Welcome...

dr. E. Mocanu (Elena)

Assistant Professor

About Me

News

  • 29 March 2024, I have one PhD and one PostDoc open positions on scalable energy-efficient deep learning (link and link)
  • 29 March 2024, I have one PhD open position on sparse training for deep reinforcement learning (link)
  • 19 January 2024, The MISD project was accepted (link). Happy to be part of a larger effort within UT on sustainable data centers.
  • 6 November 2023, Alexander's work on "Enhancing Learning in Sparse Neural Networks: A Hebbian Learning Approach" was nominated for the Best Student Thesis Abstract Award at BNAIC2024.
  • 22 September, 2023 I gave a keynote talk about "Sparse training of neural networks" at the E-pi: Re-thinking Uncertainty and AI Workshop in TU Delft (link)
  • 6 June, 2023 I am doing a short research visit and hold a seminar about "Sparse Training in Deep Reinforcement Learning" at CaSToRC, the National HPC Competence Center - The Cyprus Institute (link)
  • 24 April, 2023 Our tutorial "Sparse Training for Supervised, Unsupervised, Continual, and Deep Reinforcement Learning with Deep Neural Networks" has been accepted at IJCAI 2023.
  • 11 April, 2023 I gave an invited talk on "Sparsity in neural networks" at the Big Data & AI workshop during the Smart Diaspora 2023 conference in Timisoara, Romania.
  • 30 January, 2023 I gave an invited talk on "Scalable and Efficient Agents using Sparse Neural Networks" at the AI for E&S Think Tank, TU Delft (link)
  • 4 January, 2023 Our paper "Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning" has been accepted at AAMAS 2023 (link)
  • 4 January, 2023 The third edition of the workshop "Sparsity in Neural Networks: On practical limitations and tradeoffs between sustainability and efficiency" - SNN 2023 will be colocated with ICLR 2023 (link)
  • 27 October, 2022 I gave an invited talk at the CoMBE Seminar Series, University of Duisburg-Essen 
  • 14 September, 2022 One paper on sparse training and time series classification accepted at NeurIPS 2022 (link)
  • 15 July, 2022 I gave an invited talk during the AI Seminar at the University of Alberta/Alberta Machine Intelligence Institute titled "Sparse training in supervised, unsupervised, and deep reinforcement learning" (link)
  • 13 July, 2022 I was recognised as an Outstanding Reviewer at ICML 2022
  • 13 July, 2022 We are organising the second edition of the "Sparsity in Neural Networks: Advancing Understanding and Practice" Workshop - SNN 2022 (link)
  • 10 June, 2022 I gave an invited talk at Calgary AI, University of Calgary
  • 21 May, 2022 I am doing a research visit to the group of Dr. Matthew Taylor at the University of Alberta
  • 10 May, 2022 Our paper "Dynamic Sparse Training for Deep Reinforcement Learning" received best paper award at ALA 2022, collocated with AAMAS 2022 (link)
  • 25 April, 2022 We had the pleasure of hosting Utku Evci, Research Engineer at Google Brain Montreal, to give a very engaging in-person talk.
  • 20 April, 2022 One paper on sparse training and deep reinforcement learning accepted at IJCAI-ECAI 2022 (link)
  • 15 April, 2022 Our tutorial "Sparse Neural Networks Training" has been accepted at ECMLPKDD 2022 (link)
  • 20 January, 2022 One paper on dynamic sparse training has been accepted at ICLR 2022 (link)

Publications

Recent
Grooten, B., Sokar, G., Dohare, S. , Mocanu, E., Taylor, M. E., Pechenizkiy, M. , & Mocanu, D. C. (2023). Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning. In A. Ricci, W. Yeoh, N. Agmon, & B. An (Eds.), AAMAS '23: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (pp. 1932-1941). (Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS; Vol. 2023). ACM Press. https://dl.acm.org./doi/10.5555/3545946.3598862
Xiao, Q., Zhang, Y., Liu, S., Pechenizkiy, M. , Mocanu, E. , & Mocanu, D. C. (2023). Dynamic Sparse Network for Time Series Classification: Learning What to “See”. Poster session presented at ICLR 2023 Workshop on Sparsity in Neural Networks, Kigali, Rwanda. https://drive.google.com/file/d/10pxPf2aWTdMumUba_8-7v_jEZ3-K_uV3/view
Xiao, Q. , Wu, B., Zhang, Y., Liu, S., Pechenizkiy, M. , Mocanu, E. , & Mocanu, D. C. (2023). Dynamic Sparse Network for Time Series Classification: Learning What to “See”. Poster session presented at ICLR 2023 Workshop on Sparsity in Neural Networks, Kigali, Rwanda. https://drive.google.com/file/d/10pxPf2aWTdMumUba_8-7v_jEZ3-K_uV3/view
Xiao, Q. , Wu, B., Zhang, Y., Liu, S., Pechenizkiy, M. , Mocanu, E. , & Mocanu, D. C. (2022). Dynamic Sparse Network for Time Series Classification: Learning What to “See”. Paper presented at 36th Annual Conference on Neural Information Processing Systems, NeurIPS 2022, New Orleans, Louisiana, United States. https://openreview.net/forum?id=ZxOO5jfqSYw
Sokar, G. A. Z. N. , Mocanu, E. , Mocanu, D. C., Pechenizkiy, M., & Stone, P. (2022). Dynamic Sparse Training for Deep Reinforcement Learning. In L. De Raedt (Ed.), Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI 2022 (pp. 3437-3443) https://doi.org/10.24963/ijcai.2022/477
Grooten, B. J., Sokar, G. , Mocanu, E., Dohare, S., Taylor, M. E., Pechenizkiy, M. , & Mocanu, D. C. (2022). Towards Implementing Truly Sparse Connections in Deep RL Agents. Poster session presented at Sparsity in Neural Networks: Advancing Understanding and Practice 2022, Virtual + ICML meetup.

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Contact Details

Visiting Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (building no. 11)
Hallenweg 19
7522NH  Enschede
The Netherlands

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Mailing Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
P.O. Box 217
7500 AE Enschede
The Netherlands