World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
9539
World Ranking
4394
National Ranking
2050

Electronics and Electrical Engineering

D-Index
55
Citations
9369
World Ranking
2219
National Ranking
869

Research.com Recognitions

  • 2019 - ACM Fellow For contributions to the design and optimization of energy-aware computing systems
  • 2015 - IEEE Fellow For contributions to design and optimization of energy-aware computing systems
  • 2011 - ACM Distinguished Member
  • 2009 - ACM Senior Member

Overview

Diana Marculescu is affiliated with The University of Texas at Austin in the United States. The primary fields of study in their research include Computer Science and Engineering, with a particular focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering, Signal Processing, and Hardware and Architecture.

Their research topics encompass Advanced Neural Network Applications, Adversarial Robustness in Machine Learning, Domain Adaptation and Few-Shot Learning, Advanced Memory and Neural Computing, Music and Audio Processing, CCD and CMOS Imaging Sensors, and Speech and Audio Processing.

Marculescu has contributed to various publication venues with a concentration of work in arXiv (Cornell University), totaling 41 publications. Other venues include Lecture Notes in Computer Science, the 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Proceedings of the AAAI Conference on Artificial Intelligence, and the IEEE Journal of Selected Topics in Signal Processing.

Selected recent papers authored or co-authored by Diana Marculescu include:

  • "Single-Path NAS: Designing Hardware-Efficient ConvNets in Less Than 4 Hours" (2020), published in Lecture Notes in Computer Science
  • "AVE-CLIP: AudioCLIP-based Multi-window Temporal Transformer for Audio Visual Event Localization" (2023), presented at the 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • "DeepNVM++: Cross-Layer Modeling and Optimization Framework of Non-Volatile Memories for Deep Learning" (2020), available on arXiv (Cornell University)
  • "SupMAE: Supervised Masked Autoencoders Are Efficient Vision Learners" (2022), available on arXiv (Cornell University)
  • "MobileTL: On-Device Transfer Learning with Inverted Residual Blocks" (2023), featured in Proceedings of the AAAI Conference on Artificial Intelligence

Frequent co-authors in their work include Tanvir Mahmud, Ting-Wu Chin, Ahmet Inci, Hung-Yueh Chiang, and Ruizhou Ding.

Marculescu has received several professional recognitions, including being named an ACM Fellow in 2019 for contributions to the design and optimization of energy-aware computing systems, IEEE Fellow status in 2015 for similar contributions, ACM Distinguished Member in 2011, and ACM Senior Member in 2009.

Best Publications

  • Analysis of dynamic voltage/frequency scaling in chip-multiprocessors

    Sebastian Herbert;Diana Marculescu

  • Electronic textiles: a platform for pervasive computing

    D. Marculescu;R. Marculescu;N.H. Zamora;P. Stanley-Marbell

  • Power and performance evaluation of globally asynchronous locally synchronous processors

    Anoop Iyer;Diana Marculescu

  • Single-Path NAS: Designing Hardware-Efficient ConvNets in less than 4 Hours

    Dimitrios Stamoulis;Ruizhou Ding;Di Wang;Dimitrios Lymberopoulos

  • The EDA Challenges in the Dark Silicon Era: Temperature, Reliability, and Variability Perspectives

    Muhammad Shafique;Siddharth Garg;Jörg Henkel;Diana Marculescu

  • Voltage-frequency island partitioning for GALS-based networks-on-chip

    Umit Y. Ogras;Radu Marculescu;Puru Choudhary;Diana Marculescu

  • MARS-C: modeling and reduction of soft errors in combinational circuits

    Natasa Miskov-Zivanov;Diana Marculescu

  • Switching Activity Analysis Considering Spatioternporal Correlations

    Radu Marculescu;Diana Marculescu;Massoud Pedram

  • Design and Management of Voltage-Frequency Island Partitioned Networks-on-Chip

    Umit Y. Ogras;Radu Marculescu;Diana Marculescu;Eun Gu Jung

  • Regularizing Activation Distribution for Training Binarized Deep Networks

    Ruizhou Ding;Ting-Wu Chin;Zeye Liu;Diana Marculescu

  • Information theoretic measures for power analysis [logic design]

    D. Marculescu;R. Marculescu;M. Pedram

  • Variation-aware dynamic voltage/frequency scaling

    Sebastian Herbert;Diana Marculescu

  • Circuit Reliability Analysis Using Symbolic Techniques

    N. Miskov-Zivanov;D. Marculescu

  • Multiple Transient Faults in Combinational and Sequential Circuits: A Systematic Approach

    N Miskov-Zivanov;D Marculescu

  • Efficient Power Estimation for Highly Correlated Input Streams

    Radu Marculescu;Diana Marculescu;Massoud Pedram

  • Towards Efficient Model Compression via Learned Global Ranking

    Ting-Wu Chin;Ruizhou Ding;Cha Zhang;Diana Marculescu

  • Probabilistic modeling of dependencies during switching activity analysis

    R. Marculescu;D. Marculescu;M. Pedram

  • Cherry-picking: exploiting process variations in dark-silicon homogeneous chip multi-processors

    Bharathwaj Raghunathan;Yatish Turakhia;Siddharth Garg;Diana Marculescu

  • Information theoretic measures of energy consumption at register transfer level

    Diana Marculescu;Radu Marculescu;Massoud Pedram

  • On the Use of Microarchitecture-Driven Dynamic Voltage Scaling

    Diana Marculescu

Frequent Co-Authors

Radu Marculescu
Radu Marculescu The University of Texas at Austin
Partha Pratim Pande
Partha Pratim Pande Washington State University
Massoud Pedram
Massoud Pedram University of Southern California
Umit Y. Ogras
Umit Y. Ogras University of Wisconsin–Madison
Dimitrios Lymberopoulos
Dimitrios Lymberopoulos Microsoft (United States)
Cha Zhang
Cha Zhang Microsoft (United States)
Jie Liu
Jie Liu Harbin Institute of Technology
Chi-Ying Tsui
Chi-Ying Tsui Hong Kong University of Science and Technology
Pradeep K. Khosla
Pradeep K. Khosla University of California, San Diego
Yao-Wen Chang
Yao-Wen Chang National Taiwan University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For those pursuing a future in Electronics and Electrical Engineering, exploring related online degrees can open new doors. Many professionals today start with certificate programs that pay well. These accelerated options offer practical skills and fast entry into the workforce, complementing traditional engineering knowledge.

Additionally, careers in engineering often appeal to individuals who prefer less social interaction. If you identify as an introvert, consider checking out the list of introvert jobs that pay well, many of which align with technical and engineering fields. This balance helps foster a productive and comfortable work environment.

For those interested in leadership roles, combining technical expertise with management skills is highly advantageous. Enrolling in an accelerated project management degree can fast-track professionals into supervisory positions. These programs emphasize skills that bridge the gap between engineering and business.

Moreover, obtaining a bachelor degree in project management online offers flexibility for students balancing studies with work. This degree enhances career prospects by equipping graduates to lead complex engineering projects efficiently.

Best Scientists Citing Diana Marculescu

Trending Scientists

Recently Published Articles