Dhiman Ray
@DhimanRay16
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Assistant Prof @uoCHandBIC, PostDoc @GroupParrinello @IITalk Genoa, PhD @UCIChemistry, BS-MS @iiserkol, Computational Biophysics (ML and MD Simulation)
Eugene, OR
Joined September 2019
I am thrilled to announce that I have accepted a tenure-track assistant professor position at the Department of Chemistry and Biochemistry, University of Oregon, USA (@uoCHandBIC), starting in Fall 2024, in the beautiful city of Eugene in the Pacific Northwest. #compchem (1)
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The first @PNASNews from the Ray group @uoCHandBIC! We show how multitask deep learning can be integrated with enhanced sampling simulations to identify mechanisms without a free energy surface. Kudos @Revanth_Elango and @SompriyaC for making this possible! #AIML #Compchem
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Introducing CECAM-US-WEST, a new CECAM node located at UC Berkeley. Programing starting next calendar year! @UCB_Chemistry @cecamEvents
https://t.co/KzfbnMsRjK
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Characterizing RNA Tetramer Conformational Landscape Using Explainable Machine Learning #machinelearning #compchem
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For any who are interested in working on machine-learning driven simulations of battery electrolyes using path-integral techniques, I am opening a new postdoctoral position in my group. The Interfolio application site is here:
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Want to run and analyze MD simulations of a disordered protein? Check out our step-by-step practical guide (+ tutorial with code) for preparing, running and analyzing replica exchange solute tempering (REST2) simulations of IDPs with @GMX_TWEET and @plumed_org on arxiv!
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This work with former grad student Jack Hanni is now out in @JChemPhys Michele Parrinello Festschrift special issue https://t.co/BwK2TJFq9G as a tribute to my PostDoc advisor @GroupParrinello! #compchem @uoCHandBIC
New preprint from my group at @uoCHandBIC: "Data-Efficient Learning of Molecular Slow Modes from Nonequilibrium Metadynamics". We use short biased trajectories to learn ideal CVs for enhanced sampling simulations using Koopman reweighting and Deep-TICA: https://t.co/m3KDa5nJXT
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We hosted Prof. @OmarValsson this week for our PChem Seminar @uoCHandBIC . It was great listening to his work on enhanced sampling simulation and we very much enjoyed our discussion about science and academic life!
TODAY! Physical Chemistry Seminar - Professor Omar Valsson, University of North Texas - April 14th @ 2pm in Tykeson 140 https://t.co/LwvRgtFpnV
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Upcoming Physical Chemistry Seminar - Professor Gül Zerze, University of Houston - April 21st @ 2pm, Tykeson 140 https://t.co/4yF4NFYnaY
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Please RT. Thanks
We are organizing a 2-day "AI in Biophysics" symposium from 28-29 April. We bring together leading experts to facilitate interdisciplinary and lively discussions. Website: https://t.co/o5TMSAq9HQ Poster abstract deadline: April 18 Registration deadline: April 24
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Upcoming Physical Chemistry Seminar - Professor Omar Valsson, University of North Texas - April 14th @ 2pm in Tykeson 140 https://t.co/LwvRgtFXdt
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#compchem In the Big Data era, a change of paradigm in the use of molecular dynamics is required. Trajectories should be stored under FAIR (findable, accessible, interoperable and reusable) requirements to favor its reuse by the community under an open science paradigm. Happy to
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Come to the wonderful symposium @GiEmmePi1 and I organized at the @AmerChemSociety meeting in SD. phenomenal lineup: @CHHDellago @kamerlinlab @LuigiBonati @DhimanRay16 @matteoslvlgl @SossoGroup @GroupTuckerman @limmerlab @ChengBingqing @thesiminegroup @PodewitzLab and others!
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Many thanks to Barak Hirshberg and @GiEmmePi1 for the kind invitation!
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Attending the ACS Spring Meeting next week in San Diego? Check out the two talks from Ray group @uoCHandBIC by me and my postdoc @SompriyaC at the symposium on Inferring Kinetics, Thermodynamics, and Mechanisms From Enhanced Sampling Simulations. #ACSSpring2025
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🚀 New preprint alert! 🚀 Introducing Loxodynamics, a simple yet powerful deep learning method for exploring chemistry and catalysis by biasing skewed distributions. Check it out! 🔬⚡ #MachineLearning #Catalysis #Chemistry
https://t.co/RPzJFvH2J5
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This work is now out at @JCIM_JCTC! The first paper from the Ray group at @uoCHandBIC. Many congratulations to @SompriyaC for the hard work and determination!
First preprint from my research group @uoCHandBIC: My postdoc Sompriya demonstrates the use of explainable representations of neural network CVs made using lasso regression surrogate models to perform enhanced sampling, https://t.co/YSueTlRaNZ
#compchem
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Proud to share a new manuscript: "Ensemble docking for intrinsically disordered proteins" from @DartmouthChem undergrad Anjali Dhar 24' and grad student Tommy Sisk. We present ensemble docking strategies for IDPs that, remarkably, seem to work! (Links in thread below)
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Some #FEP history. I presented our ethane to methanol calculations at an NSF workshop in Spring 1985 that was attended by Martin Karplus and stat mech folks. Here is a subsequent letter from him and the first page of the draft of JCP 1985, 83, 3050. I sent him the preprint.
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Our group’s 1st preprint in 2025: a tensor-based approach for CV identification, led by @SiqinCao in collaboration with @MichelineSoley and Feliks Nüske from MPI Magdeburg. Thanks to all co-authors! @BojunLiu0818 @TCI_UW_Madison
Our preprint of AMUSET-TICA is out now. It identifies CVs for biomolecular dynamics with a tensor based approach. The quality of CVs is comparable to deep learning methods. AMUSET-TICA is also fast and numerically stable due to its deterministic algorithm.
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