Moin Nabi

I am a Sr. Principal Scientist in the AI/ML org at Apple (Zürich).

Prior to that, I was a Principal Scientist / Manager at SAP, leading the SAP AI Research team in Berlin. Before that, I was a Postdoctoral Researcher at University of Trento, and a Visiting Scholar at University of Washington. I received a Ph.D. in Computer Science in 2015, working with Vittorio Murino from Italian Institute of Technology and Massimiliano Pontil from University College London (UCL).

I am a member of the European Laboratory for Learning and Intelligent Systems (ELLIS) and a scientific advisor for the European Network of AI Excellence Centres (ELISE).

Email  /  CV  /  Thesis  /  Google Scholar  /  LinkedIn

I am generally interested in identifying and tackling challenging science problems that bridge the gap between academic research and scalable solutions that reach the public. I enjoy developing simple and efficient machine learning algorithms with broad applicability across various problem domains. My current research focuses on the intersection of machine learning, computer vision, and natural language processing, particularly in modeling semantics within multimodal learning, generation, and reasoning.

For the full list of my publications please visit my Google Scholar page.

	A Soft Nearest-neighbor Framework for Continual Semi-supervised Learning Z. Kang, E. Fini, M. Nabi, E. Ricci, K. Alahari IEEE International Conference on Computer Vision (ICCV), 2023   (Oral) PDF / project page / code
	miCSE: Mutual Information Contrastive Learning for Low-shot Sentence Embeddings T. Klein, M. Nabi Association for Computational Linguistics (ACL), 2023   PDF / project page / code
	Semi-supervised Learning Made Simple with Self-supervised Clustering E. Fini, P. Astolfi, K. Alahari, X. Alameda-Pineda, J. Mairal, M. Nabi, E. Ricci IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023   PDF / project page / code
	Solo-learn: A Library of Self-supervised Methods for Visual Representation Learning V. Costa, E. Fini, M. Nabi, N. Sebe, E. Ricci Journal of Machine Learning Research (JMLR), 2022   >1.2k stars on GitHub PDF / code / Documentation
	Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation G. Yang, E. Fini, D. Xu, P. Rota; M. Ding, M. Nabi, X. Alameda-Pineda, E. Ricci IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022   PDF / code
	SCD: Self-Contrastive Decorrelation for Sentence Embeddings T. Klein, M. Nabi Association for Computational Linguistics (ACL), 2022   PDF / code
	A Unified Objective for Novel Class Discovery E. Fini, E. Sangineto, S. Lathuilire, Z. Zhong, M. Nabi, E. Ricci IEEE International Conference on Computer Vision (ICCV), 2021   (Oral) PDF / project page / code
	Attention-based Contrastive Learning for Winograd Schemas T. Klein, M. Nabi Findings of Empirical Methods in Natural Language Processing (EMNLP), 2021   PDF / code
	Towards Zero-shot Commonsense Reasoning with Self-supervised Refinement of Language Models T. Klein, M. Nabi Empirical Methods in Natural Language Processing (EMNLP), 2021   PDF / code
	EaSe: A Diagnostic Tool for VQA based on Answer Diversity S. Jolly, S. Pezzelle, M. Nabi North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), 2021   PDF / code
	Online Continual Learning under Extreme Memory Constraints E. Fini, S. Lathuilire, E. Sangineto, M. Nabi, E. Ricci European Conference on Computer Vision (ECCV), 2020   PDF / code
	Contrastive Self-Supervised Learning for Commonsense Reasoning T. Klein, M. Nabi Association for Computational Linguistics (ACL), 2020   PDF / code
	Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning O. Ostapenko, M. Puscas, T. Klein, P. Jahnichen, M. Nabi IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019   PDF / code / blog
	Budget-Aware Adapters for Multi-Domain Learning R. Berriel, S. Lathuili, M. Nabi, T. Klein, T. Oliveira, N. Sebe, E. Ricci IEEE International Conference on Computer Vision (ICCV), 2019   PDF / code
	Attention Is (not) All You Need for Commonsense Reasoning T. Klein, M. Nabi Association for Computational Linguistics (ACL), 2019   PDF / code
	Self-Paced Deep Learning for Weakly Supervised Object Detection E. Sangineto*, M. Nabi*, D. Culibrk and N. Sebe IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018   PDF / code
	Differentially Private Federated Learning: A Client Level Perspective R. Gayer, T. Klein, M. Nabi Conference on Neural Information Processing Systems (NIPS), 2017   Workshop on Machine Learning on the Phone and Consumer Devices   >1000 Citations PDF / code / blog / poster
	FOIL it! Find One mismatch between Image and Language caption R. Shekhar, S. Pezzelle, A. Herbelot, M. Nabi, E. Sangineto, R. Bernardi Association for Computational Linguistics (ACL), 2017   (Oral) PDF / talk / code / data / blog
	Self-Crowdsourcing Training for Relation Extraction A. Abad, M. Nabi, A. Moschitti Association for Computational Linguistics (ACL), 2017   PDF / bibtex
	Abnormal Event Detection in Videos using Generative Adversarial Nets M. Ravanbakhsh, M. Nabi, E. Sangineto L. Mercenaro, C. Regazzoni, N. Sebe IEEE International Conference on Image Processing (ICIP), 2017   Microsoft Best Student Paper Award PDF / code / bibtex
	Autonomous Crowdsourcing through Human-Machine Collaborative Learning A. Abad, M. Nabi, A. Moschitti Special Interest Group on Information Retrieval (SIGIR), 2017   PDF / bibtex
	Learning with Dataset Bias in Latent Subcategory Models D. Stamos, S. Martelli, M. Nabi, A. McDonald, V. Murino, M. Pontil IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015   PDF / abstract / bibtex

Students and Interns: Enrico Fini (Apple), Stefan Lionar (Now a PhD student at NUS & Sea AI Lab), Jan Nikolas Morshuis (Now a PhD student at University of Tübingen), Aiham Taleb (Now a Applied Scientist at Amazon AWS), Artur Speiser (Now a PhD student at University of Tübingen), Jannik Wolff (Now a PhD student at TU-Berlin), Daniel Dorda (Now a PhD student at ETH-Zürich), Max Bain (Now a PhD student at VGG -- University of Oxford), Mahdyar Ravanbakhsh (Now a senior researcher at Zalando Research), Oleksiy Ostapenko (Now a PhD Student at MILA –- University of Montreal), Colin Samplawski (Now a PhD student at University of Massachusetts Amherst), Mihai M. Puscas (Now a researcher at Huawei Research –- Dublin), Sandro Pezzelle (Now an Assistant Professor at University of Amsterdam), Frederik Pahde (Now a ML Scientist at Amazon), Shailza Jolly (Now a Research Scientist at Amazon), Denis Dushi (Now a ML Engineer at Amazon), Vadim Tschernezki (Now a PhD student at VGG -- University of Oxford & Naver Labs), Robin C. Geyer (Now a PhD Student at Institute for ML in ETH-Zürich & Charité).

Erdös = 3 (via two paths) Thanks Jon!