Postdoctoral Fellow, Mila & Polytechnique Montreal
Email: FirstnameLastname [AT] gmail [DOT] com (note: use c instead of ç)
I am a postdoctoral fellow at Mila – Quebec AI Institute, affiliated with Polytechnique Montreal. My current research focuses on designing energy-efficiently machine learning models by leveraging algorithm-hardware co-design. I obtained my bachelor's and master's degrees at the NOVA University Lisbon in 2015 and 2017, respectively, and my doctorate degree at the Hasso Plattner Institute in 2021.
- J. Kern, S. Henwood, G. Mordido, E. Dupraz, A. Aissa-El-Bye, Y. Savaria, F. Leduc-Primeau. MemSE: Fast MSE prediction for noisy memristor-based DNN accelerators. AICAS 2022.
- Y. Zhang, Y. Savaria, S. Zhao, G. Mordido, M. Sawan, F. Leduc-Primeau. Tiny CNN for seizure prediction in wearable biomedical devices. EMBC 2022.
- G. Mordido, M. Keirsbilck, A. Keller. Compressing 1D time-channel separable convolutions
using sparse random ternary matrices. INTERSPEECH 2021.
- G. Mordido, H. Yang, C. Meinel. Evaluating post-training compression in GANs using
locality-sensitive hashing. Preprint.
- G. Mordido*, J. Niedermeier*, C. Meinel. Assessing image and text generation with topological
analysis and fuzzy logic. WACV 2021.
- G. Mordido, C. Meinel. Mark-Evaluate: Assessing language generation using population
estimation methods. COLING 2020.
- J. Sauder*, T. Hu*, X. Che, G. Mordido, H. Yang and C. Meinel. Best student forcing: A simple training mechanism in adversarial language generation. LREC 2020.
- G. Mordido, M. Keirsbilck, A. Keller. Monte Carlo gradient quantization. CVPR 2020 EDLCV workshop.
- J. Niedermeier*, G. Mordido* and C. Meinel. Improving the evaluation of generative models with fuzzy logic. AAAI 2020 Meta-Eval workshop.
- G. Mordido, H. Yang, and C. Meinel. microbatchGAN: Stimulating diversity with
multi-adversarial discrimination. WACV 2020.
- G. Mordido*, M. Keirsbilck*, A. Keller. Instant quantization of neural networks using Monte Carlo methods. NeurIPS 2019 EMC2 workshop.
- J. Sauder, X. Che, G. Mordido, H. Yang and C. Meinel. Pseudo-ground-truth for adversarial text generation using reinforcement learning. NeurIPS 2018 Deep RL workshop.
- G. Mordido, H. Yang, and C. Meinel. Dropout-GAN: Learning from a dynamic ensemble of
discriminators. KDD 2018 DL'Day.
- G. Mordido, J. Magalhaes, and S. Cavaco. Automatic organisation, segmentation, and filtering of
user-generated audio content. MMSP 2017.
- G. Mordido, J. Magalhaes, and S. Cavaco. Automatic organisation and quality analysis of
user-generated content with audio fingerprinting. EUSIPCO 2017.
- I love traveling and have had the pleasure of visiting close to 40 countries.
- Yes, orange is my favorite color :)