Shashank Nag

Shashank Nag

PhD Student, Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin

I am a PhD student in the Laboratory of Computer Architecture (LCA) at The University of Texas at Austin, advised by Prof. Lizy K. John. Previously, I received my Bachelor of Technology in Electrical Engineering from the Indian Institute of Technology (IIT) Madras.

My research spans Machine Learning–Hardware Co-Design and Computer Architecture. Currently, my work focuses on LUT-based Weightless Neural Networks (WNNs) and designing ultra-energy-efficient accelerators for edge inference.

News

  • [July 2026] “Better Call SoL: Enhancing GPUs with a Sea of LUTs Core”, Nag, et al. accepted at MICRO 2026 (Athens, Greece).
  • [March 2026] “HMix: An Efficient Hardware Accelerator for Quantized MLP-Mixer Inference”, Shyam, Nag, John, accepted at CF 2026 (Catania, Italy).
  • [Jan 2026] “HELIOS: Adaptive Model And Early-Exit Selection for Efficient LLM Inference Serving”, Kumar, Nag, et al. accepted at MLSys 2026 (Bellevue, WA).
  • [Oct 2025] “LL-ViT: Edge Deployable Vision Transformers with Look Up Table Neurons”, Nag et al. accepted at FPT 2025 (Shanghai, China).
  • [May 2025] “Hybrid Weightless Neural Networks for efficient edge inference”, Jadhao, Bacellar, Nag, et al. accepted at FPL 2025 (Leiden, NL).
  • [April 2025] Our team was selected as one of the finalists in the Qualcomm Innovation Fellowship (QIF) North America 2025.
  • [March 2025] Presented at the Young Architect’s Workshop (YArch) at ASPLOS 2025.
  • [Feb 2025] “tinyML for Human Activity Recognition”, Bacellar, Jadhao, Nag, et al. accepted at EdgeAI Symposium 2025 (Austin, TX).
  • [June 2024] “Lightweight Vision Transformers for Low Energy Edge Inference”, Nag, et al. accepted at the MLArchSys Workshop, co-located at ISCA 2024 (Buenos Aires, Argentina).
  • [May 2024] “LogicNets vs. ULEEN: Comparing two novel high throughput edge ML inference techniques on FPGA”, Nag*, Susskind*, et al. accepted at IEEE MWSCAS 2024 (Springfield, MA).
  • [Aug 2023] Started my PhD program in Electrical and Computer Engineering at UT Austin, advised by Prof. Lizy K. John. Hook ‘em! 🤘
  • [Jan 2023] “ViTA: a Vision Transformer Inference Accelerator for Edge Applications”, Nag, et al. accepted at IEEE ISCAS 2023 (Monterey, CA).