Happy to share our paper published on JCTC. Transfer learning Facilitates the Prediction of Polymer-Surface Adhesion Strength. Thanks my Ph.D. advisor Jonathan K. Whitmer Notre Dame CBE Thanks our collaborators Yamil J. Colón Rodríguez Samanvaya Srivastava Fahed Albreiki #MachineLearning

Honored to be selected as a 2023 PMSE Future Faculty Awardee! ACS PMSE Division Thanks Prof. Olsen Olsen Lab @ MIT MIT ChemE Dept for the nomination and mentorship. Thanks my co-advisor Dr. Audus National Institute of Standards and Technology for mentorship! Also, thanks my Ph.D. advisor Jonathan K. Whitmer Notre Dame CBE for academic training.

Congratulations Notre Dame CBE. I see so many familiar faces in this photo. It is so excited to see your great success.

I am delighted to announce that I will be starting my independent career as an Assistant Professor at UMass Amherst in the Department of Polymer Science and Engineering (Polymer Science & Engineering Dept @ UMass Amherst) this fall. The Morris group will engineer sustainable macromolecules using accessible automation.

I found that many other GPT relevant papers claim that they test on database built after Sept 2021. However, Database built after Sept 2021 does not mean the data in that Database has not been touched by OpenAI. The data could exist much earlier than the database. #OpenAI #GPT4

Check out this JCTC special issue on Machine Learning for Molecular Simulation containing our work "Transfer Learning Facilitates the Prediction of Polymer–Surface Adhesion Strength" pubs.acs.org/doi/10.1021/ac…

It is a great journey to attend the ACS P2F workshop ACS Grads & Postdocs and meet so many talented peers. Thank my mentor Prof. Melanie Chiu Chiucrew, for advice on the faculty application. Thanks to the workshop organizers, especially Milcah Milcah Jackson, PhD.

Excited to share my postdoc work with Olsen Lab @ MIT MIT ChemE Dept and Debra Audus National Institute of Standards and Technology on “Earth mover’s distance as a metric for calculating pairwise similarity of polymer ensembles” ACS PMSE Division #FutureFaculty #ACSFall2023 Sunday 9:25 am, Nob Hill D - Marriott Marquis

Welcome to stop by the CRIPT exhibit booth at 242 #ACSFall2023 Olsen Lab @ MIT MIT ChemE Dept Massachusetts Institute of Technology (MIT) #polymer #BigData #chemistry

I will give my second talk at #ACSFall2023 about one of my postdoc works, "Quantifying pairwise chemical similarity of polymers," in the Big Data in Polymer Chemistry session. Olsen Lab @ MIT MIT ChemE Dept ACS PMSE Division ACS POLY Division #BigData Time: 3:15 PM Aug 15 Location: Salon 5, Marriott

Proud to be one of the PMSE 2023 Future Faculty Award Winners. Thanks for the opportunities to present our work Olsen Lab @ MIT and meet so many talented peers. ACS PMSE Division ACS POLY Division #ACSFall2023 I will be on the faculty job market this year.

It was really wonderful to attend the ACS P2F workshop. Thanks for the support from ACS Grads & Postdocs Happy NPAW2023 #identity #NPAW2023 #postdocs

I am happy to share this preprint work. doi.org/10.26434/chemr… We use EMD to compute polymer ensemble similarity from single polymer chain similarity, successfully linking ensembles and single chains. MIT ChemE Dept National Institute of Standards and Technology Code: github.com/olsenlabmit/Po…

I'm on the faculty job market! My research integrates simulation, machine learning and large language models for soft matter optimal design, especially in three areas: surface, responsiveness, and LLM agent. Welcome to my poster, #58 #AIChEAnnual #AICHE #AIChE2023 American Institute of Chemical Engineers (AIChE)

Molar mass distributions (Mn, dispersity, As, α3, and α4,) can largely affect the properties of polymers. In this paper, we use EMD to quantify the similarity between different experimental MMDs and enable similarity search on MMDs. #polymer #BigData #AI #MachineLearning

Knowledge Graph RAG for Polymer Simulation---Team Project in 2024 LLM Hackathon for Applications in Materials and Chemistry. youtu.be/VXMX4sJVxdE