Reconfigurable acceleration and dynamic partial self-reconfiguration in general purpose computing. - Ioannis Sourdis; Abhijit Nandy; Venkatasubramanian Viswanathan; Anthony Brandon; Dimitris Theodoropoulos; Georgi Gaydadjiev (FPT, 2011)

Dynamic reconfiguration of modular I/O IP cores for avionic applications. - Venkatasubramanian Viswanathan; Benjamin Nakache; Rabie Ben Atitallah; Maurice Nakache; Jean-Luc Dekeyser (ReConFig, 2012)

Monte Carlo-Based Approach for Simulating Nanostructured Catalytic and Electrocatalytic Systems. - Venkatasubramanian Viswanathan; Frank Wang; Heinz Pitsch (Comput. Sci. Eng., 2012)

Redefining the role of FPGAs in the next generation avionic systems (abstract only). - Venkatasubramanian Viswanathan; Rabie Ben Atitallah; Jean-Luc Dekeyser; Benjamin Nakache; Maurice Nakache (FPGA, 2014)

Communication-centric design for FMC based I/O system. - Mokhtar Bouain; Venkatasubramanian Viswanathan; Rabie Ben Atitallah; Jean-Luc Dekeyser (ReCoSoC, 2014)

Massively Parallel Dynamically Reconfigurable Multi-FPGA Computing System. - Venkatasubramanian Viswanathan; Rabie Ben Atitallah; Jean-Luc Dekeyser (FCCM, 2015)

A Parallel And Scalable Multi-FPGA based Architecture for High Performance Applications (Abstract Only). - Venkatasubramanian Viswanathan; Rabie Ben Atitallah; Jean-Luc Dekeyser; Benjamin Nakache; Maurice Nakache (FPGA, 2015)

A scalable flexible and dynamic reconfigurable architecture for high performance embedded computing. (Une architecture évolutive flexible et reconfigurable dynamiquement pour les systèmes embarqués haute performance). - Venkatasubramanian Viswanathan (2015)

Vulnerabilities of Electric Vehicle Battery Packs to Cyberattacks on Auxiliary Components. - Shashank Sripad; Sekar Kulandaivel; Vikram Pande; Vyas Sekar; Venkatasubramanian Viswanathan (CoRR, 2017)

Machine Learning Enabled Computational Screening of Inorganic Solid Electrolytes for Dendrite Suppression with Li Metal Anode. - Zeeshan Ahmad; Tian Xie; Chinmay Maheshwari; Jeffrey C. Grossman; Venkatasubramanian Viswanathan (CoRR, 2018)

Quantifying the Economic Case for Electric Semi-Trucks. - Shashank Sripad; Venkatasubramanian Viswanathan (CoRR, 2018)

FPGA-Centric Design Process for Avionic Simulation and Test. - Rabie Ben Atitallah; Venkatasubramanian Viswanathan; Nicolas Bélanger; Jean-Luc Dekeyser (IEEE Trans. Aerosp. Electron. Syst., 2018)

Automation is no barrier to light vehicle electrification. - Aniruddh Mohan; Shashank Sripad; Parth Vaishnav; Venkatasubramanian Viswanathan (CoRR, 2019)

Autonomous discovery of battery electrolytes with robotic experimentation and machine-learning. - Adarsh Dave; Jared Mitchell; Kirthevasan Kandasamy; Sven Burke; Biswajit Paria; Barnabás Póczos; Jay Whitacre; Venkatasubramanian Viswanathan (CoRR, 2020)

Universal Battery Performance and Degradation Model for Electric Aircraft. - Alexander Bills; Shashank Sripad; William L. Fredericks; Matthew Guttenberg; Devin Charles; Evan Frank; Venkatasubramanian Viswanathan (CoRR, 2020)

Closed-Loop Design of Proton Donors for Lithium-Mediated Ammonia Synthesis with Interpretable Models and Molecular Machine Learning. - Dilip Krishnamurthy; Nikifar Lazouski; Michal L. Gala; Karthish Manthiram; Venkatasubramanian Viswanathan (CoRR, 2020)

ACED: Accelerated Computational Electrochemical systems Discovery. - Rachel C. Kurchin; Eric Muckley; Lance Kavalsky; Vinay I. Hegde; Dhairya Gandhi; Xiaoyu Sun; Matthew Johnson; Alan Edelman; James E. Saal; Christopher Vincent Rackauckas; Bryce Meredig; Viral B. Shah; et al. (CoRR, 2020)

Machine learning enabled discovery of application dependent design principles for two-dimensional materials. - Victor Venturi; Holden Parks; Zeeshan Ahmad; Venkatasubramanian Viswanathan (Mach. Learn. Sci. Technol., 2020)

PDE Observer for All-Solid-State Batteries via an Electrochemical Model. - Dong Zhang 011; Shu-Xia Tang 001; Luis D. Couto; Venkatasubramanian Viswanathan (CCTA, 2021)

The promise of energy-efficient battery-powered urban aircraft. - Shashank Sripad; Venkatasubramanian Viswanathan (CoRR, 2021)

Differentiable Physics: A Position Piece. - Bharath Ramsundar; Dilip Krishnamurthy; Venkatasubramanian Viswanathan (CoRR, 2021)

Cell-Level State of Charge Estimation for Battery Packs Under Minimal Sensing. - Dong Zhang; Luis D. Couto; Ross Drummond; Shashank Sripad; Venkatasubramanian Viswanathan (CoRR, 2021)

Autonomous optimization of nonaqueous battery electrolytes via robotic experimentation and machine learning. - Adarsh Dave; Jared Mitchell; Sven Burke; Hongyi Lin; Jay Whitacre; Venkatasubramanian Viswanathan (CoRR, 2021)

A Model Predictive Control Scheme for Fast Charging via Accurate Quadratic Battery Models. - Alexander Bills; Mauro Salazar; Dong Zhang; Venkatasubramanian Viswanathan (ACC, 2022)

Score-Based Generative Models for Molecule Generation. - Dwaraknath Gnaneshwar; Bharath Ramsundar; Dhairya Gandhi; Rachel C. Kurchin; Venkatasubramanian Viswanathan (CoRR, 2022)

Super-linear Scaling Behavior for Electric Vehicle Chargers and Road Map to Addressing the Infrastructure Gap. - Alexius Wadell; Matthew Guttenberg; Christopher P. Kempes; Venkatasubramanian Viswanathan (CoRR, 2022)

Accurate Surface and Finite Temperature Bulk Properties of Lithium Metal at Large Scales using Machine Learning Interaction Potentials. - Mgcini Keith Phuthi; Archie Mingze Yao; Simon L. Batzner; Albert Musaelian; Boris Kozinsky; Ekin Dogus Cubuk; Venkatasubramanian Viswanathan (CoRR, 2023)

Chemellia: An Ecosystem for Atomistic Scientific Machine Learning. - Anant Thazhemadam; Dhairya Gandhi; Venkatasubramanian Viswanathan; Rachel C. Kurchin (CoRR, 2023)

Differentiable Turbulence. - Varun Shankar; Romit Maulik; Venkatasubramanian Viswanathan (CoRR, 2023)

Importance of equivariant and invariant symmetries for fluid flow modeling. - Varun Shankar; Shivam Barwey; Zico Kolter; Romit Maulik; Venkatasubramanian Viswanathan (CoRR, 2023)

Differentiable Turbulence II. - Varun Shankar; Romit Maulik; Venkatasubramanian Viswanathan (CoRR, 2023)

Differentiable Chemical Physics by Geometric Deep Learning for Gradient-based Property Optimization of Mixtures. - Shang Zhu; Bharath Ramsundar; Emil Annevelink; Hongyi Lin; Adarsh Dave; Pin-Wen Guan; Kevin Gering; Venkatasubramanian Viswanathan (CoRR, 2023)

Differentiable physics-enabled closure modeling for Burgers' turbulence. - Varun Shankar; Vedant Puri; Ramesh Balakrishnan; Romit Maulik; Venkatasubramanian Viswanathan (Mach. Learn. Sci. Technol., 2023)

Multiscale graph neural network autoencoders for interpretable scientific machine learning. - Shivam Barwey; Varun Shankar; Venkatasubramanian Viswanathan; Romit Maulik (J. Comput. Phys., 2023)

Self-supervised Pretraining for Partial Differential Equations. - Varun Madhavan; Amal S. Sebastian; Bharath Ramsundar; Venkatasubramanian Viswanathan (CoRR, 2024)

Smirk: An Atomically Complete Tokenizer for Molecular Foundation Models. - Alexius Wadell; Anoushka Bhutani; Venkatasubramanian Viswanathan (CoRR, 2024)

ASIMTools: A lightweight framework for scalable and reproducible atomic simulations. - Mgcini Keith Phuthi; Emil Annevelink; Venkatasubramanian Viswanathan (J. Open Source Softw., 2024)

State estimation of solid-state batteries via a distributed parameter electrochemical model. - Dong Zhang 011; Shuxia Tang 001; Luis D. Couto; Zhongbao Wei; Venkatasubramanian Viswanathan (Autom., 2025)

Learning second-order TVD flux limiters using differentiable solvers. - Chenyang Huang 006; Amal S. Sebastian; Venkatasubramanian Viswanathan (CoRR, 2025)

CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation Learning. - Changwen Xu; Shang Zhu; Venkatasubramanian Viswanathan (CoRR, 2025)

DREAMS: Density Functional Theory Based Research Engine for Agentic Materials Simulation. - Ziqi Wang; Hongshuo Huang; Hancheng Zhao; Changwen Xu; Shang Zhu; Jan Janssen; Venkatasubramanian Viswanathan (CoRR, 2025)