Ten new faculty to join McKelvey Engineering for 2024-25

New faculty bring range of experience from data science to biomechanics

Beth Miller 
Clockwise from top left: Goodman, Hall, Hu, Kehne, Kong, Lagunas Vargas, Sorrells, Roccabianca, Manzoor, Liu.
Clockwise from top left: Goodman, Hall, Hu, Kehne, Kong, Lagunas Vargas, Sorrells, Roccabianca, Manzoor, Liu.

Ten new faculty will join the McKelvey School of Engineering at Washington University in St. Louis for the 2024-25 academic year, including six tenured/tenure-track faculty members and three lecturers.

Computer Science & Engineering

Ilan Goodman, lecturer

MS, computer science, Stanford University, 2016
BS, physics, Stanford University, 2015

Ilan Goodman joins the Department of Computer Science & Engineering as a lecturer Sept.1, 2024. Most recently, Goodman was a machine learning engineer at Meta Platforms Inc. Previously, Goodman was an engineer at Robinhood Markets Inc., the Chan Zuckerberg Initiative and Facebook.

At Stanford, Goodman was a teaching assistant in various classes, including Data Structures, Introduction to Probability for Computer Scientists, Programming Abstractions, and Design and Analysis of Algorithms. Among his honors and awards is a Centennial Teaching Assistant Award for outstanding teaching assistants from Stanford University in 2016. Independently, he wrote a neural network to teach a computer to compose music and developed new techniques for understanding the strength of college football teams from the season’s competitive graph. He also is an accomplished musician.

Michael Hall, lecturer

PhD, computer engineering, Washington University in St. Louis, 2015
MS, electrical engineering, Southern Illinois University Edwardsville, 2007
BS, computer engineering, Southern Illinois University Edwardsville, 2006 

Michael Hall joins the departments of computer science & engineering and electrical & systems engineering as a lecturer Sept. 1. Most recently, Hall has been an adjunct instructor for CSE 132, Introduction to Computer Engineering, and CSE 560M in McKelvey Engineering. In addition, Hall has been a software engineer for OpenVault since 2021. Previously, Hall was a hardware engineer with VelociData. His experience spans reconfigurable logic, integrated circuit and PCB design, networking, software engineering, parallel programming, optimization and data science.

Gregory Kehne, assistant professor

PhD, computer science, Harvard University, 2023
BA, mathematics, Williams College, 2016

Gregory Kehne joins the Department of Computer Science & Engineering Aug. 1, 2024, from the University of Texas at Austin, where he has been a postdoctoral researcher in the Department of Computer Science. He studies online and approximation algorithms, computational social choice, and algorithms for the study and improvement of collective decision-making. Previously, he was a doctoral student at Harvard University in the EconCS Group, which pursues research, both theoretical and experimental, on artificial intelligence and algorithms for social and economic impact, and at Carnegie Mellon University in the Department of Mathematical Sciences. He has been an author of numerous papers and has given a variety of talks.

Qinghua Liu, assistant professor

PhD, electrical and computer engineering, Princeton University, 2024
BE, electrical engineering and BS, mathematics, Tsinghua University, 2018 

Qinghua Liu will join the Department of Computer Science at Washington University in St. Louis in 2025. He is a postdoctoral researcher at Microsoft Research in New York. He has also spent time at DeepMind in London and the Simons Institute.

Liu studies machine learning for decision-making. His past research encompasses a wide range of areas within reinforcement learning, including multi-agent reinforcement learning, partially observable reinforcement learning, and reinforcement learning with large state spaces. He is particularly interested in reinforcement learning from human feedback and the development of foundation models for decision-making. His work has been recognized with the Princeton SEAS Award and a Best Paper Award at the ICLR 2022 MARL workshop.

Electrical & Systems Engineering

Hong Hu, assistant professor

PhD, engineering and applied sciences, Harvard University, 2021
BS, automation, Tsinghua University, 2015

Hong Hu will join the Preston M. Green Department of Electrical & Systems Engineering as an assistant professor in fall 2024. 

Hu is a postdoctoral researcher in the Department of Statistics at the Wharton School at the University of Pennsylvania. He earned a doctorate in Engineering and Applied Sciences from Harvard University in 2021 and a bachelor’s degree in automation from Tsinghua University in 2015.

Hu’s research interests lie in the field of signal processing, statistics and machine learning, with a particular focus on developing theoretical underpinnings for algorithms that process high-dimensional data. His work aims to facilitate systematic and refined designs of information processing algorithms in real applications.

Hu will also have an appointment in the Department of Statistics and Data Science in Arts & Sciences.

Janet Sorrells, assistant professor

PhD and MS, bioengineering, University of Illinois, Urbana-Champaign, 2024 and 2020, respectively
BS, biomedical engineering, University of Rochester, 2018

Janet Sorrells will join the Preston M. Green Department of Electrical & Systems Engineering as an assistant professor in August 2024.

Sorrells is expected to earn a doctorate in bioengineering in July from the University of Illinois at Urbana-Champaign, where she also earned a master’s degree in bioengineering in 2020. She earned a bachelor’s in biomedical engineering from the University of Rochester in 2018.

Sorrells works in the Biophotonics Imaging Laboratory with Stephen Boppart, professor and Grainger Distinguished Chair in Engineering at UIUC. Her doctoral thesis focuses on various hardware and software improvements for label-free nonlinear optical microscopy to enable faster and higher-throughput imaging. Part of the work has been developing the SPEED (Single- and multi-photon PEak Event Detection) algorithm to enable the fastest-ever single-detector photon counting in fluorescence lifetime imaging microscopy, for which she received the 2023 Illinois Innovation Award. She also is a member of the Center for Optical Molecular Imaging (COMI), a collaboration between the Biophotonics Imaging Lab and GSK, where she contributes to nonlinear optical microscopy system development. 

Mechanical Engineering & Materials Science

Fanwei Kong, assistant professor

PhD, mechanical engineering, University of California, Berkeley, 2022
BSc, biomedical engineering, Georgia Institute of Technology, 2016

Fanwei Kong plans to join McKelvey Engineering in January 2025 from Stanford University, where she has been a postdoctoral scholar since 2022. Her research interests lie at the intersection of AI, medical computer vision and computational modeling of the heart. Her research has focused on developing machine learning and computational methods to create digital twins of patients’ hearts to enable personalized treatment planning, outcome predictions and early risk detection for cardiovascular diseases.

In addition to academic research, Kong worked as an algorithm consultant for EnChannel Medical Inc., a medical device startup company for treating atrial fibrillation. She also completed an internship in computer vision and medical imaging research with Intuitive Surgical. She has numerous peer-reviewed publications, won first place at the ASME-BED/SB3C Student Paper Competition, and was selected as a Rising Star in Mechanical Engineering in 2022 by Stanford University.

Francisco Lagunas Vargas, assistant professor

PhD, physics, University of Illinois at Chicago, 2023
BS, physics, Southern Illinois University Edwardsville, 2018

Francisco Lagunas Vargas will join the McKelvey School of Engineering as an assistant professor in June 2025 from Argonne National Laboratory, where he is a postdoctoral appointee. At Argonne, he conducts research on renewable energy materials and next-generation ionic sensors. His expertise lies in utilizing advanced Scanning Transmission Electron Microscopes (STEM) to investigate materials at angstrom scales.

At Washington University, Lagunas Vargas plans to develop an atomic-scale understanding of materials' electrochemical, catalytic and structural properties. His work aims to elucidate how these properties can be harnessed and optimized for various engineering applications, specifically by observing their real-time nanoscale interactions. 

While a doctoral student at the University of Illinois Chicago, he received numerous awards, including the Outstanding Dissertation Award, Access to Excellence Fellowship and James Kouvel Fellowship. His dissertation work advanced the use of low-temperature (100 K) STEM to analyze the atomic structure of novel, highly delicate 2D and 1D materials. Lagunas Vargas’ arrival will coincide with the acquisition of the state-of-the-art, sub-angstrom resolution STEM by the Institute of Material Science and Engineering.

Afaque Manzoor, senior lecturer

PhD, mechatronics engineering, Jeju National University, 2021
ME, power engineering, Quaid-e-Awam University of Engineering, Science and Technology, 2018
BE, electrical engineering, Sukkur IBA University

Afaque Manzoor will join McKelvey Engineering as a senior lecturer in August 2024 from Sukkur IBA University in Pakistan, where he has been an assistant professor of electrical engineering since 2021. He heads the Advanced Micro Mechatronics and Energy Lab, where he and lab members use theoretical, numerical and experimental approaches to tackle challenges in emerging electronics, robotics, energy storage and harvesting, and health care. Manzoor’s research focuses on soft materials and soft robotics, flexible and wearable electronics, energy storage and harvesting, and 3D and 4D printing of multifunctional materials. He focuses on the design, modeling and fabrication of soft bioinspired robots and flexible sensors using innovative fabrication techniques. He serves as academic editor of the Journal of Robotics and of the Journal of Sensors and is an editorial board member of AI, Computer Science and Robotics Technology. 

Sara Roccabianca, associate professor

PhD, engineering, civil and mechanical structural systems, University of Trento, 2011
BS, MS, civil engineering, University of Trento, 2004 and 2007, respectively

Sara Roccabianca plans to join McKelvey Engineering as an associate professor in August 2024 from Michigan State University, where she has been on the faculty in the Department of Mechanical Engineering since 2014, most recently as associate professor. Previously, she was a postdoctoral fellow at Yale University in the Department of Biomedical Engineering. Roccabianca’s research is in bladder and cardiovascular biomechanics, extracellular matrix remodeling, growth and remodeling, collagen and elastin, and constitutive modeling. Her research is funded by the National Science Foundation and the National Institutes of Health, as well as Michigan State University. She has been a co-author of 27 peer-reviewed journal articles and more than 60 conference papers. Through her research, she has collaborated with colleagues in various engineering fields as well as in pharmacology and toxicology, chemistry, physiology and urology. She serves as a reviewer for various scientific journals and has been a guest editor for ASME Journal of Biomechanical Engineering. She also has been involved in community outreach activities aimed to increase equity, diversity and inclusion in engineering, including activities to bring girls and young women into engineering.

The departments of Biomedical Engineering and of Energy, Environmental & Chemical Engineering have no new faculty for 2024-25.

 

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