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Ramin Hasani

Co-founder & CEO

Ramin Hasani



Position: Co-founder & CEO at Liquid AI; Research Affiliate at CSAIL MIT

Company: Liquid AI

Current Roles:
1. Co-founder and CEO at Liquid AI: Responsible for leading the company which specializes in advanced AI technologies, particularly focusing on liquid neural networks aimed at robust decision-making algorithms in complex dynamical systems.
2. Research Affiliate at CSAIL, MIT: Engaged in cutting-edge research in artificial intelligence and machine learning, particularly on liquid neural networks.

Educational Background:
  • Ph.D. in Computer Science from Technische Universität Wien (TU Wien), Austria, completed with distinction in May 2020. Dissertation focused on Liquid Neural Networks, co-advised by Prof. Radu Grosu (TU Wien) and Prof. Daniela Rus (MIT).


Professional Experience:
  • Collaborations with MIT: Previously served as a Principal AI and Machine Learning Scientist at the Vanguard Group while holding a concurrent position as a Research Affiliate at CSAIL MIT. Formerly a Postdoctoral Associate at CSAIL MIT, conducting impactful research under Prof. Daniela Rus on modeling intelligence and sequential decision-making.

  • Recognized internationally with numerous awards, including the TÜV Austria Dissertation Award nomination in 2020, and the HPC Innovation Excellence Award in 2022.


Research Focus:
  • Development and application of liquid neural networks.

  • Emphasis on robust deep learning and decision-making algorithms in dynamic and complex systems.


Selected Publications:
1. Liquid Structural State-Space Models - Presented at the International Conference on Learning Representations (ICLR), 2023.
2. Closed-form Continuous-time Neural Networks - Accepted in Nature Machine Intelligence, 2022.
3. Causal Navigation by Continuous-time Neural Networks - Presented at the Conference on Neural Information Processing Systems (NeurIPS), 2021.
4. Liquid Time-constant Networks - Presented at the AAAI Conference on Artificial Intelligence (AAAI), 2021.
5. Neural Circuit Policies Enabling Auditable Autonomy - Published in Nature Machine Intelligence, 2020.

Recent Achievements & Activities:
  • Led the launch of Liquid Foundation Models (LFMs), introducing models of various scales including 1B, 3B, and 40B parameter versions.

  • Presented a TED Talk at TEDxMIT on liquid neural networks and their application in adaptable AI algorithms.

  • Delivered multiple invited talks including keynote addresses at MIT, Stanford University, and Vanguard’s Artificial Intelligence and Machine Learning Summit.

  • Published numerous high-impact research papers and preprints in prestigious conferences and journals such as ICML, ICLR, NeurIPS, and Nature Machine Intelligence.


Professional Interests & Contributions:
  • Ramin Hasani is highly focused on pioneering explainable AI solutions that can be leveraged in real-world applications such as autonomous driving, robotics, and medical diagnosis.

  • Regularly involved in academic and industrial discussions on the future of AI, including panels at World Economic Forum and collaborations with institutions such as MIT and Vanguard Group.


Contact Information:


  • Email: rhasani@csail.mit.edu


This summary provides a detailed and comprehensive overview of Ramin Hasani's professional background, educational qualifications, research interests, notable achievements, and current roles, making it a valuable resource for understanding his contributions to the field of AI and deep learning. The strategic insights derived from his work at Liquid AI and MIT CSAIL can significantly aid in identifying potential collaborative opportunities and understanding the scope of his influence in the AI landscape.