Chemistry PhD Student - University of Toronto (Aspuru-Guzik Group & Team Tran) | ex-ML Intern @KebotixInc | Views my own

Toronto, Ontario
Joined November 2020
Stanley Lo retweeted
New research: The AI Fluency Index. We tracked 11 behaviors across thousands of Claude.ai conversations—for example, how often people iterate and refine their work with Claude—to measure how well people collaborate with AI. Read more: anthropic.com/research/AI-fl…
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The "AI + Robotics" field has exploded in recent years. To stay on top of what's happening, we've put together a comprehensive review: "Self-Driving Labs for Chemistry and Materials Science", with @M_Seifrid & @A_Aspuru_Guzik – now out in @ACSChemRev! pubs.acs.org/doi/10.1021/acs…
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It's finally out thanks to @mistergtom and the team's dedication! Check out our behemoth of a review about #SelfDrivingLabs
Our review on all things self-driving labs for chem 🧪 and mat sci now at 🏡on @ACSChemRev. Check it out doi.org/10.1021/acs.chemrev.… (free and open-access!🌟) A huge effort led by myself @felix_s_k @M_Seifrid @A_Aspuru_Guzik, ft. @Stefan_P_Schmid and many more 👇
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Stanley Lo retweeted
Our review on all things self-driving labs for chem 🧪 and mat sci now at 🏡on @ACSChemRev. Check it out doi.org/10.1021/acs.chemrev.… (free and open-access!🌟) A huge effort led by myself @felix_s_k @M_Seifrid @A_Aspuru_Guzik, ft. @Stefan_P_Schmid and many more 👇
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Our exploration of machine learning to predict #OPV device performance from molecular structure of the materials *and* processing data is now officially published in @JMaterChem A as part of their 2024 Emerging Investigators series! doi.org/10.1039/D4TA01942C
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It’s finally out, my last piece of undergraduate work! DOI: doi.org/10.1039/D4TA01942C Really glad to have been a part of this project! Learned so much from @M_Seifrid who has been a great mentor to me. Shoutout to Dylan Choi, the group at @QuyenUCSB, and @A_Aspuru_Guzik !
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It was my first ever experience with Machine Learning for Chemistry and I’ve learned a lot of what it takes to be a proficient coder and scientist!
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Can’t wait to take what I’ve learned here and apply it to my future projects 🤩
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Out now @ChemRxiv! We explored using machine learning to predict #OPV device performance from molecular structure of the materials *and* processing data. Hopefully this somewhat didactic approach is useful to those in the field who are interested in ML. doi.org/10.26434/chemrxiv-20…
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Checkout my latest article on the Review of Low-cost Self-driving Laboratories: The “Frugal Twin” Concept (doi.org/10.26434/chemrxiv-20…) It was great working with @SterlingBaird1 where we sparked a lot of fascinating discussion! Big thanks to all of our co-authors as well!
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We found that by adding modularity, and hardware-centric design it can help lower the costs of these systems.
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Excited to see what other people think of our review! Whether it is researchers, citizen scientists, or students, I hope that this article will help propel people forward into developing their own SDLs!!!
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Canada’s federal graduate scholarships and postdoctoral fellowships are not competitive! 😞 For ex, the NSF postdoctoral fellowship is valued at $106,000 CAD 🇺🇸, compared to the $45,000 🇨🇦 offered by the Tri-Agency fellowships 😱🤕 #scholarships #graduate
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This is truly bleeding edge research! It has been a pleasure to see the amazing resilience from the MADNESS team. I’m really proud of the team and my mentors @M_Seifrid @felix_s_k 🥳🥳 If anyone wants inspiration for figures, take it from this guy @felix_s_k
I'm thrilled to share that the big project from my postdoc is now available on @ChemRxiv! doi.org/10.26434/chemrxiv-20… A delocalized self-driving lab for organic materials discovery, featuring ML experiment planning, robotic synthesis, and automated testing across multiple sites. 🧵
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#ICYMI – our 2023 research #grants are now live, with a short EOI due July 31. Funding is open to #UofT faculty or #UofT hospital partners, collaborators can be from universities across Canada. See full guidelines: acceleration.utoronto.ca/pro…
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I’m usually not good at celebrating my wins, but I’m really proud of myself for publishing my first first-author paper! If you’re working in #ML4Science or #polymerinformatics, please check it out! Augmenting Polymer Datasets by Iterative Rearrangement pubs.acs.org/doi/abs/10.1021…
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