Nikhil V S Avula

Research Associate @jncasr | interested in the intersection of computational physical chemistry and #MachineLearning | PhD @jncasr, BTech @iitmadras

[BalasubramanianS @jncbala]

Prof. Michael Klein's (Temple U.) @ICMS_HPC lecture in the MD@60 conference, JNCASR, Bangalore, February 26-29, 2024.
"My fifty years of molecular dynamics: A personal trajectory"
https://t.co/aNxCYrxomH

[BalasubramanianS @jncbala]

Celebrating 60 years of Rahman l-argon MD paper thru JNCASR-CECAM MD@60 #MDat60 Conference.
Program, Book of Abstracts at https://t.co/83tqZyeYMg
198 Poster Presentations! 300 Participants!!
Starts Feb 26, 2024 at @jncasr
@cecamEvents
Volunteers hard at work! 👇👇

[Jean-Philip Piquemal @jppiquem]

#compchem Good read: Understanding the Anomalous Diffusion of Water in Aqueous Electrolytes Using Machine Learned Potentials https://t.co/OPClHFURDJ

[BalasubramanianS @jncbala]

Work of @avs_nikhil along with Prof. Michael Klein in JPhysChemLett.
Expt: NaCl dissolved in water slows it down, while CsI speeds it up.
Reproduced & interpreted here via MD simulations with Machine Learned Potentials trained on Condensed phase DFT data
https://t.co/UY0Czyx2iy

[Tarak Karmakar @TarakChem]

We are looking for a postdoc fellow experienced with MD simulations, multiscale modelling & machine learning (optional) methods. Good programming (C++ and Python) skill is desired. The deadline is 30th June 2023 Details https://t.co/YFaeQbxa4n RT appreciated @iitdelhi #compchem

[BioExcel CoE @BioExcelCoE]

📢Our last webinar before the summer break which features one of our core codes: "GROMACS-PMX for accurate estimation of free energy differences"

🗓️20 June 2023 at 15:00 CEST
➡️registration: https://t.co/QHEBp0pSf3

@sudarshanb259 @CompBioPhys

[Hummer Lab @HummerLab]

Common unwrapping schemes for NPT MD trajectories can mess up diffusion coefficients.
Congrats to Jakob Bullerjahn @SoBuelow @MaziarHeidari1 @jerome_henin for showing how to unwrap properly by staying off-lattice: https://t.co/A2YBObO0IQ

[George Thomas' Group @KGT_Lab]

We are excited to share our new article published in @acsnano !!!
Structurally Induced Chirality of an Achiral Chromophore on Self-Assembled Nanofibers: A Twist Makes It Chiral
https://t.co/2tHhM11t9z
Congratulations to all👏@mssanoop93 @SrinathKompella @tvmiiser @jncasr @jncbala

[Machine Learning: Science and Technology @MLSTjournal]

'Building robust #machinelearning models for small chemical science #data: the case of shear #viscosity of #fluids' by @avs_nikhil @jncbala @sudarshanb259 et al @jncasr his 1000 downloads! https://t.co/QVQEqa2pwv #compchem #fluiddynamics #moleculardynamics #AI #datascience #HPC

[BioExcel CoE @BioExcelCoE]

Please take a few minutes to fill in our @GMX_TWEET user survey 2023 and help us better understand your needs, preferences, and identify ways to improve our support.

▶️Take the survey: https://t.co/a9lWY5irNq

[Nikhil V S Avula @avs_nikhil]

@TarakChem @MolecularPhys @iitdelhi Congratulations Tarak!

[PLUMED @plumed_org]

Applications are open for the @cecamEvents PLUMED Flagship School in Lausanne, July 3-6 2023. More details about how to put an application together 👇 https://t.co/eqZhp3DnWf

[Raghunathan Ramakrishnan @raghurama123]

Excited to be back in the Madurai area after 20 years for the ML4Sciences conference! Looking forward to reliving old memories and kickstarting the program with a hackathon. #ML4Sciences #MaduraiMemories

[Martínez Group @mtzlab]

Our paper “Bringing chemical structures to life with AR, ML, and quantum chemistry” has been published in @JChemPhys. https://t.co/wHrOJn9Fjp Try our free app, now available on iOS and Android.
@sukolsak
@HayleyWeir6 @uraucci87
#chemtwitter ​​#CompChem #ChemEd
@StanfordUChem

[Louis Tiao @louistiao]

In sparse Gaussian process regression, the optimal mean and covariance of the inducing points can be exactly determined by the inducing inputs and the observations🎯

This animation shows how the inducing inputs influences the posterior👇
#MachineLearning #Stats #DataScience📈 🤖

[Ioan Magdau @MagdauIoan]

Interested in Machine Learning for Molecular Materials? Here's an exciting PhD studentship opportunity in my group at Newcastle University!

[Steven Strogatz @stevenstrogatz]

The second season of THE JOY OF WHY, a podcast I'm hosting for @QuantaMagazine, starts tomorrow! You can catch up on season 1 at the link below, or wherever you get your podcasts. https://t.co/w50uRY9scu

[Digital Discovery @digital_rsc]

Today's featured article from White, Hocky et al. asks whether large language models like GPT (including #ChatGPT) know chemistry, and explores their capabilities and implications in this field. Read the full article here: https://t.co/28Sehtvrhy #openaccess

[Tyler Morgan-Wall @tylermorganwall]

Simulated Annealing: a stochastic optimization method inspired by nature. As "temperature" decreases, random fluctuations (that allow it to escape local minima/maxima) decrease and the particle resorts to hillclimbing. No gradient calculation required.

#RStats #rayshader

[Berend Smit @SmitBerend]

The most controversial article I have ever written! @kmjablonka shows that making a #MachineLearning model for different problems in #Chemistry with #GPT3 is as easy as a literature search. The scary part; it outperforms all the conventional ML models https://t.co/1WfdfYk5v1 1/4