Four EECS faculty members receive promotions

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Friday, March 23, 2018 - 1:00pm

L to R: Professors Constantinos Daskalakis, Ruonan Han, Caroline Uhler, Nickolai Zeldovich

EECS Staff

Four EECS faculty members have received significant promotions, department head Asu Ozdaglar has announced.

Constantinos Daskalakis and Nickolai Zeldovich were each promoted to full professor of EECS, while Ruonan Han and Caroline Uhler were each promoted to associate professor without tenure (AWOT). All the appointments are effective July 1, 2018.

Constantinos Daskalakis is a leading theoretical computer scientist working in a variety of areas involving foundations and applications of probability, including algorithmic game theory, mechanism design, and statistical sampling. He received a PhD from the University of California Berkeley in 2008 and joined MIT in 2009 after a one-year postdoctoral position at Microsoft Research. He is a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL), and he was granted tenure in 2015.

Daskalakis began his research career working in the field of algorithmic game theory. His most notable result in that area says that Nash equilibria, which describe stable configurations of competitive multi-player games, cannot be computed efficiently. After obtaining a series of related results, he began working in mechanism design, where he obtained another breakthrough: he showed that the general problem of mechanism design, which allows a system to achieve desired results in the face of strategic, possibly dishonest participants, can be reduced to the simpler problem of algorithm design, in which the participants are assumed to be honest.

More recently, Daskalakis worked on a long-standing problem from economic theory: optimal pricing for multiple items. Again, he obtained a breakthrough result, this one providing a mathematical characterization of the structure of optimal solutions. He has also been pioneering new methods for discerning properties of unknown probability distributions by using sampling.

Among other honors, he has received a Game Theory and Computer Science Prize, an Association for Computing Machinery (ACM) Doctoral Dissertation Award, a Society for Industrial and Applied Mathematics (SIAM) Outstanding Paper Prize, and a Vatican Giuseppe Sciacca Foundation Research and Development Award. At MIT, he has taught many courses in algorithms, probability, game theory, inference, and data science, and has received the EECS Ruth and Joel Spira Award for distinguished teaching.

Nickolai Zeldovich received a PhD from Stanford University in 2008 and, after a short postdoctoral appointment at Stanford, joined MIT later that year. He was granted tenure in 2014.

Zeldovich, also a CSAIL member, works on improving the state of computer-system security and on enabling new applications that might not be deployed today because of security concerns. To that end, he has worked on a variety of types of systems, including operating systems and distributed systems that avoid security vulnerabilities, systems that guarantee security even in the face of programmer errors, systems that recover gracefully from intrusions, systems that run applications on encrypted data, and systems that hide the identities of communicating parties.

Recently, he has also been developing rigorous techniques for finding security vulnerabilities in code or proving their absence, as well as building new secure applications such as cryptocurrencies.

Among other honors, he has received a Sloan Research Fellowship, an NSF CAREER Award, and an MIT Harold E. Edgerton Faculty Achievement Award. In February 2018, he was one of two EECS professors to receive the department’s Faculty Research Innovation Fellowship (FRIF), an award that recognizes midcareer faculty members for outstanding research contributions and international leadership and provides them with resources to pursue new research and development. At MIT, he has taught many different courses in systems and security, and has also received the EECS Ruth and Joel Spira Award for distinguished teaching.

Ruonan Han received a PhD degree in electrical engineering from Cornell University in January 2014. After a short stint as a research scientist at Cornell, he joined MIT as an assistant professor in July 2014, and he is also a core faculty member of the Microsystems Technology Laboratory (MTL). His work focuses on pushing the fundamental limits of chip-scale electronics and exploring new application opportunities in the realms of sensing and communications. In particular, he is pursuing critical problems in the important “terahertz gap” (0.1-10 THz).

Han’s work has generated multiple records in the performance metrics of silicon-based THz circuits, including the highest radiated power and the highest detection sensitivity. In addition, his group invented a new sensor architecture that maintains high efficiency across a scalable, broad bandwidth. His group also demonstrated new applications of THz chips beyond traditional wireless radio and non-invasive imaging: molecular spectroscopy with high specificity, ultra-broadband inter-chip link through a THz dielectric waveguide, and most recently, fully-electronic time-keeping with a molecular clock.

Han’s awards include an NSF CAREER Award and best student paper awards at the IEEE Custom Integrated Circuits Conference (CICC) and IEEE Radio Frequency Integrated Circuits (RFIC) Symposium. He also received Cornell’s award for the best PhD thesis. At MIT, he has taught multiple courses in circuits, and contributed to the development of other courses in that subject. He served as the workshop chair of the 2016 IEEE International Wireless Symposium and is steering-committee member for the 2019 IEEE International Microwave Symposium, the flagship conference for the microwave theory and technique society.

Caroline Uhler received a PhD in Statistics from the University of California Berkeley in 2011. After serving as an assistant professor at IST Austria, she joined MIT as an assistant professor of EECS and a core faculty member of the Institute for Data, Systems, and Society (IDSS). Currently, she is the Henry L. and Grace Doherty Assistant Professor of EECS and IDSS. 

Uhler’s primary expertise is in the general area of algebraic statistics, a field that focuses on the application of algebra, algebraic geometry, graph theory, optimization and combinatorics to statistical modeling. This broad expertise enables her to produce new paradigms and algorithms for the analysis of large heterogeneous data sets that arise in various applications. Her work to date has broken new ground on providing a systematic approach to studying graphical models. In her PhD work, she initiated the study of Gaussian graphical models using algebraic methods and introduced hyperbolic exponential families as a general class of graphical models that share the nice computational properties of Gaussian models. 

Uhler’s awards include a Sofja Kovalevskaja Award, a Sloan Research Fellowship, and an NSF CAREER Award. She was a plenary speaker on the subject of algebraic statistics during the 2017 SIAM Conference on Applied Algebraic Geometry.

She has developed two courses at MIT, one of which serves as the capstone class for the minor in statistics. She serves on the EECS admissions committee and the Broad Institute Fellows selection committee, and she was an organizer of the joint conference between MIT, Harvard, and Microsoft for Women in Data Science.