Faculty & Staff
Welcoming our New Faculty
Meet the researchers and innovators who have recently joined Columbia Engineering.
Columbia Engineering welcomes its newest faculty members to the School of Engineering and Applied Science. The new cohort of scholars brings expertise across a wide breadth of areas, contributing to research and education in critical minerals, causal AI, advanced materials for space, software security, quantum engineering, energy conversion and storage, and more.
Pengbo Chu
Pengbo Chu joined the Department of Earth and Environmental Engineering as an assistant professor in January 2026.
His research focuses on critical minerals processing and extractive metallurgy, particularly with rare earth minerals, lithium, nickel, and copper. His research motivation is to develop innovative extraction technologies using an interdisciplinary approach to enable resource recovery from both primary and secondary resources. His research also includes space mining with interest in developing mineral extraction technologies for in-situ resource utilization.
He obtained his BEng (2009), MEng (2012) in mechanical engineering, and PhD (2017) in materials engineering from McGill University in Canada. For two years, he was a research scientist in mineral processing at Natural Resources Canada. Prior to Columbia, he was a faculty member at the University of Nevada, Reno.
Research areas: Critical Minerals/materials, mineral processing, space resources recovery.
Greg Elsaesser
Greg Elsaesser joined the Department of Earth and Environmental Engineering as an associate professor of professional practice in July 2026.
Elsaesser spent over a decade as a research scientist at the Columbia University-NASA Goddard Institute for Space Studies (GISS) and is a principal investigator with the NSF Learning the Earth with AI and Physics (LEAP) Science and Technology Center. His research uses satellite remote-sensing and in situ observations to improve understanding of global thunderstorms and precipitation patterns. He then applies these insights to Earth system model (ESM) development, with particular emphasis on the GISS ESM (ModelE). He led the GISS effort to automate calibration of the ModelE atmosphere using machine learning (ML), producing the first ML-calibrated atmosphere configuration submitted to Phase 6 of the international Coupled Model Intercomparison Project (CMIP6). He maintains a close connection with the satellite remote-sensing community, and currently co-chairs the international WCRP-ESMO Obs4MIPs effort.
He received his PhD (2011) and MS (2006) from Colorado State University and his BS from Ohio State University.
Research areas: Global precipitation and heavy rainfall, remote sensing, tropical thunderstorms, global climate modeling.
Dimitrios Fafalis
Dimitrios Fafalis joined the Department of Mechanical Engineering as a senior lecturer in discipline in July 2026.
His teaching and scholarly work advance the integration of computational mechanics, engineering design, and artificial intelligence, with particular interests in finite element methods, computer-aided engineering, machine learning, digital twins, mechanics of materials, aerospace applications, and engineering management. Fafalis designs courses that connect rigorous engineering theory with computational practice and consequential design decisions. He is particularly interested in preparing mechanical engineers to use artificial intelligence and advanced computational tools with both technical sophistication and sound engineering judgment.
Before joining Columbia, Fafalis taught undergraduate and graduate courses at Drexel University, where he also developed collaborations with industry and government partners in industrial predictive analytics, machine learning-based condition monitoring, and autonomous transportation systems.
Fafalis earned his PhD in Computational Mechanics from Columbia University and subsequently completed a postdoctoral fellowship in Mechanical Engineering at Columbia under Professor Jeffrey Kysar. He holds a BS in Mechanical Engineering and Aeronautics from the University of Patras and three MS degrees from the National Technical University of Athens in Computational Mechanics, Automation Systems, and Technology Management.
Research areas: Computation, engineering design, engineering education, biomechanics, materials.
Yuchen Hu
Yuchen Hu joined the Department of Industrial Engineering and Operations Research as an assistant professor in July 2026.
She is interested in developing interdisciplinary methodologies that enhance the applicability, robustness, and efficiency of data-driven decisions in complex environments. She was a postdoctoral associate at the MIT Laboratory for Information and Decision Systems and obtained her PhD at Stanford University in 2025. Hu holds an MS from Harvard University and a BSc from Hong Kong Polytechnic University.
Research areas: Causal inference, data-driven decision making.
Luana Canzian Llanes
Luana Canzian Llanes joined the Department of Earth and Environmental Engineering as a Lecturer in Discipline in July 2026.
In her teaching, Llanes uses hands-on experiments to explore core principles of earth and environmental engineering, with a focus on the applications of chemistry, biology, and thermodynamics to real-world environmental challenges.
She was a postdoctoral research scientist at Columbia University and previously worked as a research scientist at two startups: Aegilys and the Avanti Battery Company. She also interned at PARC, a Xerox company. She holds a PhD from the University of California, Santa Barbara (2023) and a BS from the Universidade Federal de Santa Catarina in Brazil (2017).
Research areas: Polymers, metallurgy, materials science.
Cody Paige
Cody Paige joined the Department of Mechanical Engineering as an assistant professor in January 2026.
Paige develops innovative technological and operational solutions to enable a permanent human presence in space. Her research focuses on vision systems, virtual reality and digital twins for the Lunar surface and has extended to materials development for advanced spacesuits, and space architecture concepts for both short-term and permanent habitation on the Moon. She also works on mission planning and operations, and is more broadly enabling a pipeline to prototype, test and fly space-related research for a regular cadence of space missions.
Paige completed her PhD at Massachusetts Institute of Technology (MIT) in 2023, her MS at the University of Toronto in 2012, and her BS from Queen’s University in Canada in 2008. She also completed a master’s at Dalhousie University. She was a Fulbright scholar, as well as a National Geographic Explorer. Paige was director of the Space Exploration Initiative from 2023 to 2025 at MIT and a project engineer at Bombardier Aerospace.
Research areas: Vision systems, virtual reality and digital twins for the Lunar surface; space mission planning and operations.
Zishen Wan
Zishen Wan will join Columbia University’s Department of Computer Science as an assistant professor in September 2026.
As a computer architect and system-on-chip designer, he develops architectures and hardware-software systems for emerging AI workloads. His works at the intersection of computer architecture, systems, and VLSI, with a focus on two complementary directions: (1) cross-layer co-design spanning systems, architecture, and silicon for physical AI, and (2) agentic AI for computing system design. His work aims to enable intelligent machines to sense, learn, reason, plan, and act efficiently and reliably in the physical world. He also explores how AI agents can collaborate with human designers to reason about complex design decisions, optimize hardware and software, and continually improve computing systems.
Before joining Columbia, he was a postdoctoral fellow at Harvard University and received his PhD from the Georgia Institute of Technology in 2025. His research has been recognized with ACM SIGDA Outstanding PhD Dissertation Award, Best Paper Awards at DAC, CAL, and SRC JUMP2.0, First Place in DAC PhD Forum, First Place in ACM Student Research Competition, and IEEE Micro Top Picks. He was also selected as ML and Systems Rising Star and Cyber-Physical Systems Rising Star.
Research areas: Computer architecture, VLSI and systems-on-chip, domain-specific architectures, embodied and agentic AI systems, AI for computing system design, hardware-software co-design, system-technology co-optimization.
Zhaoyou Wang
Zhaoyou Wang joined the Department of Electrical Engineering as an assistant professor in January 2026.
Zhaoyou's research focuses on developing methods to control and protect quantum information systems for potential applications in communication, computation, and sensing, while investigating the theoretical limits of these systems. His work explores the connection between fundamental quantum theory and practical quantum engineering.
He received his PhD from Stanford University and his BS from Tsinghua University in China. He then continued as a postdoctoral researcher at the University of Chicago.
Research areas: Quantum theory, quantum engineering.
Yan Yao
Yan Yao joined the Department of Earth and Environmental Engineering as a professor in July 2026. He also holds a joint appointment at the Columbia Climate School.
Yao’s research sits at the intersection of electrochemistry and materials science. He is known for his work on battery chemistries beyond lithium-ion, with a focus on sustainable alternatives built from earth-abundant materials.
He is a Clarivate Highly Cited Researcher and served as a principal investigator and leader for several Department of Energy initiatives, including the Battery500, Energy Storage Research Alliance (ESRA), and Low-cost Earth-abundant Na-ion Storage (LENS) consortia.
He joins Columbia from the University of Houston, where he was the Hugh Roy and Lillie Cranz Cullen Distinguished Professor in the Electrical and Computer Engineering Department and where he established the first Solid-State Battery Prototyping Facility in Texas. He has also co-founded two startup companies.
Yao is a Fellow of the Royal Society of Chemistry and a senior member of both the National Academy of Inventors and the IEEE. He was a postdoctoral scholar at Stanford University and received his PhD from the University of California, Los Angeles in 2008, and an MS (2003) and BS (2000) from Fudan University in China.
Research areas: Advanced materials and devices for energy conversion and storage; magnesium and sodium batteries; organic and polymeric batteries; aqueous batteries for grid storage; solid state electrolytes and all-solid-state-batteries; computational modeling of battery microstructures.
Qihao Ye
Qihao Ye joined the Department of Applied Physics and Applied Mathematics as the Chu Assistant Professor in July 2026.
His research lies at the intersection of numerical analysis, scientific computing, and machine learning, with a focus on developing mathematically grounded computational methods for partial differential equations (PDEs), nonlocal models, stochastic dynamics, and data-driven inference. He is also increasingly interested in using advanced modern tools to accelerate mathematical research, especially through systems that support reliable, self-corrective, and verifiable reasoning.
He received his PhD from the University of California, San Diego in 2026 and his BS from the Southern University of Science and Technology in 2020.
Research areas: Computational methods for PDEs, nonlocal models, stochastic dynamics, and data-driven inference.
Zhuo Zhang
Zhuo Zhang joined the Department of Computer Science as an assistant professor in January 2026.
Zhang's research advances software and systems security for both traditional and agentic computing. He develops practical techniques that strengthen assurance and enable precise auditing in real-world settings.
He received his PhD from Purdue University in 2023 and his BS from Shanghai Jiao Tong University in China in 2018. He is a recipient of the ACM SIGSAC Doctoral Dissertation Award.
Research areas: Security for software systems.
Ben Zhu
Ben Zhu joined the Department of Applied Physics and Applied Mathematics as an assistant professor of applied physics in January 2026.
Zhu is a theoretical and computational physicist whose research advances our understanding of fusion and laboratory plasmas. His work focuses on magnetic fusion energy (MFE), with particular emphasis on the nonlinear dynamics of magnetized plasmas across multiple spatial and temporal scales. He is also at the forefront of applying machine learning and artificial intelligence (ML/AI) to plasma physics, developing neural-network-based kinetic closures and surrogate models for tokamak control and predictive modeling.
Zhu received his PhD from Dartmouth College in 2017, his MS degree from the University of California, Davis in 2009, and his BS from the University of Science and Technology of China in 2008. After serving as a research associate at Dartmouth College, he joined Lawrence Livermore National Laboratory (LLNL) in 2018 and became a staff scientist in 2020. He was honored with the U.S. Department of Energy (DOE) Early Career Award in 2024.
Research areas: Plasma physics; numerical modeling of magnetized plasma; turbulence and transport processes; fusion exhaust and control strategies; ML/AI applications in fusion energy science.