Department of EECS announces 2023 promotions

Upper row, left to right: Christina Delimitrou (photo courtesy subject); Justin Solomon (photo credit: Lillie Paquette); Tamara Broderick (photo credit: Jodi Hilton) Lower row, left to right: Jonathan Ragan-Kelley (photo courtesy subject); Jacob Andreas (photo credit: Gretchen Ertl); Daniel Sanchez (photo courtesy subject); Kevin O’Brien (photo courtesy subject)

The Department of Electrical Engineering and Computer Science is proud to announce the following promotions.

To Associate Professor Without Tenure (AWOT):

Jacob Andreas has been promoted to Associate Professor without tenure. His work is in Natural Language Processing (NLP) and more broadly in AI. A large amount of current progress in the field of NLP (and ML in general) is driven by strongly empirical work. Current learning approaches to language do not exploit the structural richness of language, instead focusing on using massive training datasets to discover the language structure (a path that has been quite successful nevertheless). Unfortunately, for many languages and applications, the available training data is sparse and cannot be easily obtained, limiting the reach of these methods. Andreas pursues a very different approach to the mainstream in NLP. He focuses on developing linguistically informed approaches for sample-efficient learning in a diverse set of applications, such as the use of language-based supervision to enable sample-efficient training, language-based constraints to improve robustness and user control, and language-based explanations to improve transparency. Among other honors, Andreas has received Samsung’s AI Researcher of the Year award, MIT’s Kolokotrones teaching award, and paper awards at NAACL and ICML.

Andreas received his BS from Columbia; his M.Phil from Cambridge (where he studied as a Churchill scholar), and his Ph.D. degree in natural language processing from Berkeley. A research scientist at Microsoft Semantic Machines, Andreas joined Microsoft as a senior researcher. He remains at Microsoft, and is now a principal researcher. He joined MIT as an Assistant Professor in EECS in July 2019.

Christina Delimitrou has been promoted to Associate Professor without tenure. Delimitrou’s research sits at the intersection of computer architecture and computer systems; specifically, she is one of the first systems researchers to apply machine learning (ML) techniques to design and management problems in the cloud. One key advantage of cloud computing is the possibility of dynamic allocation of servers to individual components and incoming requests, which is especially valuable for applications that experience highly dynamic or unpredictable load.  These exact characteristics make deploying applications on the cloud complex. Delimitrou’s work addresses two key questions in this space: First, how should we build hardware that populates cloud datacenters today, and second, how many and which specific resources should we allocate to each application, such that services meet their performance constraints and the cloud is used efficiently? 

Delimitrou’s work has been broadly recognized. Among other awards, she has received the IEEE TCCA Young Architect Award, the NSF CAREER award, the Sloan Fellowship, the Google Faculty Research Award, the Google Research Award in Recognition of Technical Leadership and Achievements in Systems Research, the Google-Initiated Focused Research Award, two Facebook Research Faculty Awards, the Microsoft Research Faculty Fellowship, the Intel Rising Star Award, two Intel Research Awards, and the Cornell School of Engineering Research Excellence Award, as well as multiple best paper awards and “top conference pick” awards. 

Christina obtained her BS from the National Technical University of Athens in 2009 and her Ph.D. from Stanford in 2015. She was a postdoc at Stanford from 2015-2016, before joining Cornell as an Assistant Professor in 2016. She joined MIT as an Assistant Professor in 2022.

Kevin O’Brien has been promoted to Associate Professor without tenure. O’Brien’s research efforts focus on developing tools to enhance the measurement of quantum systems, most notably quantum computers. He has made pioneering contributions in the amplification of low-energy quantum signals by developing a new type of amplifier. He then deciphered the noise sources of that approach, enabling him to propose an improved amplifier approach that could achieve performance within 0.1% of the quantum limit.  To improve the readout of quantum information, he developed a purely nonlinear circuit to couple quantum devices to the rest of the world, enabling an order of magnitude increase in the coupling, with direct implications for faster readout.

O’Brien received his BS in Physics from Purdue University before going on to earn his Ph.D. from UC Berkeley in Physics in 2016. He performed postdoctoral research at UC Berkeley for two years before joining MIT as an Assistant Professor in EECS in July 2018.

Jonathan Ragan-Kelley has been promoted to Associate Professor without tenure. A pioneer in the development of high-performance domain-specific languages (especially for computer graphics), Ragan-Kelley has repeatedly identified important domains that require significant expert effort to deliver the necessary performance before developing new high-level programming languages that capture this expertise and can deliver high performance with less effort and lower risk of bugs. Ragan-Kelley’s computer graphics language Halide has become the industry standard for image processing, and is used by companies including Google, Meta (Instagram), and Adobe, among others. His earlier work, on the system Lightspeed, was used to produce movies for several years at Industrial Light and Magic and was a finalist for a technical Oscar award. Ragan-Kelley’s work has earned him the ACM SIGGRAPH Significant New Researcher Award, the highest award given by the community to young researchers. His work has also been featured in CACM research highlights in 2018 and 2019. 

Ragan-Kelley obtained his PhD from MIT in 2014, and after spending time as a postdoctoral researcher at Stanford (2014-2016), a visiting scientist at Google (2016-2017), and an Assistant Professor at Berkeley (2017-2019), he joined MIT in January of 2020.

To Associate Professor with tenure: 

Tamara Broderick is being promoted to Associate Professor with tenure, effective July 1, 2023. Broderick joined the Department in 2015; she is affiliated with the MIT Laboratory for Information and Decision Systems (LIDS), the MIT Statistics and Data Science Center, and the Institute for Data, Systems, and Society (IDSS). Broderick works in the fields of machine learning and statistics. Her research focuses on providing fast and reliable quantification of both uncertainty and robustness in complex data analysis procedures. Together with her team and collaborators, she provides data analysis tools in areas ranging from genetics to economics to assistive technology.

Broderick earned her Ph.D. in Statistics at the University of California, Berkeley in 2014. Previously, she received an AB in Mathematics from Princeton University, a Master of Advanced Study for completion of Part III of the Mathematical Tripos from the University of Cambridge, an MPhil by research in Physics from the University of Cambridge, and an MS in Computer Science from the University of California, Berkeley. Among many other honors, Broderick has been awarded selection to the COPSS Leadership Academy (2021), an Early Career Grant (ECG) from the Office of Naval Research (2020), the Ruth and Joel Spira Award for Distinguished Teaching (2020), the Junior Bose Award (2019), an NSF CAREER Award (2018), a Sloan Research Fellowship (2018), an Army Research Office Young Investigator Program (YIP) award (2017), the Jerome H. Saltzer Award (2017), Google Faculty Research Awards, and an Amazon Research Award.

Justin Solomon is being promoted to Associate Professor with tenure, effective July 1, 2023. Solomon joined the Department in 2016. He is also an affiliate of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), where he leads the Geometric Data Processing group, which studies problems at the intersection of geometry, large-scale optimization, computer graphics, and machine learning. Solomon and his team have tackled a diverse array of challenges in applied geometry, from developing machine learning for 3D data to identifying geometric structures in abstract datasets, assessing compliance of political redistricting plans with civil rights law, and assisting digital artists as they create sketches and 3D models. Solomon’s passion for geometry processing led him to create the Summer Geometry Initiative, a six-week research program designed to introduce undergraduate and graduate students to the field. 

Solomon earned his BS, MS, and PhD from Stanford University before taking a postdoctoral appointment at Princeton University for a year and then joining MIT in 2016. Additionally, he has conducted research at Pixar Animation Studios, the University of Southern California, and the British Library Sound Archives. His textbook, “Numerical Algorithms,” was published in 2015. Solomon’s many awards and honors include the Harold E. Edgerton Faculty Achievement Award (2023); the ACM SIGGRAPH Significant New Researcher Award (2022); the Seth J. Teller Award for Excellence, Inclusion, and Diversity (2022); the Google Research Scholar Award (2022); the Teaching With Digital Technology Award (2021); the Junior Bose Award (2020); the NSF BIGDATA Award (with P. Rigollet, in 2018), and the Amazon Research Award (2018).

To Full Professor:

Daniel Sanchez is being promoted to Full Professor. Sanchez works in the field of computer architecture. He has designed techniques to make general-purpose parallel processors more efficient, including software-managed cache hierarchies and Swarm, an architecture to exploit unstructured parallelism. Recently, he has also focused on specialized hardware accelerators, specifically for sparse algorithms (including graph analytics and sparse linear algebra) and fully homomorphic encryption (FHE). His prolific work has led to the publication of at least 16 articles in top conferences and journals since 2019; his honors include multiple IEEE Micro Top Pick Awards, the Louis Smullin Award for teaching at MIT, multiple Faculty Research Awards from Google and Facebook, an NSF CAREER Award, and induction into the Halls of Fame of MICRO, ISCA, and HPCA. 

Sanchez received his BS in Telecommunications Engineering from the Technical University of Madrid, UPM in 2007, and his MS in Electrical Engineering from Stanford in 2009. He received his PhD from Stanford in 2012, and immediately joined MIT as an Assistant Professor. He was promoted to AWOT in 2017, and was granted tenure in 2019.

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