Alishba Imran is a deep learning researcher at UC Berkeley's BAIR AI Lab, a Research Fellow at the Arc Institute, a former Research Intern at the Chan Zuckerberg Biohub, co-founder of battery tech startup Voltx, and co-author of "AI for Robotics: Toward Embodied and General Intelligence in the Physical World"
See below for episode links, chapters, and our socials. Hosted by Nabil Laoudji.
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Episode Links:
- Alishba's LinkedIn
- Alishba's Twitter
- "AI for Robotics" book
- Arc Institute
- UC Berkeley BAIR AI Lab
- Chan Zuckerberg Biohub
- DynaCLR Paper
- Biopunk Lab
Chapters:
- (00:00) - Preview & Introduction
- (05:02) - Why AI for Science?
- (10:34) - Bootstrapping Your Own Learning
- (16:02) - Why Battery Testing Matters: Launching Voltx
- (20:19) - Batteries, Raw Earth Minerals: Incremental vs Transformative Chemistries
- (23:54) - The Business Side of Deep Tech Entrepreneurship
- (29:14) - The State of Battery Tech Today
- (30:50) - Working with Chan Zuckerberg Biohub
- (33:37) - DynaCLR For Contrastive Learning of Cell State Dynamics
- (36:21) - Why Self-Supervised + Contrastive Learning
- (41:06) - Generalizing to Different Cells Contexts With Embeddings
- (42:06) - Microscopy or ML Advancements for Unlocking Progress
- (43:54) - Managing Terabytes of Data
- (46:51) - Arc Institute: Collecting Largest Single Cell Dataset
- (48:40) - Role of Tech-Founder Funded Institute To Advance Foundational Work
- (50:41) - Book Launch! Merging Classical Robotics Methods With Cutting-Edge Deep Learning
- (53:42) - Robotics Progress: Hype vs Reality
- (57:09) - Robotics for Science
- (58:54) - Future Trends: Automation, Foundational Single Cell Models, Protein and Genome Language Models, Transcriptomics
- (01:00:41) - Pivoting into AI for Science Early, Mid, or Late Career
- (01:02:49) - Exchanging Ideas; DynaCLR Paper; AI for Robotics Book
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