhattan.

Quantum computing may represent one potential vision of future computing, but huge advances are also being made in classical computing speed and capability.

New Materials

Atomically thin, 2D hexagonal boron nitride (h-BN) is a promising material whose protean ability to undergo phase transformations to strong, super lightweight, chemically stable, oxidation-resistant films makes them ideal for protective coatings, nanotechnology thermal applications, deep-UV light emitters, and much more. The possibilities embodied in different polytypes of h-BN include the ultra-hard diamond phase, a cubic structure (c-BN) with strength and hardness second only to actual carbon diamonds. Key to fabricating such materials is the ability to induce and control the transformation between their various crystalline phases, in a way that is efficient and cost effective enough to allow for economies of scale.

While synthesizing such materials in their “bulk” or 3D configurations requires immense pressure and heat, researchers at the NYU Tandon School of Engineering have discovered that h-BN in layered, molecule-thin 2D sheets can phase transition to c-BN at room temperature.

Elisa Riedo, Professor of Chemical and Biomolecular Engineering produced experiments and simulations using a nanoscopic tip compressing atomically thin, 2D h-BN layers to reveal how these room-temperature phase transitions occur and how to optimize them, partly by varying the number of layers in the h-BN thin film.

Riedo also discovered a fundamental friction law that is leading to a deeper understanding of energy dissipation in friction and the design of two-dimensional materials capable of minimizing energy loss alongside a new method to measure the interfacial shear between two atomic layers and discovered that this quantity is inversely related to friction, following a new law. This work could lead to more efficient manufacturing processes, greener vehicles, and a generally more sustainable world. Both the materials and the law of friction are opening up the possibilities for the next generation of computing with materials that can massively reduce the traditional forces that drag down performance at the highest level.

Riedo’s work is not the only major advance in computer materials that has happened at Tandon in recent years. The colloidal diamond has been a dream of researchers since the 1990s. These structures — stable, self-assembled formations of minuscule materials — have the potential to make light waves as useful as electrons in computing, as well as a host of other applications. But while the idea of colloidal diamonds was developed decades ago, no one was able to reliably produce the structures. Until now. 

Researchers led by David Pine, Professor of Chemical and Biomolecular Engineering, devised a new process for the reliable self-assembly of colloids in a diamond formation that could lead to cheap, scalable fabrication of such structures. The discovery could open the door to highly efficient optical circuits leading to advances in optical computers and lasers, light filters that are more reliable and cheaper to produce than ever before, and much more.

The design and production of computer chips is a time-consuming task that requires a lot of expertise, and this can act as a bottleneck for prototyping and other technical innovations. Now, Siddharth Garg, Institute Associate Professor at NYU Tandon School of Engineering and a member of the NYU Center for Cybersecurity and NYU WIRELESS, is leading a team to democratize chip design, with the help of AI and large language models.

The research team presents how two hardware engineers “talked” in standard English with ChatGPT-4 – a Large Language Model (LLM) built to understand and generate human-like text type – to design a new type of microprocessor architecture. The researchers then sent the designs to manufacture.

The NYU Tandon research team, which also includes Professor Ramesh Karri, Hammond Pearce of the NYU Center for Cybersecurity, and doctoral student Jason Blocklove, used LLMs to work on eight hardware design examples, specifically by generating Verilog code for functional and verification purposes, before focusing on chip fabrication for a deep-dive case study. Previously, the researchers had tested LLMs to convert English to Verilog but, they said, adding back-and-forth interaction with a live engineer produced the best results.

Designing chips is difficult enough, but computer science research needs access to state-of-the-art semiconductors and other materials. On October 18th of 2023, the ribbon was cut at the newly-minted NYU Nanofabrication (NanoFab) Cleanroom, a specialized research environment in which scientists and engineers can fabricate cutting-edge semiconductor chips to advance research on quantum science and engineering, precision medicine, neurotechnologies, next-generation communications technology and secure computing.

Located on NYU Tandon’s campus, the NYU NanoFab helps fulfill the promise of the bipartisan CHIPS and Science Act, signed into law by President Biden in 2022. 

The CHIPS and Science Act aims to bolster U.S. chip manufacturing to meet growing global demand, and to support related research and development and workforce cultivation. The NanoFab is the only such academic facility in Brooklyn, and is available to all NYU faculty and students, and to the academic and tech communities in Brooklyn and beyond. The state-of-the-art facility will allow researchers to make semiconductors that accelerate artificial intelligence advances, power quantum computing, produce new medical devices and develop other innovations that improve people’s lives and create connected and safe communities.

The NanoFab Lab is led by Davood Shahrjerdi, a professor of Electrical and Computer Engineering at the NYU Tandon School of Engineering and a faculty member of NYU WIRELESS. Shahrjerdi’s work in future materials has earned him a host of honors, including his work improving the efficiency of van der Waals (vdW) heterostructures, stacked graphene that power computers.