Deep Learning the Physics of Transport Phenomena. - Amir Barati Farimani; Joseph Gomes; Vijay S. Pande (CoRR, 2017)

Deep Learning Phase Segregation. - Amir Barati Farimani; Joseph Gomes; Rishi Sharma 005; Franklin L. Lee; Vijay S. Pande (CoRR, 2018)

Weakly-Supervised Deep Learning of Heat Transport via Physics Informed Loss. - Rishi Sharma 005; Amir Barati Farimani; Joe Gomes; Peter K. Eastman; Vijay S. Pande (CoRR, 2018)

Bio-inspired Stochastic Growth and Initialization for Artificial Neural Networks. - Kevin Dai; Amir Barati Farimani; Victoria A. Webster-Wood (Living Machines, 2019)

Creativity in Robot Manipulation with Deep Reinforcement Learning. - Juan Carlos Vargas; Malhar Bhoite; Amir Barati Farimani (CoRR, 2019)

Effects of sparse rewards of different magnitudes in the speed of learning of model-based actor critic methods. - Juan Carlos Vargas; Lazar Andjelic; Amir Barati Farimani (CoRR, 2020)

Potential Neutralizing Antibodies Discovered for Novel Corona Virus Using Machine Learning. - Rishikesh Magar; Prakarsh Yadav; Amir Barati Farimani (CoRR, 2020)

Deep Learning Convective Flow Using Conditional Generative Adversarial Networks. - Changlin Jiang; Amir Barati Farimani (CoRR, 2020)

StressGAN: A Generative Deep Learning Model for 2D Stress Distribution Prediction. - Haoliang Jiang; Zhenguo Nie; Roselyn Yeo; Amir Barati Farimani; Levent Burak Kara (CoRR, 2020)

Orbital Graph Convolutional Neural Network for Material Property Prediction. - Mohammadreza Karamad; Rishikesh Magar; Yuting Shi; Samira Siahrostami; Ian Donald Gates; Amir Barati Farimani (CoRR, 2020)

Data-driven Identification of 2D Partial Differential Equations using extracted physical features. - Kazem Meidani; Amir Barati Farimani (CoRR, 2020)

Deep Learning for Efficient Reconstruction of High-Resolution Turbulent DNS Data. - Pranshu Pant; Amir Barati Farimani (CoRR, 2020)

Graph Convolutional Neural Networks for Body Force Prediction. - Francis Ogoke; Kazem Meidani; Amirreza Hashemi; Amir Barati Farimani (CoRR, 2020)

FaultNet: A Deep Convolutional Neural Network for Bearing Fault Classification. - Rishikesh Magar; Lalit Ghule; Junhan Li; Yang Zhao; Amir Barati Farimani (IEEE Access, 2021)

Understanding mutation hotspots for the SARS-CoV-2 spike protein using Shannon Entropy and K-means clustering. - Baishali Mullick; Rishikesh Magar; Aastha Jhunjhunwala; Amir Barati Farimani (Comput. Biol. Medicine, 2021)

Airfoil GAN: Encoding and Synthesizing Airfoils forAerodynamic-aware Shape Optimization. - Yuyang Wang 005; Kenji Shimada; Amir Barati Farimani (CoRR, 2021)

Deep Reinforcement Learning Optimizes Graphene Nanopores for Efficient Desalination. - Yuyang Wang 005; Zhonglin Cao; Amir Barati Farimani (CoRR, 2021)

Thermal Control of Laser Powder Bed Fusion Using Deep Reinforcement Learning. - Francis Ogoke; Amir Barati Farimani (CoRR, 2021)

MolCLR: Molecular Contrastive Learning of Representations via Graph Neural Networks. - Yuyang Wang 005; Jianren Wang; Zhonglin Cao; Amir Barati Farimani (CoRR, 2021)

An Energy-Saving Snake Locomotion Gait Policy Using Deep Reinforcement Learning. - Yilang Liu 002; Amir Barati Farimani (CoRR, 2021)

Deep learning of material transport in complex neurite networks. - Angran Li; Amir Barati Farimani; Yongjie Jessica Zhang (CoRR, 2021)

Deep Learning for Reduced Order Modelling and Efficient Temporal Evolution of Fluid Simulations. - Pranshu Pant; Ruchit Doshi; Pranav Bahl; Amir Barati Farimani (CoRR, 2021)

AugLiChem: Data Augmentation Library ofChemical Structures for Machine Learning. - Rishikesh Magar; Yuyang Wang 005; Cooper Lorsung; Chen Liang; Hariharan Ramasubramanian; Peiyuan Li; Amir Barati Farimani (CoRR, 2021)

Graph Neural Networks Accelerated Molecular Dynamics. - Zijie Li; Kazem Meidani; Prakarsh Yadav; Amir Barati Farimani (CoRR, 2021)

Graph convolutional networks applied to unstructured flow field data. - Francis Ogoke; Kazem Meidani; Amirreza Hashemi; Amir Barati Farimani (Mach. Learn. Sci. Technol., 2021)

Deep reinforcement learning for predicting kinetic pathways to surface reconstruction in a ternary alloy. - Junwoong Yoon; Zhonglin Cao; Rajesh K. Raju; Yuyang Wang 005; Robert Burnley; Andrew J. Gellman; Amir Barati Farimani; Zachary W. Ulissi (Mach. Learn. Sci. Technol., 2021)

Isolating Specific vs. Non-Specific Binding Responses in Conducting Polymer Biosensors for Bio-Fingerprinting. - Phil M. Smith; Indorica Sutradhar; Maxwell Telmer; Rishikesh Magar; Amir Barati Farimani; B. Reeja-Jayan (Sensors, 2021)

TPU-GAN: Learning temporal coherence from dynamic point cloud sequences. - Zijie Li; Tianqin Li; Amir Barati Farimani (ICLR, 2022)

Prototype memory and attention mechanisms for few shot image generation. - Tianqin Li; Zijie Li; Andrew Luo; Harold Rockwell; Amir Barati Farimani; Tai Sing Lee (ICLR, 2022)

VecMetaPy: A vectorized framework for metaheuristic optimization in Python. - AmirPouya Hemmasian; Kazem Meidani; Seyedali Mirjalili; Amir Barati Farimani (Adv. Eng. Softw., 2022)

MAB-OS: Multi-Armed Bandits Metaheuristic Optimizer Selection. - Kazem Meidani; Seyedali Mirjalili; Amir Barati Farimani (Appl. Soft Comput., 2022)

Forecasting COVID-19 new cases using deep learning methods. - Lu Xu; Rishikesh Magar; Amir Barati Farimani (Comput. Biol. Medicine, 2022)

Graph neural network-accelerated Lagrangian fluid simulation. - Zijie Li; Amir Barati Farimani (Comput. Graph., 2022)

MeltpoolNet: Melt pool Characteristic Prediction in Metal Additive Manufacturing Using Machine Learning. - Parand Akbari; Francis Ogoke; Ning-Yu Kao; Kazem Meidani; Chun-Yu Yeh; William Lee; Amir Barati Farimani (CoRR, 2022)

Crystal Twins: Self-supervised Learning for Crystalline Material Property Prediction. - Rishikesh Magar; Yuyang Wang 005; Amir Barati Farimani (CoRR, 2022)

Deep-Learned Generators of Porosity Distributions Produced During Metal Additive Manufacturing. - Francis Ogoke; Kyle Johnson; Michael Glinsky; Chris Laursen; Sharlotte Kramer; Amir Barati Farimani (CoRR, 2022)

Surrogate Modeling of Melt Pool Thermal Field using Deep Learning. - AmirPouya Hemmasian; Francis Ogoke; Parand Akbari; Jonathan Malen; Jack L. Beuth; Amir Barati Farimani (CoRR, 2022)

TransPolymer: a Transformer-based Language Model for Polymer Property Predictions. - Changwen Xu; Yuyang Wang 005; Amir Barati Farimani (CoRR, 2022)

Graph Neural Networks for Molecules. - Yuyang Wang 005; Zijie Li; Amir Barati Farimani (CoRR, 2022)

MAN: Multi-Action Networks Learning. - Keqin Wang; Alison Bartsch; Amir Barati Farimani (CoRR, 2022)

Mechanical Properties Prediction in Metal Additive Manufacturing Using Machine Learning. - Parand Akbari; Ning-Yu Kao; Amir Barati Farimani (CoRR, 2022)

Predicting CO2 Absorption in Ionic Liquids with Molecular Descriptors and Explainable Graph Neural Networks. - Yue Jian; Yuyang Wang 005; Amir Barati Farimani (CoRR, 2022)

MOFormer: Self-Supervised Transformer model for Metal-Organic Framework Property Prediction. - Zhonglin Cao; Rishikesh Magar; Yuyang Wang 005; Amir Barati Farimani (CoRR, 2022)

MeshDQN: A Deep Reinforcement Learning Framework for Improving Meshes in Computational Fluid Dynamics. - Cooper Lorsung; Amir Barati Farimani (CoRR, 2022)

Online metaheuristic algorithm selection. - Kazem Meidani; Seyedali Mirjalili; Amir Barati Farimani (Expert Syst. Appl., 2022)

Improving Molecular Contrastive Learning via Faulty Negative Mitigation and Decomposed Fragment Contrast. - Yuyang Wang 005; Rishikesh Magar; Chen Liang; Amir Barati Farimani (J. Chem. Inf. Model., 2022)

Molecular contrastive learning of representations via graph neural networks. - Yuyang Wang 005; Jianren Wang; Zhonglin Cao; Amir Barati Farimani (Nat. Mach. Intell., 2022)

Dominant motion identification of multi-particle system using deep learning from video. - Yayati Jadhav; Amir Barati Farimani (Neural Comput. Appl., 2022)

Adaptive grey wolf optimizer. - Kazem Meidani; AmirPouya Hemmasian; Seyedali Mirjalili; Amir Barati Farimani (Neural Comput. Appl., 2022)

AugLiChem: data augmentation library of chemical structures for machine learning. - Rishikesh Magar; Yuyang Wang 005; Cooper Lorsung; Chen Liang; Hariharan Ramasubramanian; Peiyuan Li; Amir Barati Farimani (Mach. Learn. Sci. Technol., 2022)

Minimizing Human Assistance: Augmenting a Single Demonstration for Deep Reinforcement Learning. - Abraham George; Alison Bartsch; Amir Barati Farimani (ICRA, 2023)

Inverse Lighting with Differentiable Physically-Based Model. - Kazem Meidani; Igor Borovikov; Amir Barati Farimani; Harold Chaput (LION, 2023)

Scalable Transformer for PDE Surrogate Modeling. - Zijie Li; Dule Shu; Amir Barati Farimani (NeurIPS, 2023)

Transformer-based Planning for Symbolic Regression. - Parshin Shojaee; Kazem Meidani; Amir Barati Farimani; Chandan K. Reddy (NeurIPS, 2023)

Denoise Pre-training on Non-equilibrium Molecules for Accurate and Transferable Neural Potentials. - Yuyang Wang 005; Changwen Xu; Zijie Li; Amir Barati Farimani (CoRR, 2023)

Neural Network Predicts Ion Concentration Profiles under Nanoconfinement. - Zhonglin Cao; Yuyang Wang 005; Cooper Lorsung; Amir Barati Farimani (CoRR, 2023)

Physics Informed Token Transformer. - Cooper Lorsung; Zijie Li; Amir Barati Farimani (CoRR, 2023)

HNO: Hyena Neural Operator for solving PDEs. - Saurabh Patil; Zijie Li; Amir Barati Farimani (CoRR, 2023)

RoboChop: Autonomous Framework for Fruit and Vegetable Chopping Leveraging Foundational Models. - Atharva Dikshit; Alison Bartsch; Abraham George; Amir Barati Farimani (CoRR, 2023)

Fluid Property Prediction Leveraging AI and Robotics. - Jong Hoon Park; Gauri Pramod Dalwankar; Alison Bartsch; Abraham George; Amir Barati Farimani (CoRR, 2023)

Materials Informatics Transformer: A Language Model for Interpretable Materials Properties Prediction. - Hongshuo Huang; Rishikesh Magar; Changwen Xu; Amir Barati Farimani (CoRR, 2023)

Catalyst Property Prediction with CatBERTa: Unveiling Feature Exploration Strategies through Large Language Models. - Janghoon Ock; Chakradhar Guntuboina; Amir Barati Farimani (CoRR, 2023)

PeptideBERT: A Language Model based on Transformers for Peptide Property Prediction. - Chakradhar Guntuboina; Adrita Das; Parisa Mollaei; Seongwon Kim; Amir Barati Farimani (CoRR, 2023)

Pour me a drink: Robotic Precision Pouring Carbonated Beverages into Transparent Containers. - Feiya Zhu; Shuo Hu; Letian Leng; Alison Bartsch; Abraham George; Amir Barati Farimani (CoRR, 2023)

One ACT Play: Single Demonstration Behavior Cloning with Action Chunking Transformers. - Abraham George; Amir Barati Farimani (CoRR, 2023)

GPT-MolBERTa: GPT Molecular Features Language Model for molecular property prediction. - Suryanarayanan Balaji; Rishikesh Magar; Yayati Jadhav; Amir Barati Farimani (CoRR, 2023)

Multi-scale Time-stepping of Partial Differential Equations with Transformers. - AmirPouya Hemmasian; Amir Barati Farimani (CoRR, 2023)

Inexpensive High Fidelity Melt Pool Models in Additive Manufacturing Using Generative Deep Diffusion. - Francis Ogoke; Quanliang Liu; Olabode Ajenifujah; Alexander Myers; Guadalupe Quirarte; Jack L. Beuth; Jonathan Malen; Amir Barati Farimani (CoRR, 2023)

Transformer for Partial Differential Equations' Operator Learning. - Zijie Li; Kazem Meidani; Amir Barati Farimani (Trans. Mach. Learn. Res., 2023)

Activity Map and Transition Pathways of G Protein-Coupled Receptor Revealed by Machine Learning. - Parisa Mollaei; Amir Barati Farimani (J. Chem. Inf. Model., 2023)

A physics-informed diffusion model for high-fidelity flow field reconstruction. - Dule Shu; Zijie Li; Amir Barati Farimani (J. Comput. Phys., 2023)

Identification of parametric dynamical systems using integer programming. - Kazem Meidani; Amir Barati Farimani (Expert Syst. Appl., 2023)

Airfoil GAN: encoding and synthesizing airfoils for aerodynamic shape optimization. - Yuyang Wang 005; Kenji Shimada; Amir Barati Farimani (J. Comput. Des. Eng., 2023)

ManufacturingNet: A machine learning toolbox for engineers. - Akshay Antony; Chakradhar Guntuboina; Rishikesh Magar; Lalit Ghule; Ruchit Doshi; Aman Khalid; Sharan Seshadri; Amir Barati Farimani (SoftwareX, 2023)

SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training. - Kazem Meidani; Parshin Shojaee; Chandan K. Reddy; Amir Barati Farimani (ICLR, 2024)

SculptBot: Pre-Trained Models for 3D Deformable Object Manipulation. - Alison Bartsch; Charlotte Avra; Amir Barati Farimani (ICRA, 2024)

SculptDiff: Learning Robotic Clay Sculpting from Humans with Goal Conditioned Diffusion Policy. - Alison Bartsch; Arvind Car; Charlotte Avra; Amir Barati Farimani (IROS, 2024)

FaultFormer: Pretraining Transformers for Adaptable Bearing Fault Classification. - Anthony Y. Zhou; Amir Barati Farimani (IEEE Access, 2024)

Multimodal Language and Graph Learning of Adsorption Configuration in Catalysis. - Janghoon Ock; Rishikesh Magar; Akshay Antony; Amir Barati Farimani (CoRR, 2024)

PICL: Physics Informed Contrastive Learning for Partial Differential Equations. - Cooper Lorsung; Amir Barati Farimani (CoRR, 2024)

Pretraining Strategy for Neural Potentials. - Zehua Zhang; Zijie Li; Amir Barati Farimani (CoRR, 2024)

Inpainting Computational Fluid Dynamics with Deep Learning. - Dule Shu; Wilson Zhen; Zijie Li; Amir Barati Farimani (CoRR, 2024)

Latent Neural PDE Solver: a reduced-order modelling framework for partial differential equations. - Zijie Li; Saurabh Patil; Francis Ogoke; Dule Shu; Wilson Zhen; Michael Schneier; John R. Buchanan Jr.; Amir Barati Farimani (CoRR, 2024)

GradNav: Accelerated Exploration of Potential Energy Surfaces with Gradient-Based Navigation. - Janghoon Ock; Parisa Mollaei; Amir Barati Farimani (CoRR, 2024)

Visuo-Tactile Pretraining for Cable Plugging. - Abraham George; Selam Gano; Pranav Katragadda; Amir Barati Farimani (CoRR, 2024)

AlloyBERT: Alloy Property Prediction with Large Language Models. - Akshat Chaudhari; Chakradhar Guntuboina; Hongshuo Huang; Amir Barati Farimani (CoRR, 2024)

ThermoPore: Predicting Part Porosity Based on Thermal Images Using Deep Learning. - Peter Myung-Won Pak; Francis Ogoke; Andrew Polonsky; Anthony Garland; Dan S. Bolintineanu; Dan R. Moser; Michael J. Heiden; Amir Barati Farimani (CoRR, 2024)

Large Language Model Agent as a Mechanical Designer. - Yayati Jadhav; Amir Barati Farimani (CoRR, 2024)

Deep Learning for Melt Pool Depth Contour Prediction From Surface Thermal Images via Vision Transformers. - Francis Ogoke; Peter Myung-Won Pak; Alexander Myers; Guadalupe Quirarte; Jack L. Beuth; Jonathan Malen; Amir Barati Farimani (CoRR, 2024)

CaFA: Global Weather Forecasting with Factorized Attention on Sphere. - Zijie Li; Anthony Y. Zhou; Saurabh Patil; Amir Barati Farimani (CoRR, 2024)

Integrating Multi-Physics Simulations and Machine Learning to Define the Spatter Mechanism and Process Window in Laser Powder Bed Fusion. - Olabode Ajenifujah; Francis Ogoke; Florian Wirth; Jack L. Beuth; Amir Barati Farimani (CoRR, 2024)

BeadSight: An Inexpensive Tactile Sensor Using Hydro-Gel Beads. - Abraham George; Yibo Chen; Atharva Dikshit; Peter Myung-Won Pak; Amir Barati Farimani (CoRR, 2024)

Explainable Data-driven Modeling of Adsorption Energy in Heterogeneous Catalysis. - Tirtha Vinchurkar; Janghoon Ock; Amir Barati Farimani (CoRR, 2024)

AMGPT: a Large Language Model for Contextual Querying in Additive Manufacturing. - Achuth Chandrasekhar; Jonathan Chan 003; Francis Ogoke; Olabode Ajenifujah; Amir Barati Farimani (CoRR, 2024)

Query2CAD: Generating CAD models using natural language queries. - Akshay Badagabettu; Sai Sravan Yarlagadda; Amir Barati Farimani (CoRR, 2024)

LLM-Craft: Robotic Crafting of Elasto-Plastic Objects with Large Language Models. - Alison Bartsch; Amir Barati Farimani (CoRR, 2024)

Low Fidelity Visuo-Tactile Pretraining Improves Vision-Only Manipulation Performance. - Selam Gano; Abraham George; Amir Barati Farimani (CoRR, 2024)

Zero-Shot Uncertainty Quantification using Diffusion Probabilistic Models. - Dule Shu; Amir Barati Farimani (CoRR, 2024)

LLM-3D Print: Large Language Models To Monitor and Control 3D Printing. - Yayati Jadhav; Peter Myung-Won Pak; Amir Barati Farimani (CoRR, 2024)

Airfoil Diffusion: Denoising Diffusion Model For Conditional Airfoil Generation. - Reid Graves; Amir Barati Farimani (CoRR, 2024)

PLATO: Planning with LLMs and Affordances for Tool Manipulation. - Arvind Car; Sai Sravan Yarlagadda; Alison Bartsch; Abraham George; Amir Barati Farimani (CoRR, 2024)

Deep Learning based Optical Image Super-Resolution via Generative Diffusion Models for Layerwise in-situ LPBF Monitoring. - Francis Ogoke; Sumesh Kalambettu Suresh; Jesse Adamczyk; Dan S. Bolintineanu; Anthony Garland; Michael J. Heiden; Amir Barati Farimani (CoRR, 2024)

Explain Like I'm Five: Using LLMs to Improve PDE Surrogate Models with Text. - Cooper Lorsung; Amir Barati Farimani (CoRR, 2024)

Adsorb-Agent: Autonomous Identification of Stable Adsorption Configurations via Large Language Model Agent. - Janghoon Ock; Tirtha Vinchurkar; Yayati Jadhav; Amir Barati Farimani (CoRR, 2024)

Peptide-GPT: Generative Design of Peptides using Generative Pre-trained Transformers and Bio-informatic Supervision. - Aayush Shah; Chakradhar Guntuboina; Amir Barati Farimani (CoRR, 2024)

BAPULM: Binding Affinity Prediction using Language Models. - Radheesh Sharma Meda; Amir Barati Farimani (CoRR, 2024)

Predicting Change, Not States: An Alternate Framework for Neural PDE Surrogates. - Anthony Y. Zhou; Amir Barati Farimani (CoRR, 2024)

Fluid viscosity prediction leveraging computer vision and robot interaction. - Jong Hoon Park; Gauri Pramod Dalwankar; Alison Bartsch; Abraham George; Amir Barati Farimani (Eng. Appl. Artif. Intell., 2024)

Pretraining Strategies for Structure Agnostic Material Property Prediction. - Hongshuo Huang; Rishikesh Magar; Amir Barati Farimani (J. Chem. Inf. Model., 2024)

Multimodal language and graph learning of adsorption configuration in catalysis. - Janghoon Ock; Srivathsan Badrinarayanan; Rishikesh Magar; Akshay Antony; Amir Barati Farimani (Nat. Mac. Intell., 2024)

Pretraining a Neural Operator in Lower Dimensions. - AmirPouya Hemmasian; Amir Barati Farimani (Trans. Mach. Learn. Res., 2024)

Masked Autoencoders are PDE Learners. - Anthony Y. Zhou; Amir Barati Farimani (Trans. Mach. Learn. Res., 2024)

Strategies for Pretraining Neural Operators. - Anthony Y. Zhou; Cooper Lorsung; AmirPouya Hemmasian; Amir Barati Farimani (Trans. Mach. Learn. Res., 2024)

GPCR-BERT: Interpreting Sequential Design of G Protein-Coupled Receptors Using Protein Language Models. - Seongwon Kim; Parisa Mollaei; Akshay Antony; Rishikesh Magar; Amir Barati Farimani (J. Chem. Inf. Model., 2024)

Physics informed token transformer for solving partial differential equations. - Cooper Lorsung; Zijie Li; Amir Barati Farimani (Mach. Learn. Sci. Technol., 2024)

Dual Diffusion for Unified Image Generation and Understanding. - Zijie Li; Henry Li; Yichun Shi; Amir Barati Farimani; Yuval Kluger; Linjie Yang; Peng Wang (CVPR, 2025)

RT-Cache: Training-Free Retrieval for Real-Time Manipulation. - Owen Kwon; Abraham George; Alison Bartsch; Amir Barati Farimani (Humanoids, 2025)

LLM-SR: Scientific Equation Discovery via Programming with Large Language Models. - Parshin Shojaee; Kazem Meidani; Shashank Gupta; Amir Barati Farimani; Chandan K. Reddy (ICLR, 2025)

Text2PDE: Latent Diffusion Models for Accessible Physics Simulation. - Anthony Y. Zhou; Zijie Li; Michael Schneier; John R. Buchanan Jr.; Amir Barati Farimani (ICLR, 2025)

VITaL Pretraining: Visuo-Tactile Pretraining for Tactile and Non-Tactile Manipulation Policies. - Abraham George; Selam Gano; Pranav Katragadda; Amir Barati Farimani (ICRA, 2025)

Multi-Peptide: Multimodality Leveraged Language-Graph Learning of Peptide Properties. - Srivathsan Badrinarayanan; Chakradhar Guntuboina; Parisa Mollaei; Amir Barati Farimani (J. Chem. Inf. Model., 2025)

MOFGPT: Generative Design of Metal-Organic Frameworks using Language Models. - Srivathsan Badrinarayanan; Rishikesh Magar; Akshay Antony; Radheesh Sharma Meda; Amir Barati Farimani (J. Chem. Inf. Model., 2025)

Latent neural PDE solver: A reduced-order modeling framework for partial differential equations. - Zijie Li; Saurabh Patil; Francis Ogoke; Dule Shu; Wilson Zhen; Michael Schneier; John R. Buchanan Jr.; Amir Barati Farimani (J. Comput. Phys., 2025)

OpenVR: Teleoperation for manipulation. - Abraham George; Alison Bartsch; Amir Barati Farimani (SoftwareX, 2025)

Text to Band Gap: Pre-trained Language Models as Encoders for Semiconductor Band Gap Prediction. - Ying-Ting Yeh; Janghoon Ock; Amir Barati Farimani (CoRR, 2025)

Modeling Melt Pool Features and Spatter Using Symbolic Regression and Machine Learning. - Olabode Ajenifujah; Amir Barati Farimani (CoRR, 2025)

AdditiveLLM: Large Language Models Predict Defects in Additive Manufacturing. - Peter Myung-Won Pak; Amir Barati Farimani (CoRR, 2025)

NANOGPT: A Query-Driven Large Language Model Retrieval-Augmented Generation System for Nanotechnology Research. - Achuth Chandrasekhar; Omid Barati Farimani; Olabode Ajenifujah; Janghoon Ock; Amir Barati Farimani (CoRR, 2025)

LLM-Drone: Aerial Additive Manufacturing with Drones Planned Using Large Language Models. - Akshay Raman; Chad Merrill; Abraham George; Amir Barati Farimani (CoRR, 2025)

Protein Structure-Function Relationship: A Kernel-PCA Approach for Reaction Coordinate Identification. - Parisa Mollaei; Amir Barati Farimani (CoRR, 2025)

Generative Latent Neural PDE Solver using Flow Matching. - Zijie Li; Anthony Y. Zhou; Amir Barati Farimani (CoRR, 2025)

LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models. - Parshin Shojaee; Ngoc-Hieu Nguyen; Kazem Meidani; Amir Barati Farimani; Khoa D. Doan; Chandan K. Reddy (CoRR, 2025)

Semantic Intelligence: Integrating GPT-4 with A Planning in Low-Cost Robotics. - Jesse Barkley; Abraham George; Amir Barati Farimani (CoRR, 2025)

RT-cache: Efficient Robot Trajectory Retrieval System. - Owen Kwon; Abraham George; Alison Bartsch; Amir Barati Farimani (CoRR, 2025)

Neural Functional: Learning Function to Scalar Maps for Neural PDE Surrogates. - Anthony Y. Zhou; Amir Barati Farimani (CoRR, 2025)

BlastOFormer: Attention and Neural Operator Deep Learning Methods for Explosive Blast Prediction. - Reid Graves; Anthony Y. Zhou; Amir Barati Farimani (CoRR, 2025)

DistMLIP: A Distributed Inference Platform for Machine Learning Interatomic Potentials. - Kevin Han; Bowen Deng; Amir Barati Farimani; Gerbrand Ceder (CoRR, 2025)

Beyond Force Metrics: Pre-Training MLFFs for Stable MD Simulations. - Shagun Maheshwari; Janghoon Ock; Adeesh Kolluru; Amir Barati Farimani; John R. Kitchin (CoRR, 2025)

LLM-guided Chemical Process Optimization with a Multi-Agent Approach. - Tong Zeng; Srivathsan Badrinarayanan; Janghoon Ock; Cheng-Kai Lai; Amir Barati Farimani (CoRR, 2025)

Planning and Reasoning With 3D Deformable Objects for Hierarchical Text-to-3D Robotic Shaping. - Alison Bartsch; Amir Barati Farimani (IEEE Robotics Autom. Lett., 2025)

Large Language Model Agent for Modular Task Execution in Drug Discovery. - Janghoon Ock; Radheesh Sharma Meda; Srivathsan Badrinarayanan; Neha S. Aluru; Achuth Chandrasekhar; Amir Barati Farimani (CoRR, 2025)

Automating MD simulations for Proteins using Large language Models: NAMD-Agent. - Achuth Chandrasekhar; Amir Barati Farimani (CoRR, 2025)

PinchBot: Long-Horizon Deformable Manipulation with Guided Diffusion Policy. - Alison Bartsch; Arvind Car; Amir Barati Farimani (CoRR, 2025)

LLM Trainer: Automated Robotic Data Generating via Demonstration Augmentation using LLMs. - Abraham George; Amir Barati Farimani (CoRR, 2025)

Reframing Generative Models for Physical Systems using Stochastic Interpolants. - Anthony Y. Zhou; Alexander Wikner; Amaury Lancelin; Pedram Hassanzadeh; Amir Barati Farimani (CoRR, 2025)

RheOFormer: A generative transformer model for simulation of complex fluids and flows. - Maedeh Saberi; Amir Barati Farimani; Safa Jamali (CoRR, 2025)

Agentic Additive Manufacturing Alloy Discovery. - Peter Myung-Won Pak; Achuth Chandrasekhar; Amir Barati Farimani (CoRR, 2025)

Meta-Learning for Cross-Task Generalization in Protein Mutation Property Prediction. - Srivathsan Badrinarayanan; Yue Su; Janghoon Ock; Alan Pham; Sanya Ahuja; Amir Barati Farimani (CoRR, 2025)

TDFlow: Agentic Workflows for Test Driven Software Engineering. - Kevin Han; Siddharth Maddikayala; Tim Knappe; Om Patel; Austen Liao; Amir Barati Farimani (CoRR, 2025)