Lu Yin

l.yin@surrey.ac.uk ; l.yin@tue.nl

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Greetings! I’m Lu, an Assistant Professor in the School of Computer Science and Electronic Engineering at the University of Surrey. I am honored to be a long-term visitor and collaborator with the Visual Informatics Group (VITA) at UT Austin, led by Prof. Atlas Wang. Additionally, I am a long-term visiting researcher at Eindhoven University of Technology (TU/e).

Previously, I served as a Postdoctoral Fellow at TU/e and worked as a research scientist intern at Google’s New York City office.

My research interests include:

  • #AI Efficiency
  • #AI for Science
  • #Large Language Models

Feel free to reach out if you’d like to discuss anything with me :)




News

Dec, 2024 [CAI 2024 Workshop X2] 🔥 Thrilled to co-organize CAI 2024 Workshop LLM Stable Pretraining and Federated Optimization and Learning.
Sep, 2024 [NeurIPS 2024 ] one paper got accepted by NeurIPS 2024: E2ENet
Sep, 2024 [EMNLP 2024 X2] Two paper got accepted by EMNLP 2024: FFN-SkipLLM and C4 Pruning Enough?
Aug, 2024 [BMVC 2024] We got one paper accepted at BMVC 2024: Are Sparse Neural Networks Better Hard Sample Learners?
Jun, 2024 [Interspeech 2024×2] 🔥 We got TWO paper in collaboration with Meta London have been accepted at Interspeech 2024: Data Prunning for ASR and Training ASR from scatch.
Jun, 2024 [NeurIPS Challenge] 🔥 Excited to co-organize NeurIPS 2024 challenge Edge-Device Large Language Model Competition. We invite you to join the competition!
May, 2024 [ICML 2024×3] 🔥 We got THREE paper accepted at ICML 2024: (1) LLM pruning OWL (with Google Research) (2) understanding the small magnitude in LLM JunkDNA hypothesis (with Intel Research). (3) BiDST
Jan, 2024 [ICLR 2024] One paper got accepted by ICLR 2024: NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization
Jan, 2024 [Takl CityU] Honored to be invited to give a talk about The Power of Model Sparsity at Multimedia Analytics (MA) Laboratory in City University of Hong Kong.
Dec, 2023 [CPAL 2024×3] Three papers got accpeted in CPAL at spotlight track
Dec, 2023 [Grant: NWO] We have been awarded 10,000,000 credits for the use of NVIDIA A100 GPUs, totaling 78,120 hours. Our sincere thanks go to NWO.
Jul, 2023 [NeurIPS 2023] One paper got accepted by NeurIPS 2023: Dynamic Sparsity Is Channel-Level Sparsity Learner
Jul, 2023 [Intern: Google] I am joining Google's NYC office as a researcher intern.
Jun, 2023 [ECML 2023×2] Two paper got accepted by ECML-PKDD 2023: Robust overfitting, RDebiased Sparse Training
Apr, 2023 [ICML 2023] One paper got accepted by ICML 2023: Large Kernel Distillation
Nov, 2022 [AAAI 2023] Our paper Lottery Pools got accepted by AAAI 2023
Nov, 2022 [LoG 2022 BEST PAPER] Our paper Untrained GNNs Tickets receive the Best Paper Award from LoG 2022
Sep, 2022 [Talk: CMU] I was invited to give a talk about Model/supervision Efficency at Xu Lab in Carnegie Mellon University
May, 2022 [UAI 2022] Our paper Sup-tickets sparse training got accepted by UAI 2022
Mar, 2022 [IDA 2022] Our paper is accpeted by IDA 2022, which was also the first conference (symposium) that I have attended in the first year of my PhD. Life is like a cycle :smile: