https://charlesxjyang.github.io/ (Charles Yang) is an EECS masters student at UC Berkeley focusing on AI and dynamical systems. He writes the excellent https://ml4sci.substack.com/ (Machine Learning For Science newsletter) where he showcases a wide range of use cases for machine learning in scientific research and engineering. Learn more about Charles: Website: https://charlesxjyang.github.io/ (https://charlesxjyang.github.io/) Google Scholar: https://scholar.google.com/citations?user=BYOREdwAAAAJ&hl=en (https://scholar.google.com/citations?user=BYOREdwAAAAJ&hl=en) ML4Sci Newsletter (Highly Recommended!): https://ml4sci.substack.com/ (https://ml4sci.substack.com/) Want to level-up your skills in machine learning and software engineering? Subscribe to our newsletter: https://mlengineered.ck.page/943aa3fd46 (https://mlengineered.ck.page/943aa3fd46)
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Timestamps: (02:08) Getting started in material science and machine learning (08:58) "ImageNet moment" for ML in science (13:20) Model explainability and transparency (17:06) Charles' Current Research (18:40) Embedding existing knowledge into ML models (22:26) "Bilingual Scientists" (24:46) Learning ML as a traditional scientist (28:22) Private vs Public ML Research (32:42) Rise of open-access research (35:22) "SOTA chasing" in ML research (38:10) Scientific ML research processes (44:34) Applying ML knowledge to a scientific problem (48:00) Biggest opportunities for ML in science (51:18) Diversity in the research community (54:24) Writing the ML4Sci newsletter (56:20) Keeping up with new research (01:05:30) Rapid Fire Questions
Links: https://ml4sci.substack.com/ (Charles' ML4Sci newsletter) https://ml4sci.substack.com/p/ml4sci-8-defining-the-new-saas-science (Charles' article on AI-powered Science as a Service) https://towardsdatascience.com/deep-learning-in-science-fd614bb3f3ce (Charles' article on Deep Learning in Science) https://ml4sci.substack.com/p/ml4sci-12-thoughts-on-covid-19-scientific (Charles' article on Scientific Gatekeeping) https://ml4sci.substack.com/p/ml4sci-15-news-from-the-world-of (Charles' article on Open Access Research) https://arxiv.org/abs/1912.12132 (Google Weather Forecasting paper) https://ai.googleblog.com/2020/03/a-neural-weather-model-for-eight-hour.html?m=1 (Google 2nd Weather Forecasting paper ) https://deepmind.com/blog/article/AlphaFold-Using-AI-for-scientific-discovery (DeepMind Protein Folding paper) https://www.biorxiv.org/content/10.1101/2020.03.07.982272v1.full.pdf (SalesForce Protein Folding paper) https://www.sciencemag.org/news/2020/02/models-galaxies-atoms-simple-ai-shortcuts-speed-simulations-billions-times (ML speeding up simulations by 9+ orders of magnitude (!)) https://www.anl.gov/ai-for-science-report (Oak Ridge AI for Science Report) https://www.nature.com/articles/s41586-019-1335-8 (Nature paper using word2vec on MatSci papers) https://arxiv.org/abs/2006.11287 (Paper using Graph NNs to find dark matter concentrations) https://www.amazon.com/Power-Broker-Robert-Moses-Fall/dp/0394720245/ (Robert Caro - The Power Broker) https://www.amazon.com/Golden-Gates-Fighting-Housing-America/dp/0525560211/ (Conor Dougherty - Golden Gates)