Mechanical and AI LAB (MAIL)

Research Snapshot

Our publications span 2011–2026, from transport phenomena and nanoscale materials to AI for scientific discovery, robotics, manufacturing, and biology. These connected themes offer a guide to the chronological bibliography below.

Nanoscale Transport, Membranes, and Sensing. Early studies of water transport in carbon nanotubes (2011) and DNA sensing with MoS₂ (2014) led to work on nanopore desalination (2015), thermal transport, and AI-guided membrane design.

Physical Modeling and Scientific Discovery. From deep learning of transport phenomena (2017) to flexible PDE learning with OFormer (2023), scalable modeling with FactFormer (NeurIPS 2023), and equation discovery with LLM-SR (ICLR 2025).

Materials and Molecular Discovery. Learning useful molecular and materials representations through MolCLR (2022), MOFormer (2023), and TransPolymer (2023); extending prediction toward generation with MOFGPT (2025) and autonomous search with Adsorb-Agent (2026).

Robotics and Embodied Learning. Learning perception and manipulation policies for deformable objects, including robotic clay sculpting; connecting language-guided planning in LLM-Craft (2025) with visuo-tactile policy pretraining in VITaL (ICRA 2025).

AI for Manufacturing. Linking process understanding to control: MeltpoolNet (2022) predicts melt-pool characteristics, LLM-3D Print (2025) uses feedback for printer control, and Image2Gcode (2026) translates images into manufacturing toolpaths.

Biology and Health. Connecting molecular simulation and protein modeling with biological applications—from machine learning for molecular dynamics (2020) and airway organoids (2022) to protein language models, AgentD drug-discovery workflows (2026), and recent airway-organoid research (2026).

2026

142. Ziyue Wang, Yayati Jadhav, Peter Pak, A. Barati Farimani; “Image2Gcode: Image-to-G-code generation for additive manufacturing using diffusion-transformer model”, Additive Manufacturing Letters, 17, 100374, 2026.

Image2Gcode overview: object photographs and sketches are converted into G-code toolpaths and 3D-printed parts. Figure 1, Wang et al., arXiv:2511.20636v3, CC BY 4.0.

141. Kevin Han, Bowen Deng, A. Barati Farimani, Gerbrand Ceder; “DistMLIP: A distributed inference platform for machine learning interatomic potentials”, International Conference on Learning Representations (ICLR), 2026.

undefined Source: https://arxiv.org/abs/2506.02023

140. Janghoon Ock, Radheesh Sharma Meda, Tirtha Vinchurkar, Yayati Jadhav, A. Barati Farimani; “Adsorb-Agent: autonomous identification of stable adsorption configurations via a large language model agent”, Digital Discovery, 5(2), 617–629, 2026.

Representative figure for publication 140. Source: https://arxiv.org/abs/2410.16658. Adsorb-Agent workflow for proposing and evaluating molecule–surface adsorption configurations.

139. Yayati Jadhav, A. Barati Farimani; “Large language model agent as a mechanical designer”, Journal of Engineering Design, 1–37, 2026.

Representative figure for publication 139. Source: https://arxiv.org/abs/2404.17525. Truss design optimization visualization supplied by coauthor Yayati Jadhav.

138. Janghoon Ock, Radheesh Sharma Meda, Srivathsan Badrinarayanan, Neha S. Aluru, Achuth Chandrasekhar, A. Barati Farimani; “Large Language Model Agent for Modular Task Execution in Drug Discovery”, Journal of Chemical Information and Modeling, 66(4), 2055–2068, 2026.

AgentD modules and workflow for computational drug discovery. Source: https://arxiv.org/abs/2507.02925

137. Peter Pak, Achuth Chandrasekhar, A. Barati Farimani; “Agentic additive manufacturing alloy evaluation”, Additive Manufacturing Letters, 17, 100355, 2026.

Agentic alloy evaluation workflow connecting language-model tools, material properties, and manufacturing process maps. Source: https://arxiv.org/abs/2510.02567

2025

136. A. Bartsch, A. Barati Farimani; “Planning and Reasoning With 3D Deformable Objects for Hierarchical Text-to-3D Robotic Shaping”, IEEE Robotics and Automation Letters, 10(6), 6215–6222, 2025.

Point-cloud processing of clay shapes for hierarchical robotic sculpting. Source: https://arxiv.org/abs/2412.01765

135. A. Bartsch, A. Barati Farimani; “LLM-Craft: Robotic Crafting of Elasto-Plastic Objects With Large Language Models”, IEEE Robotics and Automation Letters, 10(10), 10450–10457, 2025.

LLM-Craft uses camera observations and language-model planning to guide robotic clay shaping. Source: https://arxiv.org/abs/2406.08648

134. Yayati Jadhav, Peter Pak, A. Barati Farimani; “LLM-3D print: Large Language Models to monitor and control 3D printing”, Additive Manufacturing, 114, 105027, 2025.

Representative figure for publication 134. Source: https://arxiv.org/abs/2408.14307. A feedback cycle for language-model-assisted monitoring and control of 3D printing.

133. Francis Ogoke, Sumesh Kalambettu Suresh, Jesse Adamczyk, Dan Bolintineanu, Anthony Garland, Michael Heiden, A. Barati Farimani; “Deep Learning based Optical Image Super-Resolution via Generative Diffusion Models for Layerwise in-situ LPBF Monitoring”, Additive Manufacturing, 107, 104790, 2025.

Representative figure for publication 133. Source: https://arxiv.org/abs/2409.13171. Diffusion-based enhancement of low-resolution process-monitoring images in additive manufacturing.

132. Zijie Li, Saurabh Patil, Francis Ogoke, Dule Shu, Wilson Zhen, Michael Schneier, John R. Buchanan Jr., A. Barati Farimani; “Latent neural PDE solver: A reduced-order modeling framework for partial differential equations”, Journal of Computational Physics, 524, 113705, 2025.

Representative figure for publication 132. Source: https://arxiv.org/abs/2402.17853. Latent PDE solver architecture with a spatial encoder, reduced-state evolution model, and decoder.

131. Abraham George, Alison Bartsch, A. Barati Farimani; “OpenVR: Teleoperation for manipulation”, SoftwareX, 29, 102054, 2025.

Virtual-reality teleoperation pipeline connecting the user, robot controller, and scene observations. Source: https://arxiv.org/abs/2305.09765

130. Anthony Zhou, A. Barati Farimani; “Predicting change, not states: An alternate framework for neural PDE surrogates”, Computer Methods in Applied Mechanics and Engineering, 441, 117990, 2025.

Temporal-derivative prediction used to advance a neural PDE surrogate in time. Source: https://arxiv.org/abs/2412.13074

129. Zijie Li, Henry Li, Yichun Shi, A. Barati Farimani, Yuval Kluger, Linjie Yang, Peng Wang; “Dual diffusion for unified image generation and understanding”, Proceedings of the Computer Vision and Pattern Recognition Conference, 2025, 2779–2790.

Representative figure for publication 129. Source: https://arxiv.org/abs/2501.00289. Dual Diffusion Transformer architecture for joint image and text denoising.

128. Peter Pak, A. Barati Farimani; “AdditiveLLM: Large Language Models Predict Defects in Additive Manufacturing”, Additive Manufacturing Letters, 14, 100292, 2025.

AdditiveLLM training and prediction workflow for additive-manufacturing defects. Source: https://arxiv.org/abs/2501.17784

127. Abraham George, Selam Gano, Pranav Katragadda, A. Barati Farimani; “VITaL Pretraining: Visuo-tactile pretraining for tactile and non-tactile manipulation policies”, 2025 IEEE International Conference on Robotics and Automation (ICRA), 258–264, 2025.

VITaL combines visual and tactile pretraining for robot imitation learning. Source: https://arxiv.org/abs/2403.11898

126. Dhruv Bhattaram, Kian Golestan, Xuanshuo Zhang, Shihong Yang, Zhuowei Gong, Steven L Brody, Amjad Horani, Victoria A Webster-Wood, A. Barati Farimani, Xi Ren; “AggreBots: Configuring CiliaBots through guided, modular tissue aggregation”, Science Advances, 11(39), eadx4176, 2025.

AggreBot motion visualization from Carnegie Mellon College of Engineering research coverage. Source: https://www.science.org/doi/10.1126/sciadv.adx4176

125. Parisa Mollaei, A. Barati Farimani; “Protein structure–function relationship: a kernel-PCA approach for reaction coordinate identification”, Journal of Chemical Theory and Computation, 21(14), 7122–7130, 2025.

Kernel-PCA framework for finding protein reaction coordinates from molecular trajectories. Source: https://arxiv.org/abs/2503.19186

124. Parshin Shojaee, Ngoc-Hieu Nguyen, Kazem Meidani, A. Barati Farimani, Khoa D Doan, Chandan K Reddy; “LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models”, International Conference on Machine Learning (ICML), 2025.

Representative figure for publication 124. Source: https://arxiv.org/abs/2504.10415. Scientific equation-discovery workflow evaluated by LLM-SRBench.

123. Anthony Zhou, A. Barati Farimani; “Neural Functional: Learning Function to Scalar Maps for Neural PDE Surrogates”, Advances in Neural Information Processing Systems (NeurIPS), 2025.

Neural Functional architecture for learning function-to-scalar maps and functional derivatives. Source: https://arxiv.org/abs/2505.13275

122. Srivathsan Badrinarayanan, Rishikesh Magar, Akshay Antony, Radheesh Sharma Meda, A. Barati Farimani; “MOFGPT: Generative design of metal–organic frameworks using language models”, Journal of Chemical Information and Modeling, 65(17), 9049–9060, 2025.

MOFGPT workflow for generating metal–organic frameworks. Source: https://arxiv.org/abs/2506.00198

121. Tong Zeng, Srivathsan Badrinarayanan, Janghoon Ock, Cheng-Kai Lai, A. Barati Farimani; “LLM-guided chemical process optimization with a multi-agent approach”, Machine Learning: Science and Technology, 6(4), 045067, 2025.

Multi-agent workflow for chemical process optimization. Source: https://arxiv.org/abs/2506.20921

120. Chad Merrill, Akshay Raman, Abraham George, A. Barati Farimani; “LLM-drone: aerial additive manufacturing with drones planned using large language models”, Construction Robotics, 9(2), 20, 2025.

Representative figure for publication 120. Source: https://arxiv.org/abs/2503.17566. LLMDrone system overview connecting language planning, vision, and aerial assembly.

119. Owen Kwon, Abraham George, Alison Bartsch, A. Barati Farimani; “RT-Cache: Training-Free Retrieval for Real-Time Manipulation”, 2025 IEEE-RAS 24th International Conference on Humanoid Robots (Humanoids), 1–8, 2025.

RT-Cache pipeline for retrieving robot trajectories. Source: https://arxiv.org/abs/2505.09040

2024

118. Alison Bartsch, Charlotte Avra, A. Barati Farimani; "Sculptbot: Pre-trained models for 3d deformable object manipulation", 2024 IEEE International Conference on Robotics and Automation (ICRA), 12548-12555, 2024.

Representative figure for publication 118. Source: https://arxiv.org/abs/2309.08728. SculptBot robot and examples of sculpted clay shapes.

117. AmirPouya Hemmasian, A. Barati Farimani; "Multi-scale time-stepping of partial differential equations with transformers", Computer Methods in Applied Mechanics and Engineering, 426, 116983, 2024.

Autoencoder and transformer architecture for multiscale PDE time stepping. Source: https://arxiv.org/abs/2311.02225

116. Francis Ogoke, Quanliang Liu, Olabode Ajenifujah, Alexander Myers, Guadalupe Quirarte, Jonathan Malen, Jack Beuth, A. Barati Farimani; "Inexpensive high fidelity melt pool models in additive manufacturing using generative deep diffusion", Materials & Design, 245, 113181, 2024.

Representative figure for publication 116. Source: https://arxiv.org/abs/2311.16168. Diffusion-based upscaling of melt pool simulations.

115. Janghoon Ock, Srivathsan Badrinarayanan, Rishikesh Magar, Akshay Antony, A. Barati Farimani; "Multimodal language and graph learning of adsorption configuration in catalysis", Nature Machine Intelligence, 6 (12), 1501-1511, 2024.

Representative figure for publication 115. Source: https://arxiv.org/abs/2401.07408. Graph-assisted language model training for catalyst adsorption energies.

114. Cooper Lorsung, A. Barati Farimani; "Picl: Physics informed contrastive learning for partial differential equations", APL Machine Learning, 2 (4), 2024.

Physics-informed contrastive pretraining workflow. Source: https://arxiv.org/abs/2401.16327

113. Alison Bartsch, Arvind Car, Charlotte Avra, A. Barati Farimani; "SculptDiff: Learning Robotic Clay Sculpting from Humans with Goal Conditioned Diffusion Policy", International Conference on Intelligent Robots and Systems (IROS), 2024.

Goal-conditioned robotic clay sculpting examples and framework. Source: https://arxiv.org/abs/2403.10401

112. Janghoon Ock, Parisa Mollaei, A. Barati Farimani; "Gradnav: Accelerated exploration of potential energy surfaces with gradient-based navigation", Journal of Chemical Theory and Computation, 20 (10), 4088-4098, 2024.

GradNav algorithm and navigation across potential energy wells. Source: https://arxiv.org/abs/2403.10358

111. Anthony Zhou, A. Barati Farimani; "Masked Autoencoders are PDE Learners", Transactions on Machine Learning, 2024.

Masked PDE pretraining and downstream prediction tasks. Source: https://arxiv.org/abs/2403.17728

110. Parisa Mollaei, Danush Sadasivam, Chakradhar Guntuboina, A. Barati Farimani; "IDP-Bert: predicting properties of intrinsically disordered proteins using large language models", The Journal of Physical Chemistry B, 128 (49), 12030-12037, 2024.

IDP-Bert sequence processing and protein property prediction workflow. Source: https://arxiv.org/abs/2403.19762

109. Akshat Chaudhari, Chakradhar Guntuboina, Hongshuo Huang, A. Barati Farimani; "AlloyBERT: Alloy Property Prediction with Large Language Models", Computational Material Science, 244 (113256), 2024.

AlloyBERT architecture for predicting alloy properties from text. Source: https://arxiv.org/abs/2403.19783

108. Hongshuo Huang, Amir Barati Farimani; "Multimodal learning of heat capacity based on transformers and crystallography pretraining". J. Appl. Phys. 28 April 2024; 135 (16): 165104.

107. Meidani, Kazem, Parshin Shojaee, Chandan K. Reddy, and Amir Barati Farimani. "Snip: Bridging mathematical symbolic and numeric realms with unified pre-training." International Conference on Learning Representation (2024).

106. Zhonglin Cao, Omid Barati Farimani, Janghoon Ock, and Amir Barati Farimani " Machine Learning in Membrane Design: From Property Prediction to AI-Guided Optimization" Nano Letters 2024 24 (10), 2953-2960.

105. Cooper Lorsung, Zijie Li and Amir Barati Farimani,"Physics informed token transformer for solving partial differential equations" Machine Learning: Science and Technology, Volume 5, Number 1

104. Seongwon Kim, Parisa Mollaei, Akshay Antony, Rishikesh Magar, and Amir Barati Farimani "GPCR-BERT: Interpreting Sequential Design of G Protein-Coupled Receptors Using Protein Language Models" Journal of Chemical Information and Modeling 2024 64 (4), 1134-1144

103. Hongshuo Huang, Rishikesh Magar, and A. Barati Farimani,"Pretraining Strategies for Structure Agnostic Material Property Prediction" Journal of Chemical Information and Modeling 2024 64 (3), 627-637

2023 (24)

102. Francis Ogoke, William Lee, Ning-Yu Kao, Alexander Myers, Jack Beuth, Jonathan Malen, A. Barati Farimani, Convolutional Neural Netwroks for melt depth prediction and visualization in laser powder bed fusion ", The International Journal of Advanced Manufacturing Technology, 2023 129 (24), 3047-3062.

101. Yuyang Wang, Zijie Li, A. Barati Farimani,"Graph Neural Networks for Molecules" A book chapter, Machine Learning in Molecular Science. 2023.

100. Janghoon Ock, Chakradhar Guntuboina, A. Barati Farimani, "Catalyst Energy Prediction with CatBERTa: Unveiling Feature Exploration Strategies through Large Language Model", ACS Catalysis, 2023 13 (24), 16032-16044

99. Saurabh Patil, Zijie Li, A. Barati Farimani,"Hyena neural operator for partial differential equations" 1 December 2023; 1 (4): 046114.", Applied Machine Learning. 2023, 19 (22), 8472-8480.

98. Chakradhar Guntuboina, Adrita Das, Parisa Mollaei, Seongwon Kim, and A. Barati Farimani, "PeptideBERT: A Language Model Based on Transformers for Peptide Property Prediction", Journal of Physical Chemistry Letters, 2023, 19, 15, 5077–5087.

97. Parisa Mollaei, A. Barati Farimani,"Unveiling Switching Function of Amino Acids in Proteins Using a Machine Learning Approach", Journal of Chemical Theory and Computation 2023, 19 (22), 8472-8480.

96. Yuyang Wang, Changwen Xu, Zijie Li, A. Barati Farimani, "Denoise Pretraining on Nonequilibrium Molecules for Accurate and Transferable Neural Potentials", Journal of Chemical Theory and Computation, 2023, 19, 15, 5077–5087.

95. Zhonglin Cao, Yuyang Wang, Cooper Lorsung, A. Barati Farimani,"Neural network predicts ion concentration profiles under nanoconfinement", Journal of Chemical Physics, 159(9), 2023, 116343.

94. Akshay Antony, Chakradhar Guntuboina, Rishikesh Magar, Lalit Ghule, Ruchit Doshi, Aman Khalid, Sharan Seshadri, A. Barati Farimani, "ManufacturingNet: A machine learning toolbox for engineers", SoftwareX, 2023, Volume 23.

93. Yayati Jadhav, Joseph Berthel, Chunshan Hu, Rahul Panat, Jack Beuth, A. Barati Farimani, "StressD: 2D Stress estimation using denoising diffusion model", Computer Methods in Applied Mechanics and Engineering, Volume 416, 2023, 116343.

92. AmirPouya Hemmasian, A. Barati Farimani, "Reduced-order modeling of fluid flows with transformers ", Physics of Fluids, 2023, 35, 057126.

91. Yuyang Wang, Kenji Shimada, A. Barati Farimani, "Airfoil GAN: encoding and synthesizing airfoils for aerodynamic shape optimization", Journal of Computational Design and Engineering, Volume 10, Issue 4, 2023, Pages 1350–1362.

90. Alexander J. Myers, Guadalupe Quirarte, Francis Ogoke, Brandon M. Lane, Syed Zia Uddin, A. Barati Farimani, Jack L. Beuth, Jonathan A. Malen, "High-resolution melt pool thermal imaging for metals additive manufacturing using the two-color method with a color camera", Additive Manufacturing, 2023, Volume 73.

89. Zijie Li, Kazem Meidani, A. Barati Farimani, "Transformer for Partial Differential Equations’ Operator Learning", Transactions on Machine Learning Research, 2023, 2835-8856.

88. Jarrett Anthony Boyd, Zhonglin Cao, Prakarsh Yadav, A. Barati Farimani, "DNA Detection Using a Single-Layer Phosphorene Nanopore", ACS Applied Nano Materials and, 2023, 6, 9, 7814–7820.

87. Parisa Mollaei, A. Barati Farimani, "Activity Map and Transition Pathways of G Protein-Coupled Receptor Revealed by Machine Learning", Journal of Chemical Information and Modeling, 2023, 63, 8, 2296–2304.

86. Changwen Xu, Yuyang Wang, and A. Barati Farimani, "TransPolymer: a Transformer-based language model for polymer property predictions", Nature Computational Material, 2023, 9, Article number: 64.

85. Rishikesh Magar, A. Barati Farimani, "Learning from mistakes: Sampling strategies to efficiently train machine learning models for material property prediction", Computational Materials Science, 2023, Volume 224, 112167.

84. Zhonglin Cao, Rishikesh Magar, Yuyang Wang, and A. Barati Farimani, "MOFormer: Self-Supervised Transformer Model for Metal–Organic Framework Property Prediction", Journal of the American Chemical Society, 2023 145 (5), 2958-2967

83. Kazem Meidani, A. Barati Farimani, "Identification of parametric dynamical systems using integer programming", Expert Systems with Applications, Volume 219, 2023.

82. Dule Shu, Zijie Li, A. Barati Farimani, "A physics-informed diffusion model for high-fidelity flow field reconstruction", Journal of Computational Physics, Volume 478, 2023, 111972.

81. AmirPouya Hemmasian, Francis Ogoke, Parand Akbari, Jonathan Malen, Jack Beuth, , A. Barati Farimani, "Surrogate Modeling of Melt Pool Temperature Field using Deep Learning", Additive Manufacturing Letters, 2023, In press.

80. Cooper Lorsung and A. Barati Farimani, "Mesh deep Q network: A deep reinforcement learning framework for improving meshes in computational fluid dynamics", AIP Advances , 2023, 13, 015026.

79. Huarong Peng, Renheng Wang, Liang Mei, Qingyong Zhang, Ting Ying, Zhengfang Qian, A. Barati Farimani, Damien Voiry, Zhiyuan Zeng, "Transition metal dichalcogenide-based functional membrane: Synthesis, modification, and water purification applications", Matter, 2023, Volume 6, Issue 1, 59-96.

2022 (24)

78. Yue Jian, Yuyang Wang, and A. Barati Farimani, "Predicting CO2 Absorption in Ionic Liquids with Molecular Descriptors and Explainable Graph Neural Networks" ACS Sustainable Chemistry & Engineering , 2022, 10 (50), 16681-16691.

77. Magar, Rishikesh., Wang, Yuyang, A. Barati Farimani, "Crystal twins: self-supervised learning for crystalline material property prediction", Nature Computational Material Science, 2022, 8, 231.

76. Magar, Rishikesh, Yuyang Wang, Cooper Lorsung, Chen Liang, Hariharan Ramasubramanian, Peiyuan Li, and A. Barati Farimani, "AugLiChem: Data Augmentation Library of Chemical Structures for Machine Learning" Machine Learning: Science and Technology , 2022.

75. Odinakachukwu Francis Ogoke, Kyle Johnson, Michael Glinsky, Chris Laursen, Sharlotte Kramer, A. Barati Farimani, "Deep-learned generators of porosity distributions produced during metal Additive Manufacturing",Additive Manufacturing, 2022, 103250.

74. Zhonglin Cao, Prakarsh Yadav, A. Barati Farimani," Which 2D Material is Better for DNA Detection: Graphene, MoS2, or MXene?", Nano Letters, 2022, 19, 7874–7881.

73. AmirPouya Hemmasian, Kazem Meidani, Seyedali Mirjalili, A. Barati Farimani, "Accelerating Optimization Using Vectorized Moth-Flame Optimizer (vMFO)",Handbook of Moth-Flame Optimization Algorithm 2022, 9781003205326.

72. Zhonglin Cao, A. Barati Farimani "Diffusion Mechanism of Water in Conductive Metal-Organic Frameworks", Physical Chemistry Chemical Physics, 2022, 24, 24852-24859

71. Kazem Meidani, Seyedali Mirjalili, A. Barati Farimani, "MAB-OS: Multi-Armed Bandits Metaheuristic Optimizer Selection", Applied Soft Computing, 2022, 109452.

70. Yilang Liu, A. Barati Farimani "An Energy-Saving Snake Locomotion Pattern Learned in Physical Constrained Environment with Online Model-based Policy Gradient Method", Journal of Mechanisms and Robotics,1-11, 2022.

69. Piyumi Wijesekara, Prakarsh Yadav, Lydia A. Perkins, Donna B. Stolz, Jonathan M. Franks, Simon C. Watkins, Emily Reinoso Jacome, Steven L. Brody, Amjad Horani, Jian Xu, A. Barati Farimani, Xi Ren, "Engineering rotating apical-out airway organoid for assessing respiratory cilia motility", iScience, Volume 25, Issue 8, 2022, 104730.

68. Yayati Jadhav, A. Barati Farimani "Dominant motion identification of multi-particle system using deep learning from video", Neural Computing and Applications, 2022.

67. Yuyang Wang, Rishikesh Magar, Chen Liang, A. Barati Farimani "Improving Molecular Contrastive Learning via Faulty Negative Mitigation and Decomposed Fragment Contrast", Journal of Chemical Information and Modeling , 2022, ASAP.

66. Yuyang Wang, Joe Joseph, T. P Aniruddhan Unni, Soji Yamakawa, A. Barati Farimani , Kenji Shimada, "3D Ship Hull Encoding and Optimization via Deep Neural Networks", Journal of Mechanical Design, 2022, 1-15.

65. Prakarsh Yadav, P Mollaei, Zhonglin Cao, Yuyang Wang, A. Barati Farimani "Prediction of GPCR activity using machine learning ", Computational and Structural Biotechnology Journal, 2022, 20, 2564-2573.

64. Parand Akbari, Francis Ogoke, Ning-Yu Kao, Kazem Meidani, Chun-Yu Yeh, William Lee, A. Barati Farimani "MeltpoolNet: Melt pool characteristic prediction in Metal Additive Manufacturing using machine learning", Additive Manufacturing, 2022, 55, 102817.

63. Zijie Li, Kazem Meidani, Prakarsh Yadav, A. Barati Farimani "Graph Neural Network Accelerated Molecular Dynamics ", Journal of Chemical Physics, 2022, 156, 144103.

62. L. Mei, Z. Cao, T. Ying, R. Yang, H. Peng, G. Wang, L. Zheng, Y. Chen, C. Y. Tang, D. Voiry, H. Wang, A. Barati Farimani , Z. Y. Zeng,"Simultaneous electrochemical exfoliation and covalent functionalization of MoS2 membrane for ion sieving", Advanced Materials, 2022.

61. Kazem Meidani, SeyyedAli Mirjalili, A. Barati Farimani "Online Metaheuristic Algorithm Selection ", Expert Systems with Applications, 2022, 201, 117058.

60. Prakarsh Yadav, A. Barati Farimani "Activation Pathways of Neurotensin Receptor 1 Elucidated Using Statistical Machine Learning", ACS Chemical Neuroscience, 2022, 3, 8, 1333–1341.

59.Yuyang Wang, Jianren Wang, Zhonglin Cao, A. Barati Farimani "Molecular Contrastive Learning of Representations via Graph Neural Networks", Nature Machine Intelligence, 2022, 4, 279-287.

58. Lu Xu, Rishikesh Magar, A. Barati Farimani "Forecasting COVID-19 new cases using deep learning methods", Computers in Biology and Medicine, 2022, 144, 105342.

57. Zijie Li, A. Barati Farimani "Graph neural network-accelerated Lagrangian fluid simulation", Computers and Graphics, 2022, 103, 201-211.

56. AmirPouya Hemmasian, Kazem Meidani, SeyyedAli Mirjalili, A. Barati Farimani "VecMetaPy: A vectorized framework for metaheuristic optimization in Python", Advances in Software Engineering, 2022, 166, 103092.

55. Kazem Meidani, AmirPouya Hemmasian, SeyyedAli Mirjalili, A. Barati Farimani "Adaptive Grey Wolf Optimizer", Neural Computing and Applications, 2022, 1-21.

2021 (15)

54. Baishali Mullick, Rishikesh Magar, Aastha Jhunjhunwala A. Barati Farimani "Understanding Mutation Hotspots for the SARS-CoV-2 Spike Protein Using Shannon Entropy and K-Means Clustering", Computers in Biology and Medicine, 2021, 104915.

53. Zhonglin Cao, Greta Markey, A. Barati Farimani "Ozark Graphene Nanopore for Efficient Water Desalination", Physical Chemistry B, 2021.

52. Pranshu Pant, Ruchit Doshi, Pranav Bahl, A. Barati Farimani "Deep learning for reduced order modelling and efficient temporal evolution of fluid simulations", Physics of Fluid, 2021, 33, 101107.

51. Phil M. Smith, Indorica Sutradhar, Maxwell Telmer, Rishikesh Magar, A. Barati Farimani and B. Reeja-Jayan "Isolating Specific vs. Non-Specific Binding Responses in Conducting Polymer Biosensors for Bio-Fingerprinting ", Sensors, 2021, 21 (19), 6335.

50. Francis Ogoke, Kazem Meidani, Amirreza Hashemi, A. Barati Farimani "Graph convolutional networks applied to unstructured flow field data" Machine Learning: Science and Technology, 2021, 2, 045020.

49. Junwoong Yoon, Zhonglin Cao, Rajesh Raju, Yuyang Wang, Robert Burnley, Andrew J Gellman, A. Barati Farimani and Zachary W Ulissi "Deep reinforcement learning for predicting kinetic pathways to surface reconstruction in a ternary alloy", Machine Learning: Science and Technology, 2021, 2 ,045018.

48. Yuyang Wang, Zhonglin Cao, A. Barati Farimani "Efficient water desalination with graphene nanopores obtained using artificial intelligence" Nature 2D Materials, 2021, 5, Article number: 66.

47. Kazem Meidani, Zhonglin Cao, A. Barati Farimani, "Titanium Carbide MXene for Water Desalination: A Molecular Dynamics Study", ACS Applied Nano Materials, 2021, 4, 6, 6145–6151.

46. Hoaliang Jiang, Zhenguo Nie, Roselyn Yeo, A. Barati Farimani, Levent Burak Kara"StressGAN: A Generative Deep Learning Model for Two-dimensional Stress Distribution Prediction" Journal of Applied Mechanics, 2021, 88(5): 051005.

45. Francis Ogoke, A. Barati Farimani, "Thermal Control of Laser Powder Bed Fusion Using Deep Reinforcement Learning", Additive Manufacturing, 2021, 102033.

44. Angran Li, A. Barati Farimani, Yongjie Jessica Zhang"Deep Learning of Material Transport in Complex Neurite Transport" Scientific Reports, 2021, 11, Article number: 1128.

43. Kazem Meidani, A. Barati Farimani, "Data-driven identification of 2D Partial Differential Equations using extracted physical features", Computer Methods in Applied Mechanics and Engineering, 2021, Volume 311, 113831.

Code and Data: https://github.com/BaratiLab/PDE-Identification-Features

42. Rishikesh Magar, Prakarsh Yadav, A. Barati Farimani, "Potential neutralizing antibodies discovered for novel corona virus using machine learning" Scientific Reports, 2021,11, Article number: 5261.

Code and Data: https://github.com/BaratiLab/Potential-Neutralizing-antibodies-discovered-for-novel-corona-virus-using-machine-learning

41. Prakarsh Yadav, Zhonglin Cao, A. Barati Farimani, "DNA Detection with Single-Layer Ti3C2 MXene Nanopore", ACS Nano, 2021, 15, 3, 4861–4869.

40. Rishikesh Magar, Lalit Ghule, Junhan Li, Yang Zhao and A. Barati Farimani, "FaultNet: A Deep Convolutional Neural Network for Bearing Fault Classification," IEEE Access, 2021, vol. 9, pp. 25189-25199, doi: 10.1109/ACCESS.2021.3056944.

Code: https://github.com/BaratiLab/FaultNet

2020 (6)

39. Mohammadreza Karamad, A. Barati Farimani, Rishikesh Magar, Samira Siahrostami, and Ian D. Gates "Heteroatom-Doped Transition Metal Nitrides for CO Electrochemical Reduction: A Density Functional Theory Screening Study", Journal of Physical Chemistry C, 2020,124, 48, 26344–26351.

38. Mohammad Reza Karamad, Rishikesh Magar, Yuting Shi, Samira Siahrostami, Ian D. Gates, and A. Barati Farimani "Orbital graph convolutional neural network for material property prediction", Physical Review Materials, 2020, 4, 093801.

Code: https://github.com/RishikeshMagar/OGCNN

37. Zhonglin Cao, Vincent Liu, A. Barati Farimani "Why is Single-Layer MoS2 a More Energy Efficient Membrane for Water Desalination?", ACS Energy Letters, 2020, 5, 7, 2217–2222

36. Alexander Joseph Gabourie, Saurabh Vinayak Suryavanshi, A. Barati Farimani and Eric Pop "Reduced Thermal Conductivity of Supported and Encased Monolayer and Bilayer MoS2", 2D Materials, 2020, 8, 1.

35. Paraskevi Gkeka, Gabriel Stoltz, A. Barati Farimani, Zineb Belkacemi, Michele Ceriotti, John D. Chodera, Aaron R. Dinner, Andrew L. Ferguson, Jean-Bernard Maillet, Hervé Minoux, Christine Peter, Fabio Pietrucci, Ana Silveira, Alexandre Tkatchenko, Zofia Trstanova, Rafal Wiewiora, and Tony Lelièvre "Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems", Journal of Chemical Theory and Computation, 2020, 16, 8, 4757–4775.

34. Samira Siahrostami, Santiago Jimenez Villegas, Amir Hassan Bagherzadeh Mostaghimi, Seoin Back, A. Barati Farimani , Haotian Wang, Kristin Aslaug Persson, and Joseph Montoya, "A Review on Challenges and Successes in Atomic-Scale Design of Catalysts for Electrochemical Synthesis of Hydrogen Peroxide", ACS Catalysis, 2020, 10, 14, 7495–7511.

2019 (4)

33. Zhonglin Cao, Vincent Liu, A. Barati Farimani "Water Desalination with Two-Dimensional Metal–Organic Framework Membranes", Nano Letters, 2019, 19, 12, 8638-8643.

32. Saurabh V. Suryavanshi, Alexander J. Gabourie, A. Barati Farimani, Eric Pop , "Thermal Boundary Conductance of Two-Dimensional MoS2 Interfaces", Journal of Applied Physics , 2019, 126, 055107.

31. Dilip Krishnamurthy, Hasso Weiland, A. Barati Farimani, Erin Antono, Josh Green, and Venkatasubramanian Viswanathan, "Machine Learning Based Approaches to Accelerate Energy Materials Discovery and Optimization", ACS Energy Letters., 2019, 4, pp 187–191

30. Ke Xu, Alexander J Gabourie, Arsalan Hashemi, Zheyong Fan, Ning Wei, A. Barati Farimani, Hannu-Pekka Komsa, Arkady V Krasheninnikov, Eric Pop, Tapio Ala-Nissila, "Thermal Transport in MoS2 from Molecular Dynamics using Different Empirical Potentials", Physical Review B, 99, 054303 , 2019.

Pre-CMU Publications from Stanford and Illinois

29. A. Barati Farimani, Mohammad Heiranian, N. R. Aluru, ” Identification of amino acids with sensitive nanoporous MoS2: towards machine learning-based prediction“, Nature 2D Materials, 2, 14, 2018.

28. A. Barati Farimani, Evan N. Feinberg, Vijay S. Pande “Binding Pathway of Opiates to μ Opioid Receptors Revealed by Unsupervised Machine Learning” Arxiv, 2018.

27. A. Barati Farimani, Joseph Gomes, Rishi Sharma, Franklin L. Lee, Vijay S. Pande, “Deep Learning Phase Segregation” Arxiv, 2018.

26. A. Barati Farimani, Joseph Gomes, Vijay S. Pande, “Deep Learning the Physics of Transport Phenomena” Arxiv, 2017.

Highlighted in Nature Physics

25. Franklin L. Lee*, A. Barati Farimani*, Kevin L. Gu, Hongping Yan, Michael F. Toney, Zhenan Bao, and Vijay S. Pande “Solution Phase Conformation and Dynamics of Conjugated Iso-indigo-Based Donor-Acceptor Polymer Single Chains“, Journal of Physical Chemistry Letters, 8, pp 5479–5486, 2017.

24. Yoon Kyeung Lee, Ki Jun Yu, Enming Song, A. Barati Farimani, Flavia Vitale, Zhaoqian Xie, Younghee Yoon, Yerim Kim, Andrew Richardson, Haiwen Luan, Yixin Wu, Xu Xie, Timothy H. Lucas, Kaitlyn Crawford, Yongfeng Mei, Xue Feng, Yonggang Huang, Brian Litt, Narayana R. Aluru, Lan Yin, and John A. Rogers “Dissolution of Monocrystalline Silicon Nanomembranes and Their Use as Encapsulation Layers and Electrical Interfaces in Water-Soluble Electronics“, ACS Nano, 2017, 11 (12), pp 12562–12572 .

23. Evan N. Feinberg*, A. Barati Farimani*, Carlos Hernandez, Vijay S. Pande, ”Ligand-Directed Conformational Change of Opioid Receptor Revealed by Kinetic Machine Learning”, biorxiv, 2017.

22. A. Barati Farimani, Mohammad Heiranian, Kyoungmin Min, Narayana Aluru, “Antibody Subclass Detection Using Graphene Nanopore“, Journal of Physical Chemistry Letters, 8 (7), pp1670-1676, 2017.

21. A. Barati Farimani, Payam Dibaeinia, N. R. Aluru,”DNA Origami-Graphene Hybrid Nanopore for DNA Detection”, ACS Applied Material Interfaces, 9 (1), pp 92100, 2017.

*Selected as ACS Editors Choice

20. Bitna Yi, Alam Jahangir, Andrew K. Evans, Denise Briggs, Kristine Ravina, Jacqueline Ernest, A. Barati Farimani, Wenchao Sun, Jayakumar Rajadas, Michael Green, Evan N. Feinberg, Vijay S. Pande, Mehrdad Shamloo ”Discovery of novel brain permeable and G protein-biased beta-1 adrenergic receptor partial agonists for the treatment of neurocognitive disorders”,PLoS ONE, 12(7): e0180319, 2017.

19. E. Yalon, C.J. McClellan, K.K.H. Smithe, M. Muoz Rojo, R.L. Xu, S.V. Suryavanshi, A.J. Gabourie,C.M. Neumann, F. Xiong, A. Barati Farimani, E. Pop, ”Energy Dissipation in Monolayer MoS2 Electronics”, Nano Letters, 17, 3429-3433, 2017.

18. Fang, J. Zhao, K. Yu, E. Song, A. Barati Farimani , C. H. Chiang , X. Jin , Y. Xue , D. Xu , W. Du , K. J. Seo , Y. Zhong , Z. Yang , S. Won , G. Fang , S. W. Choi , S. Chaudhuri , Y. Huang , M. Ashraful Alam , J. Viventi , N.R. Aluru , J. A. Rogers, “Ultra-thin, Transferred Layers of Thermally Grown Silicon Dioxide as Biofluid Barriers for Bio-Integrated Flexible Electronic Systems“, Proceeding of National Academy of Sciences, 113, 42, 11682–11687 2016.

17. A. Barati Farimani, N. R. Aluru, “Existence of Multiple Phases of Water at Nanotube Interfaces”, Journal of Physical Chemistry C, 120,41, pp 23763–23771, 2016.

16. A. Barati Farimani, M. Heiranian, N. R. Aluru, “Nano-electro-mechanical pump: Giant pumping of water in carbon nanotubes”, Scientific Reports, 6, 26211, 2016.

15. M Heiranian, A. Barati Farimani, N.R. Aluru, “Water Desalination with a Single-Layer MoS2 Nanopore”, Nature Communications, 6, Article number 8616, 2015.

14. E. Freeman, A. Barati Farimani, N.R. Aluru, M.K. Philen, “Multiscale Modeling of an Autonomous Biomolecular Material Inspired by Cellular Mechanics”, Biomicrofluidics, 9, 064101, 2015.

13. Guru A. Venkatesan , Joonho Lee , A. Barati Farimani , Mohammad Heiranian , C. Patrick Collier , Narayana R. Aluru , Stephen A. Sarles. ”Adsorption kinetics dictate monolayer self-assembly for both lipid-in and lipid-out approaches to droplet interface bilayer formation”, Langmuir, 31 (47), pp. 12883–12893, 2015.

12. A. Barati Farimani, M. Heiranian and N. R. Aluru, “Electromechanical Signatures for DNA Sequencing through a Mechano-sensitive Nanopore”, Journal of Physical Chemistry Letters, Vol. 6, pp 650–657, 2015.

11. Lan Yin, A. Barati Farimani, Kyoungmin Min, Nandigana Vishal, Jasper Lam, Yoon Kyeung Lee, Narayana R. Aluru, John A. Rogers, “Mechanisms for Hydrolysis of Silicon Nanomembranes as Used in Bioresorbable Electronics“, Advanced Materials, 2015.

10. K. Min, A. Barati Farimani, N. R. Aluru, “Mechanically-Modulated Electronic Properties of Water-Filled Fullerenes”, MRS Communications, Volume 5, Issue 02, pp 305-310, 2015.

9. A. Barati Farimani, K. Min and N. R. Aluru, “DNA base detection using a single-layer MoS2”, ACS Nano, Vol. 8, No. 8, pp. 7914-7922, 2014.

Highlighted in Nature Nanotechnology

8. A. Barati Farimani, N. R. Aluru and E. Tajkhorshid, ”Thermodynamic insight into spontaneous hydration and rapid water permeation in aquaporins”, Applied Physics Letters, Vol. 105, No. 8, Art. No. 083702, 2014.

7. K. Min, A. Barati Farimani and N. R. Aluru, ”Mechanical behaviour of water filled C60”, Applied Physics Letters,Vol. 103, No. 26, Art. No. 263112, 2013.

6. A. Barati Farimani, Y. Wu and N. R. Aluru, ”Rotational motion of a single water molecule in a buckyball”, Physical Chemistry Chemical Physics, Vol. 15, No. 41, pp. 17993-18000, 2013.

5. B. Kumar, K. Min, M. Bashirzadeh, A. Barati Farimani, M.-H. Bae, D. Estrada, Y.D. Kim, P. Yasaei, Y.D. Park, E. Pop, N.R. Aluru, A. Salehi-Khojin, “The Role of External Defects in Chemical Sensing of Graphene Field-Effect Transistors,” Nano Letters, 2013.

4. S. M. H. Karimian, S. Izadi, A. Barati Farimani,” A study on the measurement of mean velocity and its convergence in molecular dynamics simulations“.International Journal for Numerical Methods in Fluids,Vol 67, Issue 12, 2130–2140, 2011.

3. A. Barati Farimani and N. R. Aluru, “Spatial diffusion of water in carbon nanotubes: From Fickian to ballistic motion”, Journal of Physical Chemistry B, Vol. 115, No. 42, pp. 12145-12149, 2011.

2. Farimani AB, Ferreira AD, Sousa ACM. “Computational modeling of the wind erosion on a sinusoidal pile using a moving boundary method“, Geomorphology, 130 : 299–311, 2011.

1. Ferreira AD, Farimani A, Sousa ACM. “Numerical and experimental analysis of wind erosion on a sinusoidal pile“. Environmental Fluid Mechanic 11: 167-181, 2011.

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