Chair: Dr. Luis Gerardo de la Fraga
In this session will be analyzed and proposed new hardware development to solve Machine Learning tasks. We are very interested how to optimize this new developments in the area of Data Science and AI of things (AIoT).
- Devices, circuits, and systems for Machine Learning (ML)
- Analog/digital devices, circuits, and systems for ML
- Modeling, simulation, optimization, and design automation tools for ML
- Embedded/hybrid hardware and computing for ML
- Speech/video signal processing circuits and systems for ML
- ML circuits and systems for security and cryptography applications
- ML circuits and systems for biomedical, autonomous, and human–machine systems
- Emerging applications of ML
All submission will be peer-reviewed by a panel of international experts.
Contact: Dr. Luis Gerardo de la Fraga, fraga at cs.cinvestav.mx
Dr. Luis Gerardo de la Fraga received the BS degree in electrical engineering from the Veracruz Institute of Technology, in Veracruz, Mexico in 1992; he received the MSc degree from the National Institute of Astrophysics, Optics, and Electronics (INAOE), Puebla, Mexico, in 1994; and the PhD degree from the Autonomous University of Madrid, Spain, in 1998. He develop his predoctoral work in the National Center of Biotechnology (CNB) in Madrid, Spain.
Since 2000 he is in the Computer Science Department at the Center of Research and Advanced Studies (Cinvestav), in Mexico City. He research areas include computer vision, application of evolutionary algorithms, applied mathematics, and network security. He is very enthusiastic of open software and GNU/Linux systems.
Dr. de la Fraga has published more than 35 articles in international journals, 6 book chapters, 2 books and more than 50 articles in international conferences. He had graduated 28 MSc and 4 PhD students. He is member of ACM and IEEE societies since 2005.