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Alicia Golden

PhD Candidate, Computer Science
Harvard University


Email: aliciagolden@g.harvard.edu

Hello! My name is Alicia, and I am a fourth-year PhD candidate at Harvard University advised by David Brooks and Gu-Yeon Wei. My research sits at the intersection of computer architecture, machine learning, and systems, with a focus on designing efficient hardware systems for large-scale AI. Prior to Harvard, I completed my undergrad at Cornell University, where I received a B.S. in Electrical and Computer Engineering with a minor in Computer Science.

Stay tuned for our upcoming work on comparing AI accelerators! Link will be posted here soon.

Selected Publications

  • [ACM SIGENERGY 2025] Wafer-Scale Systems: A Carbon Perspective.
    Alicia Golden, Mariam Elgamal, Abdulrahman Mahmoud, Gage Hills, Carole-Jean Wu, Gu-Yeon Wei, David Brooks.
    ACM SIGENERGY Energy Informatics Review, Volume 5, Issue 2, July 2025.

  • [ISCA 2024] MAD Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems.
    Samuel Hsia, Alicia Golden, Bilge Acun, Newsha Ardalani, Zachary DeVito, Gu-Yeon Wei, David Brooks, Carole-Jean Wu.
    International Symposium on Computer Architecture (ISCA), June 2024.

  • [ISPASS 2024] Generative AI Beyond LLMs: System Implications of Multi-Modal Generation.
    Alicia Golden, Samuel Hsia, Fei Sun, Bilge Acun, Basil Hosmer, Yejin Lee, Zachary DeVito, Jeff Johnson, Gu-Yeon Wei,
    David Brooks, Carole-Jean Wu.
    International Symposium on Performance Analysis of Systems and Software (ISPASS), May 2024.

  • [EMC2 2024] Is Flash Attention Stable?
    Alicia Golden, Samuel Hsia, Fei Sun, Bilge Acun, Basil Hosmer, Yejin Lee, Zachary DeVito, Jeff Johnson, Gu-Yeon Wei,
    David Brooks, Carole-Jean Wu.
    The 9th Energy Efficient Machine Learning and Cognitive Computing (EMC2) Workshop co-located with The ACM International
    Conference on Architectural Support for Programming Languages and Operating Systems, April 2024.

  • [IEEE Micro 2025] Characterizing and efficiently accelerating multimodal generation model inference.
    Yejin Lee, Alicia Golden, Anna Sun, Basil Hosmer, Bilge Acun, Can Balioglu, Changhan Wang, Charles David Hernandez,
    Christian Puhrsch, Daniel Haziza, Driss Guessous, Francisco Massa, Jacob Kahn, Jeffrey Wan, Jeremy Reizenstein, Jiaqi
    Zhai, Joe Isaacson, Joel Schlosser, Juan Pino, Kaushik Ram Sadagopan, Leonid Shamis, Linjian Ma, Min-Jae Hwang,
    Mingda Chen, Mostafa Elhoushi, Pedro Rodriguez, Ram Pasunuru, Samuel Hsia, Scott Yih, Sravya Popuri, Xing Liu, Carole-
    Jean Wu.  
    IEEE MICRO, September 2025.

  • [ICLR 2026] Composer: A search framework for hybrid neural architecture design.
    Bilge Acun, Prasoon Sinha, Newsha Ardalani, Sangmin Bae, Alicia Golden, Chien-Yu Lin, Meghana Madhyastha, Fei Sun, Neeraja J
    Yadwadkar, Carole-Jean Wu.
    International Conference on Learning Representations (ICLR), April 2026.

Professional Experience

  • AI Research Scientist Intern, Meta FAIR (Fundamental AI Research Group)
  • ASIC Design Intern, SpaceX
  • Silicon Design Engineering Intern, Advanced Micro Devices (AMD)
  • Software Engineering Intern, 3M

News

  • July 2025 Presented our work, Wafer-Scale Systems: A Carbon Perspective, at HotCarbon 2025!
  • May 2024 Presented our work, Generative AI Beyond LLMs: System Implications of Multi-Modal Generation, at ISPASS 2024!
  • April 2024 Presented poster at Computing Research Association – Widening Participation Grad Cohort Workshop
  • March 2024 Accepted to the Young Architect’s Workshop to be held with ASPLOS ’24
  • March 2024 ISCA Paper Accepted!
  • February 2024 ISPASS Paper Accepted!
  • May 2023 Meta FAIR (Fundamental AI Research) Internship