About Me

I am currently an AI Research Scientist at Meta GenAI, where I focus on LLMs and Agents. I am also a Machine Learning Lecturer at the University of Toronto. Before joining Meta GenAI, I was an AI Research Scientist at Ranking AI Research at Meta working on large-scale graph and sequence learning for monetization. Prior to that, I held the position of Principal AI Research Scientist and Research Manager at the Autodesk AI Lab. I earned my PhD in Electrical and Computer Engineering from the University of Ottawa, with a focus on deep learning for common-sense reasoning in 3D environments. My research encompasses a broad range of deep learning areas, including Generative Learning, Multimodal Learning, Self-Supervised Learning, and Geometric Deep Learning. Currently, my research is focused on Large-Language Models (LLMs), Vision-Language Models (VLMs) and Agents. My reseach has been published in top-tier AI venues including NeurIPS, ICLR, ICML, ICCV, and AAAI. Throughout my career, I have had the pleasure of collaborating with several institutions, including NASA, Stanford University, Vector Institute, and the University of British Columbia.

Publications

	Learning Graph Quantized Tokenizers Limei Wang, Kaveh Hassani, Si Zhang, Dongqi Fu, Baichuan Yuan, Weilin Cong, Zhigang Hua, Hao Wu, Ning Yao, Bo Long International Conference on Learning Representations (ICLR), 2025
	Preference Discerning with LLM-Enhanced Generative Retrieval Fabian Paischer, Liu Yang, Linfeng Liu, Shuai Shao, Kaveh Hassani, Jiacheng Li, Ricky Chen, Zhang Gabriel Li, Xialo Gao, Wei Shao, Xue Feng, Nima Noorshams, Sem Park, Bo Long, Hamid Eghbalzadeh Arxiv Preprint, 2024
	Unifying Generative and Dense Retrieval for Sequential Recommendation Liu Yang, Fabian Paischer, Kaveh Hassani, Jiacheng Li, Shuai Shao, Zhang Gabriel Li, Yun He, Xue Feng, Nima Noorshams, Sem Park, Bo Long, Robert D Nowak, Xiaoli Gao, Hamid Eghbalzadeh Arxiv Preprint, 2024
	How to Make LLMs Strong Node Classifiers? Zhe Xu, Kaveh Hassani, Si Zhang, Hanqing Zeng, Michihiro Yasunaga, Limei Wang, Dongqi Fu, Ning Yao, Bo Long, Hanghang Tong Arxiv Preprint, 2024
	Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale Wei Wen, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Hang Yin, Weiwei Chu, Kaveh Hassani, Mengying Sun, Jiang Liu, Xu Wang, Lin Jiang, Yuxin Chen, Buyun Zhang, Xi Liu, Dehua Cheng, Zhengxing Chen, Guang Zhao, Fangqiu Han, Jiyan Yang, Yuchen Hao, Liang Xiong, Wen-Yen Chen Proceedings of the ACM Web Conference (WWW), 2024
	Staleness-Based Subgraph Sampling for Large-Scale GNNs Training Limei Wang, Si Zhang, Hanqing Zeng, Hao Wu, Zhigang Hua, Kaveh Hassani, Andrey Malevich, Bo Long, Shuiwang Ji Arxiv Preprint, 2024
	Evaluating Graph Generative Models with Contrastively Learned Features Hamed Shirzad, Kaveh Hassani, Danica J Sutherland Neural Information Processing Systems (NeurIPS), 2022
	Material Prediction for Design Automation Using Graph Representation Learning Shijie Bian, Daniele Grandi, Kaveh Hassani, Elliot Sadler, Bodia Borijin, Axel Fernandes, Andrew Wang, Thomas Lu, Richard Otis, Nhut Ho, Bingbing Li Design Automation Conference, 2022
	Cross-Domain Few-Shot Graph Classification Kaveh Hassani AAAI Conference on Artificial Intelligence, 2022
	Classifying Component Function in Product Assemblies With Graph Neural Networks Vincenzo Ferrero, Bryony DuPont, Kaveh Hassani, Daniele Grandi Journal of Mechanical Design, 2022
	Learning Graph Augmentations to Learn Graph Representations Kaveh Hassani, Amir Hosein Khasahmadi Arxiv Preprint, 2022
	Contrastive Multi-View Representation Learning on Graphs Kaveh Hassani, Amir Hosein Khasahmadi International Conference on Machine Learning (ICML), 2020
	PointMask: Towards Interpretable and Bias-Resilient Point Cloud Processing Saeid Asgari Taghanaki, Kaveh Hassani, Pradeep Kumar Jayaraman, Amir Hosein Khasahmadi, Tonya Custis International Conference on Machine Learning (ICML) Workshop on Human Interpretability in Machine Learning, 2020
	Memory-Based Graph Networks Amir Hosein Khasahmadi, Kaveh Hassani, Parsa Moradi, Leo Lee, Quaid Morris International Conference on Learning Representations (ICLR), 2020
	Relational Graph Representation Learning for Open-Domain Question Answering Salvatore Vivona, Kaveh Hassani Neural Information Processing Systems (NeurIPS) Workshop on Graph Representation Learning, 2019
	Unsupervised Multi-Task Feature Learning on Point Clouds Kaveh Hassani, Mike Haley International Conference on Computer Vision (ICCV), 2019
	Disambiguating Spatial Prepositions Using Deep Convolutional Networks Kaveh Hassani, Won-Sook Lee AAAI Conference on Artificial Intelligence, 2017
	Commonsense Knowledge for 3D Modeling: A Machine Learning Approach Kaveh Hassani PhD Thesis, 2017
	Learning Physical Properties of Objects Using Gaussian Mixture Models Kaveh Hassani, Won-Sook Lee Canadian Conference on Artificial Intelligence, 2017
	Visualizing Natural Language Descriptions: A Survey Kaveh Hassani, Won-Sook Lee ACM Computing Surveys, 2016
	Simulating Collective Intelligence of Bio-Inspired Competing Agents Aliakbar Asgari, Kaveh Hassani, Won-Sook Lee Expert Systems with Applications, 2016
	Multi-Objective Design of State Feedback Controllers Using Reinforced Particle Swarm Optimization Kaveh Hassani, Won-Sook Lee Applied Soft Computing, 2016
	A Universal Architecture for Migrating Cognitive Agents: A Case Study on Automatic Animation Generation Kaveh Hassani, Won-Sook Lee Integrating Cognitive Architectures into Virtual Character Design (Book Chapter), 2016
	Adaptive Animation Generation Using Web Content Mining Kaveh Hassani, Won-Sook Lee IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS), 2015
	A Case Study on Collective Intelligence Based on Energy Flow Kaveh Hassani, Aliakbar Asgari, Won-Sook Lee IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS), 2015
	On Designing Migrating Agents: From Autonomous Virtual Agents to Intelligent Robotic Systems Kaveh Hassani, Won-Sook Lee SIGGRAPH Asia, Autonomous Virtual Humans and Social Robot for Telepresence Workshop, 2014
	An Intelligent Architecture for Autonomous Virtual Agents Inspired by Onboard Autonomy Kaveh Hassani, Won-Sook Lee Intelligent Systems, 2014
	Optimal Tuning of Linear Quadratic Regulators using Quantum Particle Swarm Optimization Kaveh Hassani, Won-Sook Lee International Conference of Control, Dynamic Systems, and Robotics, 2014
	An Incremental Parallel Particle Swarm Approach for Classification Rule Discovery from Dynamic Data Kaveh Hassani, Won-Sook Lee International Conference on Machine Learning and Applications (ICMLA), 2013
	Design and Implementation of an Intelligent Virtual Environment for Improving Speaking and Listening Skills Kaveh Hassani, Ali Nahvi, Ali Ahmadi Interactive Learning Environments, 2013
	Architectural Design and Implementation of Intelligent Embodied Conversational Agents Using Fuzzy Knowledge Base Kaveh Hassani, Ali Nahvi, Ali Ahmadi Journal of Intelligent & Fuzzy Systems, 2013
	A Software-in-the-Loop Simulation of an Intelligent MicroSatellite within a Virtual Environment Kaveh Hassani, Won-Sook Lee IEEE International Conference on Computational Intelligence and Virtual Environments, 2013

Kaveh Hassani

About Me

Publications