Yuchi(Allan) Zhao
@allanzhao.bsky.social
CS PhD Student @ The Matter Lab UofT and Vector Institute | Robotics Researcher | UWaterloo Mechatronics Graduate
Reposted by Yuchi(Allan) Zhao
We are delighted to announce that our perspective article, “Steering towards safe self-driving laboratories (SDLs),” has been accepted for publication in Nature Reviews Chemistry.
Link: www.nature.com/articles/s41...
Link: www.nature.com/articles/s41...
August 18, 2025 at 5:46 PM
We are delighted to announce that our perspective article, “Steering towards safe self-driving laboratories (SDLs),” has been accepted for publication in Nature Reviews Chemistry.
Link: www.nature.com/articles/s41...
Link: www.nature.com/articles/s41...
Reposted by Yuchi(Allan) Zhao
Day 2 presenters:
Shi Xuan Leong
Yuchi (Allan) Zhao @allanzhao.bsky.social
Ella Ashoori
Ella Rajaonsen
Ishrath Mohamed Irshadeen
Day 3 presenters:
Alán Aspuru-Guzik @aspuru.bsky.social
Sean Park
Marcel Müller
Yunheng (Jackie) Zou
Luis Mantilla Calderón @realmantilla.bsky.social
[2/2]
Shi Xuan Leong
Yuchi (Allan) Zhao @allanzhao.bsky.social
Ella Ashoori
Ella Rajaonsen
Ishrath Mohamed Irshadeen
Day 3 presenters:
Alán Aspuru-Guzik @aspuru.bsky.social
Sean Park
Marcel Müller
Yunheng (Jackie) Zou
Luis Mantilla Calderón @realmantilla.bsky.social
[2/2]
August 8, 2025 at 6:30 PM
Day 2 presenters:
Shi Xuan Leong
Yuchi (Allan) Zhao @allanzhao.bsky.social
Ella Ashoori
Ella Rajaonsen
Ishrath Mohamed Irshadeen
Day 3 presenters:
Alán Aspuru-Guzik @aspuru.bsky.social
Sean Park
Marcel Müller
Yunheng (Jackie) Zou
Luis Mantilla Calderón @realmantilla.bsky.social
[2/2]
Shi Xuan Leong
Yuchi (Allan) Zhao @allanzhao.bsky.social
Ella Ashoori
Ella Rajaonsen
Ishrath Mohamed Irshadeen
Day 3 presenters:
Alán Aspuru-Guzik @aspuru.bsky.social
Sean Park
Marcel Müller
Yunheng (Jackie) Zou
Luis Mantilla Calderón @realmantilla.bsky.social
[2/2]
Reposted by Yuchi(Allan) Zhao
🤖 We introduce AnyPlace, a two-stage method trained entirely on synthetic data to predict a wide range of feasible placement poses for real-world scenarios. [2/5]
March 3, 2025 at 8:41 PM
🤖 We introduce AnyPlace, a two-stage method trained entirely on synthetic data to predict a wide range of feasible placement poses for real-world scenarios. [2/5]
Reposted by Yuchi(Allan) Zhao
Excited to share our latest work on leveraging quantum–classical generative models for small-molecule design, specifically targeting KRAS inhibitors for cancer therapy. [1/4]
February 27, 2025 at 10:40 PM
Excited to share our latest work on leveraging quantum–classical generative models for small-molecule design, specifically targeting KRAS inhibitors for cancer therapy. [1/4]
Reposted by Yuchi(Allan) Zhao
Excited to have #selfdrivinglaboratories listed as one of the seven technologies to watch in 2025 by @nature.com Thanks to the #matterlab, the @accelerationc.bsky.social and of course all the global community on SDLs! @uoft.bsky.social @vectorinst.bsky.social l
www.nature.com/articles/d41...
www.nature.com/articles/d41...
Self-driving laboratories, advanced immunotherapies and five more technologies to watch in 2025
Sustainability and artificial intelligence dominate our seventh annual round-up of exciting innovations.
www.nature.com
January 21, 2025 at 2:15 AM
Excited to have #selfdrivinglaboratories listed as one of the seven technologies to watch in 2025 by @nature.com Thanks to the #matterlab, the @accelerationc.bsky.social and of course all the global community on SDLs! @uoft.bsky.social @vectorinst.bsky.social l
www.nature.com/articles/d41...
www.nature.com/articles/d41...
Excited to share our latest work on object placement for robot manipulation, AnyPlace! 🚀 A two-stage method that predicts diverse placement poses for objects in the real world - trained entirely on synthetic data.
Big thanks to all my collaborators! Check out the full post for more details👇.
Big thanks to all my collaborators! Check out the full post for more details👇.
How can robots reliably place objects in diverse real-world tasks?
🤖🔍 Placement is hard! - objects vary in shape & placement modes (such as stacking, hanging, insertion)
AnyPlace predicts placement poses of unseen objects in real-world with ony using synthetic training data!
Read on👇
🤖🔍 Placement is hard! - objects vary in shape & placement modes (such as stacking, hanging, insertion)
AnyPlace predicts placement poses of unseen objects in real-world with ony using synthetic training data!
Read on👇
February 25, 2025 at 3:53 AM
Excited to share our latest work on object placement for robot manipulation, AnyPlace! 🚀 A two-stage method that predicts diverse placement poses for objects in the real world - trained entirely on synthetic data.
Big thanks to all my collaborators! Check out the full post for more details👇.
Big thanks to all my collaborators! Check out the full post for more details👇.