Asu Ozdaglar

About

Asu Ozdaglar is a faculty member at MIT EECS with a focus on electrical engineering and computer science. Her research areas include systems theory, control, and autonomy, as well as optimization and game theory. She is involved in developing groundbreaking systems that sense, process, and transmit energy and information, leveraging computational, theoretical, and experimental tools to address shared challenges facing humanity. Her work encompasses a broad spectrum of topics within electrical engineering and computer science, emphasizing the development of innovative algorithms, systems, and theoretical frameworks.

Research topics

• Computer science
• Computer network
• Mathematics
• Economics
• Microeconomics

Selected publications

• Network security and contagion

  Journal of Economic Theory · 2016-10-10 · 159 citations

  articleOpen accessSenior author
  PublisherOA PDFDOI

• Beyond Shannon: the quest for fundamental performance limits of wireless ad hoc networks

  IEEE Communications Magazine · 2011-05-01 · 96 citations

  article

  We describe a new theoretical framework for determining fundamental performance limits of wireless ad hoc networks. The framework expands the traditional definition of Shannon capacity to incorporate notions of delay and outage. Novel tools are described for upper and lower bounding the network performance regions associated with these metrics under a broad range of assumptions about channel and network dynamics, state information, and network topologies. We also develop a flexible and dynamic i…

  PublisherDOI

• Estimating Social Network Structure and Propagation Dynamics for an Infectious Disease

  Lecture notes in computer science · 2014-01-01 · 18 citations

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  PublisherDOI

• Asynchronous CSMA Policies in Multihop Wireless Networks With Primary Interference Constraints

  IEEE Transactions on Information Theory · 2011-05-25 · 12 citations

  articleSenior author

  We analyze asynchronous carrier sense multiple access (CSMA) policies for scheduling packet transmissions in multihop wireless networks subject to collisions under primary interference constraints. While the (asymptotic) achievable rate region of CSMA policies for single-hop networks has been well-known, their analysis for general multihop networks has been an open problem due to the complexity of complex interactions among coupled interference constraints. Our work resolves this problem for net…

  PublisherDOI

• Global Convergence Rate of Proximal Incremental Aggregated Gradient Methods

  SIAM Journal on Optimization · 2018-01-01 · 8 citations

  preprintOpen accessSenior author

  We focus on the problem of minimizing the sum of smooth component functions (where the sum is strongly convex) and a nonsmooth convex function, which arises in regularized empirical risk minimization in machine learning and distributed constrained optimization in wireless sensor networks and smart grids. We consider solving this problem using the proximal incremental aggregated gradient (PIAG) method, which at each iteration moves along an aggregated gradient (formed by incrementally updating gr…

  PublisherOA PDFDOI

Frequent coauthors

• Daron Acemoğlu

  Massachusetts Institute of Technology

  10 shared

• Azarakhsh Malekian

  5 shared

• James Siderius

  4 shared

• Ali Makhdoumi

  3 shared

• N. Denizcan Vanli

  Massachusetts Institute of Technology

  3 shared

• Mert Gürbüzbalaban

  Rutgers, The State University of New Jersey

  3 shared

• Muriel Médard

  Massachusetts Institute of Technology

  3 shared

• Ali ParandehGheibi

  Cisco College

  2 shared

Awards & honors

• Edgerton Award winners (2026)

Similar researchers at Massachusetts Institute of Technology

• Manolis Kellish-164
• Antonio Torralbah-133
• Daniela Rush-129