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In this episode, I talk with Shalini De Mello, who is a Principal Research Scientist and Research Lead at NVIDIA. Her research interests are in computer vision and machine learning for human-computer interaction and smart interfaces. At NVIDIA, she has developed technologies for gaze estimation, 2D and 3D head pose estimation, hand gesture recognition, face detection, video stabilization and GPU-optimized libraries for mobile computer vision. Her research has been focused on human-computer interaction in cars and has led to the development of NVIDIA’s innovative DriveIX product for smart AI-based automotive interfaces for future generations of cars. Shalini received her Masters and PhD in Electrical and Computer Engineering from the University of Texas at Austin. She received a Bachelor of Engineering degree in Electronics and Electrical Communication Engineering from Punjab Engineering College. In this episode, we talk about her journey - about how she got started with Computer Vision and Machine Learning, from her Bahelor's to her Master's in Biomedical Imaging to her PhD work on Human Face Recognition - about how her research interests shaped over the years. We also talk about Machine Learning inside the car, about her vision of using Machine Learning & Deep Learning for building smart assistive interfaces for inside the car, and about how that manifested into the DriveIX product that NVIDIA recently launched. Among other things, we talk about the importance of open-sourcing technology, about the future of autonomous and semi-autonomous vehicles, about the joys of learning something new everyday, about how to keep track of the ever growing amount of research and much more. It was an absolute pleasure to talk with Shalini and learn from her research insights. I hope you like the conversation. Shalini De Mello: Twitter: / shalinidemello Website: https://research.nvidia.com/person/sh... Links: NVIDIA Drive IX: https://www.nvidia.com/en-us/self-dri..., https://developer.nvidia.com/drive/dr... Self-Supervised Viewpoint Learning From Image Collections: https://research.nvidia.com/publicati... Multi-sensor System for Driver’s Hand-Gesture Recognition: https://research.nvidia.com/publicati... AI Co-Pilot: RNNs for Dynamic Facial Analysis: https://developer.nvidia.com/blog/ai-... Audio podcast links 🎧 : Spotify: https://tinyurl.com/yb6sn2rv Apple Podcasts: https://tinyurl.com/y9hu7lzq Google Podcasts: https://tinyurl.com/ybb8gxd5 Anchor.fm: https://tinyurl.com/ya98vk7b Timeline: 00:00 Introduction 02:40 Productivity during the pandemic 05:00 Virtual conferences 10:25 Getting started with CS & ML / Bachelor's 16:20 Master's in Biomedical Imaging 20:30 Machine Learning in the 2000s 23:08 PhD work in face recognition 24:57 Video stabilisation & signal processing 29:35 ML inside the car - the vision 36:05 Open sourcing technology & driving research 39:00 Drive IX nuts & bolts 42:40 Integrating subsystems 48:32 Assistive interfaces; keeping humans in the loop 53:11 Extending to a semi/fully autonomous system 1:00:05 Keeping track of research 1:06:20 Research, fascination 1:08:04 Advice for people starting out Connect with me 🙎🏻♂️: Twitter: twitter.com/mkulkhanna Instagram: instagram.com/mkulkhanna/ Deep Neural Notebooks podcast 🎙: Youtube: / @mkulkhanna Anchor: www.anchor.fm/deep-neural-notebooks Spotify: www.open.spotify.com/show/2eq1jD7V5K19aZUUJnIz5z Apple Podcasts: www.podcasts.apple.com/in/podcast/deep-neural-notebooks/id1488705711 Website: https://mukulkhanna.github.io Hashtags: #computervision #deeplearning #nvidia #humancomputerinteraction