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Isaac Parker Siyu Tian
Researcher at Singapore–MIT alliance
Publications - 3
Citations - 118
Isaac Parker Siyu Tian is an academic researcher from Singapore–MIT alliance. The author has contributed to research in topics: Bayesian optimization & Artificial neural network. The author has an hindex of 3, co-authored 3 publications receiving 21 citations.
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Journal ArticleDOI
Two-step machine learning enables optimized nanoparticle synthesis
Flore Mekki-Berrada,Zekun Ren,Tan Huang,Wai Kuan Wong,Fang Zheng,Jiaxun Xie,Isaac Parker Siyu Tian,Senthilnath Jayavelu,Zackaria Mahfoud,Daniil Bash,Kedar Hippalgaonkar,Saif A. Khan,Tonio Buonassisi,Qianxiao Li,Qianxiao Li,Xiaonan Wang +15 more
TL;DR: In this paper, a Gaussian process-based Bayesian optimization (BO) with a deep neural network (DNN) is combined with a microfluidic platform to produce silver nanoparticles with the desired absorbance spectrum.
Posted ContentDOI
Two-Step Machine Learning Enables Optimized Nanoparticle Synthesis
Flore Mekki-Berrada,Zekun Ren,Tan Huang,Wai Kuan Wong,Fang Zheng,Jiaxun Xie,Isaac Parker Siyu Tian,Senthilnath Jayavelu,Zackaria Mahfoud,Daniil Bash,Kedar Hippalgaonkar,Saif A. Khan,Tonio Buonassisi,Qianxiao Li,Qianxiao Li,Xiaonan Wang +15 more
TL;DR: This study presents a two-step framework for a machine learning driven high-throughput microfluidic platform to rapidly produce silver nanoparticles with a desired absorbance spectrum by combining a Gaussian Process based Bayesian Optimization with a Deep Neural Network.
Posted ContentDOI
Machine Learning and High-Throughput Robust Design of P3HT-CNT Composite Thin Films for High Electrical Conductivity
Daniil Bash,Yongqiang Cai,Chellappan Vijila,Swee Liang Wong,Yang Xu,Pawan Kumar,Jin Da Tan,Anas Abutaha,Jayce Jian Wei Cheng,Yee-Fun Lim,Isaac Parker Siyu Tian,Zekun Ren,Wai Kuan Wong,Flore Mekki-Berrada,Jatin N. Kumar,Saif A. Khan,Qianxiao Li,Tonio Buonassisi,Kedar Hippalgaonkar +18 more
TL;DR: In this article, an automated flow system with high-throughput drop-casting for thin film preparation is introduced, followed by fast characterization of optical and electrical properties, with the capability to complete one cycle of learning of fully labeled ~160 samples in a single day.