Ayse Coskun

About

Dr. Ayse Coskun is a Professor of Electrical and Computer Engineering in the College of Engineering at Boston University. She is also an affiliated faculty member in the Department of Computer Science and serves as the Director of the Center for Information and Systems Engineering. Her research interests include energy-efficient computing, cloud computing, high performance computing, computer architecture, and embedded systems. Dr. Coskun holds additional affiliations with the Hariri Institute and the Division of Systems Engineering. She has received numerous honors and awards, including the IBM Faculty Award in 2020, the NSF CAREER Award from 2012 to 2017, and the Ernest S. Kuh Early Career Award from the IEEE Council on Electronic Design Automation in 2017. Her editorial roles include Deputy Editor-in-Chief of the IEEE Transactions on Computer Aided Design since 2022, and associate editor positions for several prominent journals such as ACM Transactions on Architecture and Code Optimization, IEEE Transactions on Computers, and Elsevier Microelectronics Journal. Dr. Coskun earned her PhD from the University of California, San Diego, and is actively involved in advancing research in her fields of expertise.

Research topics

• Computer Science
• Materials science
• Machine Learning
• Engineering
• Data Mining
• Electrical engineering
• Embedded system
• Programming language
• Operating system
• Computer network

Selected publications

• Counterfactual Explanations for Multivariate Time Series

  2021 · 71 citations

  Senior authorCorresponding

  Multivariate time series are used in many science and engineering domains, including health-care, astronomy, and high-performance computing. A recent trend is to use machine learning (ML) to process this complex data and these ML-based frameworks are starting to play a critical role for a variety of applications. However, barriers such as user distrust or difficulty of debugging need to be overcome to enable widespread adoption of such frameworks in production systems. To address this challenge,…

  DOI

• Monolithic 3D Integrated Circuits: Recent Trends and Future Prospects

  IEEE Transactions on Circuits & Systems II Express Briefs · 2021 · 65 citations

  Monolithic 3D integration technology has emerged as an alternative candidate to conventional transistor scaling. Unlike conventional processes where multiple metal layers are fabricated above a single transistor layer, monolithic 3D technology enables multiple transistor layers above a single substrate. By providing vertical interconnects with physical dimensions similar to conventional metal vias, monolithic 3D technology enables unprecedented integration density and high bandwidth communicatio…

  DOI

• Cross-Layer Co-Optimization of Network Design and Chiplet Placement in 2.5-D Systems

  IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · 2020 · 50 citations

  1st authorCorresponding

  2.5-D integration technology is gaining attention and popularity in manycore computing system design. 2.5-D systems integrate homogeneous or heterogeneous chiplets in a flexible and cost-effective way. The design choices of 2.5-D systems impact overall system performance, manufacturing cost, and thermal feasibility. This article proposes a cross-layer co-optimization methodology for 2.5-D systems. We jointly optimize the network topology and chiplet placement across logical, physical, and circui…

  DOI

• Analysis of Power Consumption and GPU Power Capping for MILC

  2024-11-17 · 10 citations

  article

  Power has been a key constraint for supercomputers, and limitations on power become increasingly noticeable through the exascale era. Limited power availability pushes the facilities to operate under power constraints and develop power management methods, making it crucial to understand applications’ power consumption behavior and their performance under power constraints. In this study, we examine the power consumption of MILC, a widely used lattice quantum chromodynamics application, on the Pe…

  PublisherDOI

• Why transparency matters for sustainable data centers and carbon-neutral artificial intelligence (AI)

  iScience · 2025-10-06 · 8 citations

  reviewOpen access

  As artificial intelligence (AI) applications demand substantial computational power, their energy consumption and the attendant carbon footprint of data centers are accelerating at an alarming rate. Due to increasing demand, data centers could consume 9% of global electricity demand by 2030. However, the path toward more sustainable AI and carbon-neutral data centers is hindered by the lack of transparency in data sharing. Without access to operational data from data centers, researchers face li…

  PublisherDOI

Recent grants

• CAREER: 3D Stacked Systems for Energy-Efficient Computing: Innovative Strategies in Modeling and Runtime Management

  NSF · $450k · 2012–2017

• SHF: Small: Reclaiming Dark Silicon via 2.5D Integrated Systems with Silicon Photonic Networks

  NSF · $450k · 2017–2021

• SHF: Small: Collaborative Research: Managing Thermal Integrity in Monolithic 3D Integrated Systems

  NSF · $250k · 2019–2022

Frequent coauthors

• Vitus J. Leung

  Sandia National Laboratories

  29 shared

• Tajana Rosing

  26 shared

• Sherief Reda

  25 shared

• Burak Aksar

  Boston University

  20 shared

• Manuel Egele

  Boston University

  20 shared

• Emre Ateş

  18 shared

• Yvain Thonnart

  CEA Grenoble

  17 shared

• David Atienza

  École Polytechnique Fédérale de Lausanne

  17 shared

Labs

• Data Mining & Data ManagementPI

Education

• Ph.D., Computer Science

  University of California, San Diego

  2007

• M.S., Computer Science

  University of California, San Diego

  2003

• B.S., Computer Engineering

  Bogazici University

  2001

Awards & honors

• IBM Faculty Award (IBM Global University Program Academic Aw…
• Invited participant at the National Academy of Engineering F…
• Best Artifact Award at the International European Conference…
• Ernest S. Kuh Early Career Award, IEEE Council on Electronic…
• Gauss Award at the International Supercomputing Conference –…

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