Researchers studying ribosomes, plants’ Rubisco function, artificial intelligence and quantum computing are among 13 early-career professors from Cornell who’ve recently been awarded National Science Foundation Faculty Early Career Development Awards.

Grantees receive a minimum of $400,000 over five years from the program, which supports early-career faculty who “have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization,” according to the NSF. Each project must include an educational component.

Recent Cornell recipients:

Heather Feaga, assistant professor of microbiology (College of Agriculture and Life Sciences), will use her award to further her study of ribosomes, which are molecular machines that manufacture the proteins needed for cellular life. A greater understanding of the mechanisms by which ribosomes synthesize proteins has important implications for biotechnology, synthetic biology and advanced materials manufacturing. This project aims to identify proteins that aid translation during stressful conditions in bacteria.

Paul Gölz, assistant professor of operations research and information engineering (Duffield Engineering), will use his award in his study of now-ubiquitous artificial intelligence systems. This project builds a theoretical understanding of the blind spots of current AI development and deployment pipelines by studying, for example, when disagreements can make the AI system adopt an unbalanced position or behave erratically. The aim is to design new algorithms for the alignment, fine-tuning and deployment of more balanced AI.

Giulia Guidi, assistant professor of computer science (Cornell Bowers), will use her award to expand large-scale computation capabilities – in fields such as genomics – by establishing sparse linear algebra as a unifying abstraction for scientists to express their computations in a standard form, enabling portable execution on evolving computing hardware. By making advanced computing systems more accessible, the project will accelerate discovery in data-intensive sciences while strengthening the U.S. workforce in high-performance computing.

Laura Gunn, assistant professor in the Plant Biology Section, School of Integrative Plant Science (CALS), will use her award to study how plants naturally adjust their Rubisco function (carbon fixing) when temperatures change, focusing on how they do this by changing which small protein subunits are incorporated into the enzyme. Understanding this process could reveal new strategies for improving photosynthesis in crops, supporting long-term goals in agricultural biotechnology and food security.

Mohamed I. Ibrahim, assistant professor of electrical and computer engineering (Duffield Engineering), will use his award to advance quantum computing, which is currently limited by outdated technologies such as bulky coaxial cables. The aim is to develop energy-efficient, scalable interfaces for cryogenically cooled quantum processors. By addressing the input/output bottleneck, the project seeks to accelerate the development of quantum processors, enabling transformative advancements in computing, secure communications and sensing technologies.

Flavio Lehner, associate professor of earth and atmospheric sciences (CALS), seeks to further understanding of how strongly Pacific Ocean temperatures influence the occurrence of extreme weather events – such as heat waves, wildfires and drought – in North America. There is a need to reconcile the discrepancies between numerical model simulations and real-world observations, both of which attempt to predict Pacific temperature fluctuation. This project investigates the leading candidate hypotheses for these discrepancies and aims to reduce uncertainties in extreme event predictions.

Ziv D. Scully, assistant professor of operations research and information engineering (Duffield Engineering), will use his award to develop algorithms that enable highly efficient training and deployment of AI models. On the training side, the new algorithms will make smarter decisions about how to explore the vast design space of possible AI models; on the deployment side, the algorithms will make smarter decisions about the order to schedule incoming streams of AI tasks, enabling faster task completion.

Soroosh Shafiee, assistant professor of operations research and information engineering (Duffield Engineering), will use his award to develop mathematical tools for building robust AI systems that function in unpredictable real-world conditions. The project aims to advance the field by shifting from defensive methods that only patch specific vulnerabilities to a more universal approach, achieved by training AI models against a generative adversary, a strategy that uses AI to identify the most challenging data variations a system might encounter.

Aditya Vashistha, assistant professor of information science (Cornell Bowers), will use his award to investigate how people share information and govern their communities in social media platforms designed for private groups. These platforms often lack tools that help members set shared rules, resolve disagreements or manage their communities. This project will advance methods for ethically studying private groups and develop AI tools to help them manage disagreements and govern themselves more effectively.

Y. Samuel (Sam) Wang, assistant professor of statistics and data science (ILR School), will use his award to develop theory and methods that broaden the empirical use of causal discovery, a subfield of statistics and machine learning that seeks to recover possible causal relationships among variables in a complex system. The proposed work will allow for more trustworthy and reliable causal discovery by developing methods that rigorously reason about uncertainty in estimated causal structure and relax potentially restrictive assumptions.

Yao Yang, Ph.D. ’21, assistant professor of chemistry and chemical biology (College of Arts and Sciences), will use his award to study one of the grand challenges of chemical catalysis: capturing real-time nanoscale “movies” of catalytic processes – i.e., watching catalysis in action. Through the use of copper-based catalysts, this work seeks to transform mechanistic understanding of the intricate catalyst-molecule interactions, which transform molecules such as carbon dioxide into desirable products, reduce carbon emissions and advance renewable energy technologies.

Yunan Yang, the Goenka Family Assistant Professor in Mathematics (College of Arts and Sciences), will use her award to further her work on new mathematical and computational methods for solving inverse problems that arise when scientists and engineers infer hidden causes from indirect, incomplete or noisy observations. Goals include creating tools that can support faster, more accessible radiation therapy planning; improving the reliability of scientific computing with limited data; and strengthening the foundations of data-driven discovery.

Lenan Zhang, assistant professor of mechanical and aerospace engineering (Duffield Engineering), will use his award to advance his study of the liquid-vapor phase change, an important aspect in applications such as power generation, chip-cooling, water purification and air conditioning. Through a combination of advanced experimental methods and modeling, Zhang will measure heat transfer at the liquid-vapor interface, the results of which will help create design rules for high-performance phase change systems.