The Michigan Engineer News Center

Eleven New Faculty Hired in CSE in 2020

Meet the new arrivals.| Short Read
IMAGE:  Top: Greg Bodwin, Laura Burdick, Mithun Chakraborty, Paul Grubbs; Center: Anhong Guo, Xin He, YatinManerkar, Max New; Bottom: Thatchaphol Saranurak, Lu Wang, Xu Wang

From security and cryptography, to  algorithms and programming languages, to formal methods and theoretical computer science, Michigan is expanding and strengthening the scope of its research activities in computer science and engineering. Meet the new arrivals here.

Greg Bodwin – Assistant Professor
PhD Massachusetts Institute of Technology, 2018

Greg Bodwin’s research is in graph theory, combinatorics, and theoretical computer science. He has made major contributions to graph sketching and wrote an award-winning paper that proved an important bound on additive spanners. During his PhD work, he co-taught classes that introduced less-privileged high school students to game theory and probability. As a postdoc at Georgia Tech, he served as the primary instructor for Honors Discrete Math and won several “Thank-A-Teacher” awards. Greg joins the faculty in Fall 2020.

Laura Burdick – Lecturer III
PhD University of Michigan, 2020

Laura Burdick’s research is in the area of natural language processing. Her dissertation examines algorithms for producing word embeddings and introduces a new way to measure the consistency of embeddings across algorithms and datasets.  She has served as a GSI in EECS 281 and as a co-instructor for EECS 498/595 (Natural Language Processing).  In 2018, she designed and taught a new class, “EECS 198: Discover CS,” which is aimed at generating enthusiasm for computer science among first-year students, particularly those who are underrepresented in technical fields.  She has received grants for her innovative teaching from the Center for Research on Learning and Teaching and from Google, and in 2019 won an Outstanding GSI award from Rackham Graduate School. Laura joins the faculty in Winter 2021.

Mithun Chakraborty – Assistant Research Scientist
PhD Washington University, 2017

Mithun Chakraborty is broadly interested in multi-agent systems and computational economics, employing techniques from algorithmic game theory and machine learning. His PhD thesis was on incentivized collective forecasting methods such as prediction markets. As a post-doctoral research fellow at National University of Singapore, he worked on fairness and diversity issues in resource allocation problems. He has multiple publications at leading international conferences on artificial intelligence, including a spotlight presentation at NeurIPS in 2015. He taught a course on social network analysis during his PhD work, for which he received the Department Chair Award for Outstanding Teaching, and co-instructed a course on algorithmic game theory as a research fellow. Mithun joined the faculty in Winter 2020 as a member of the Strategic Reasoning Group led by Michael Wellman.

Paul Grubbs –  Assistant Professor
PhD Cornell University, 2020

Paul Grubbs’s research is in the areas of security, cryptography, and systems. He designs and analyzes end-to-end encrypted systems using theoretical tools from cryptography, empirical methods, and practical knowledge of real systems. His work has impacted industry systems with billions of users. Paul has served as a teaching assistant for courses on discrete math, applied cryptography, and information security. He has mentored Cornell CS graduate students and undergraduates in the Women in Technology, New York program. Paul joins the faculty in Fall 2021.

Anhong Guo – Assistant Professor
PhD Carnegie Mellon University, 2020

Anhong’s research interests are in the areas of human-computer interaction and artificial intelligence. His work combines human and machine intelligence to create interactive systems for solving problems that are currently impossible with either alone. He has developed systems to make visual information more accessible for visually impaired people to understand and navigate their environments. His work on deployments of camera-based environmental sensing is now part of a startup. Anhong has been a co-instructor and teaching assistant for courses on user-centered research and evaluation, accessibility, and human-centered systems. He has also mentored a dozen students, and been involved in various programs to promote diversity and inclusion. Anhong joins the faculty in Winter 2021.

Xin He – Assistant Research Scientist
PhD University of Chinese Academy of Sciences, 2017

Xin He’s research aims at improving the energy efficiency of computing systems by cross-layer collaborative optimizations, including hardware-aware algorithm design, approximate computing, reconfigurable architecture and application-specific acceleration. His work has been published in major conferences and journals in computer architecture and EDA areas. During his postdoc at Washington University in St. Louis, he led  a group of WUSTL graduate students to study adversarial attacks on autonomous driving and published several papers. Xin joined the faculty in Summer 2020.

Yatin Manerkar – Assistant Professor
PhD Princeton University, 2020

Yatin Manerkar works on the boundary between computer architecture and formal methods. His research has enabled automated formal verification of memory consistency model properties across the hardware/software stack, and four of his papers have been chosen or nominated for awards at top conferences. He has served as a teaching assistant for two courses at Princeton and one course (EECS 280) at U-M, and he has led tutorials at several conferences. He has been an active advocate for diversity in the organization of the MICRO conference. Yatin joins the faculty in Fall 2021.

Max New – Assistant Professor
PhD Northeastern University, 2020

Max New has done foundational work in programming languages, with a focus on gradually typed languages and language interoperability.  His recent theoretic reformulation of gradual typing allowed him to prove an important theorem about parametricity, which had been thought to be incompatible with gradual typing. Max has served as a TA for a range of classes, including introductory programming, compiler construction, and graduate programming languages.  His teaching philosophy increases inclusion in CS by leveling the playing field for students in early programming classes. Max joins the faculty in Fall 2021.

Thatchaphol Saranurak – Assistant Professor
PhD KTH Institute of Technology, 2018

Thatchaphol Saranurak’s main research interest is in graph algorithms, with a current focus on dynamic, local, and distributed algorithms.  His research on expander decomposition of dynamic graphs resolved a major open question on dynamic graph connectivity.  Thatchaphol has served as a teaching assistant for algorithms, data structures, and complexity theory, and has mentored several junior PhD students and research interns. As an undergraduate, he helped organize and teach an educational camp for students from underprivileged backgrounds. Currently a Research Assistant Professor at Toyota Technological Institute in Chicago, Thatchapol  joins the faculty in Winter 2021.

Lu Wang – Assistant Professor
PhD Cornell University, 2016

Lu Wang’s research focuses on natural language processing; i.e., teaching machines to communicate in human language. She designs machine learning methods and statistical models to solve problems in text summarization, language generation, argument mining, and their applications in computational social science. Her work on argument mining won an outstanding paper award at ACL 2017, and her work on summarization was nominated for best paper award at SIGDIAL 2012. Her group’s work is funded by National Science Foundation (NSF), Intelligence Advanced Research Projects Activity (IARPA), and industry partners. Lu joins the faculty in Fall 2020.

Xu Wang – Assistant Professor
PhD Carnegie Mellon University, 2020

Xu Wang conducts interdisciplinary research within the fields of human-computer interaction, cognitive science, artificial intelligence, and education. Her research goal is to support more people to learn in effective ways. She develops computational methods and systems to support scalable teaching and learning and at the same time studies the cognitive processes behind human problem solving and learning. Her work has been published in top conferences and journals in HCI and Learning Sciences, and her UpGrade system for semi-automatically generating high-quality questions has been used in eight classes at CMU.  She has participated in programs such as TechNights and OurCS workshops to encourage greater participation by women in STEM fields. Xu joins the faculty in Winter 2021.

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Steve Crang
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