Syracuse University College of Engineering and Computer Science

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Syracuse University College of Engineering and Computer Science A vibrant, inclusive community of innovators with the spirit to seek.

10/17/2026

First play for the Syracuse offense against Louisville! 🏈🍊

Developing a manufacturing process might sound easy but first year chemical engineering students got to see where it get...
10/16/2026

Developing a manufacturing process might sound easy but first year chemical engineering students got to see where it gets tricky when you start making salad dressing.... 🍊

Great reasons to study abroad in the fall! Fall-only programs, better availability, similar costs and holiday magic make...
10/16/2026

Great reasons to study abroad in the fall!
Fall-only programs, better availability, similar costs and holiday magic make autumn a strong choice for your Syracuse Abroad semester. Applications open November 15th.

10/15/2026

First year chemical engineering students learning to develop a manufacturing process with salad dressing production!

400+ Central New York high school students got to see where and engineering and computer science education could take th...
10/15/2026

400+ Central New York high school students got to see where and engineering and computer science education could take them during our Engineering Exploration Day at !

Electrical Engineering and Computer Science Professor Junzhe Zhang has received a National Science Foundation (NSF) gran...
10/13/2026

Electrical Engineering and Computer Science Professor Junzhe Zhang has received a National Science Foundation (NSF) grant to develop artificial intelligence systems that make more dependable decisions when the data they learn from is incomplete or no longer matches real-world conditions.

The project aims to develop learning methods that account for both problems so that AI decision-making becomes more efficient, robust, generalizable and easier to interpret. 

The work centers on reinforcement learning, a widely used approach to teaching AI systems to make a series of decisions. Its practical use is limited because it typically assumes that no hidden factors influenced how the data were collected and that the environment stays the same between training and deployment. Those assumptions rarely hold in real-world data.

“In fields like medicine or robotics, a bad decision has real consequences. This grant will help develop AI that not only performs well in the lab but also holds up when it meets the messy real world,” said Zhang.

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Electrical Engineering and Computer Science Professor Junzhe Zhang has received a National Science Foundation (NSF) gran...
10/13/2026

Electrical Engineering and Computer Science Professor Junzhe Zhang has received a National Science Foundation (NSF) grant to develop artificial intelligence systems that make more dependable decisions when the data they learn from is incomplete or no longer matches real-world conditions.

The project aims to develop learning methods that account for both problems so that AI decision-making becomes more efficient, robust, generalizable and easier to interpret.

The work centers on reinforcement learning, a widely used approach to teaching AI systems to make a series of decisions. Its practical use is limited because it typically assumes that no hidden factors influenced how the data were collected and that the environment stays the same between training and deployment. Those assumptions rarely hold in real-world data.

“In fields like medicine or robotics, a bad decision has real consequences. This grant will help develop AI that not only performs well in the lab but also holds up when it meets the messy real world,” said Zhang.

Zhang's team will develop a framework called Approximate Causal Reinforcement Learning. It connects the formal requirements of causal inference theory with the limited knowledge about a system that reinforcement learning practitioners usually have. The real environment is modeled as a structural causal model, while the AI learner works from a simplified version that captures both hidden influences on past decisions and differences between training and deployment settings.

Civil and Environmental Engineering Professor Kun-Hao Yu has received a multiyear award from the New York State Energy R...
10/12/2026

Civil and Environmental Engineering Professor Kun-Hao Yu has received a multiyear award from the New York State Energy Research and Development Authority (NYSERDA) to develop energy-efficient building panels that are installed with robotic assistance. 

The project, “3D-Printed Siding and Human-Robot Collaboration for High-Performance Retrofits,” will support the development of a prefabricated, carbon-sequestering concrete siding system for home energy retrofits, while pairing the new material with a collaborative human-robot installation process. The goal is to improve building performance while making retrofits faster, more efficient, and safer for construction workers. 

New York has an estimated 5.3 million single-family homes, more than half of which were built before 1960. The state also has a substantial stock of older multifamily buildings, creating significant opportunities for energy-efficiency retrofits. Yu’s project will test the 3D-printed panels in the lab, comparing how they perform against conventional wall assemblies. The team will also conduct field testing at the Building Envelope Systems Test (BEST) Facility, an on-campus testbed used to evaluate building performance in real-world conditions. Finally, they plan to complete a full-scale dormitory retrofit on Syracuse University’s South Campus. 

“Our prior work showed that 3D-printable concrete can be designed to increase carbon uptake through both material formulation and the geometric freedom enabled by 3D printing,” explains Yu. “This NYSERDA project takes the next step by integrating that material into a complete building-envelope retrofit system and pairing it with robot-assisted installation. The goal is to demonstrate how these technologies can work together at building scale and help create more energy-efficient, lower-carbon retrofit solutions for New York.”

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Civil and environmental engineering professor Kun-Hao Yu has received a multiyear award from the New York State Energy R...
10/12/2026

Civil and environmental engineering professor Kun-Hao Yu has received a multiyear award from the New York State Energy Research and Development Authority to develop energy-efficient building panels that are installed with robotic assistance.

The project, “3D-Printed Siding and Human-Robot Collaboration for High-Performance Retrofits,” will support the development of a prefabricated, carbon-sequestering concrete siding system for home energy retrofits, while pairing the new material with a collaborative human-robot installation process. The goal is to improve building performance while making retrofits faster, more efficient, and safer for construction workers.

New York has an estimated 5.3 million single-family homes, more than half of which were built before 1960. The state also has a substantial stock of older multifamily buildings, creating significant opportunities for energy-efficiency retrofits. Yu’s project will test the 3D-printed panels in the lab, comparing how they perform against conventional wall assemblies. The team will also conduct field testing at the Building Envelope Systems Test (BEST) Facility, an on-campus testbed used to evaluate building performance in real-world conditions. Finally, they plan to complete a full-scale dormitory retrofit on Syracuse University’s South Campus.

“Our prior work showed that 3D-printable concrete can be designed to increase carbon uptake through both material formulation and the geometric freedom enabled by 3D printing,” explains Yu. “This NYSERDA project takes the next step by integrating that material into a complete building-envelope retrofit system and pairing it with robot-assisted installation. The goal is to demonstrate how these technologies can work together at building scale and help create more energy-efficient, lower-carbon retrofit solutions for New York.”

The best way to start the week! Thank you to all the high school students and familes who came to campus to learn about ...
10/12/2026

The best way to start the week! Thank you to all the high school students and familes who came to campus to learn about our programs! 🍊

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Syracuse University'S College Of Engineering And Computer Science Dean'S Office, 223 Link Hall
Syracuse, NY
13244

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+13154432545

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