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News, talks, and lab milestones
News, talks, and lab milestones
Research advances, invited lectures, student achievements, and educational initiatives from the Mechanical and Artificial Intelligence Laboratory (MAIL) at Carnegie Mellon University.
Recent highlights
Recent highlights
March 2026 · From MAIL Ph.D. student to CMU professor
Congratulations to Dr. Francis Ogoke, a former MAIL Ph.D. student, on joining Carnegie Mellon University’s Department of Mechanical Engineering as an assistant professor. His doctoral research with Amir Barati Farimani developed machine-learning tools for additive manufacturing.
February 2026 · AI saves 3D prints in real time
MAIL researchers developed an AI-powered system that monitors 3D printing, diagnoses errors, and adjusts printing parameters in real time. The large-language-model-based approach operates without printer-specific pretraining, helping improve printing reliability and reduce manual supervision.
Read the CMU Engineering story
2026 · AI Agents for Engineers
Amir Barati Farimani’s graduate course introduces engineering students to AI systems that reason, plan, use tools, maintain memory, and interact with physical and simulated environments. Applications span scientific discovery, robotics, manufacturing, engineering design, and materials and molecular discovery.
Invited talks
Invited talks
Amir Barati Farimani’s invited lectures, seminars, and tutorials explore AI for engineering, materials discovery, molecular science, and transport phenomena.
2026
2026
August 2026 · Physical AI Accelerating Materials Science and Discovery
Gordon Research Conference on Computational Materials Science and Engineering (AI in Atomistic Modeling), Sunday River, Newry, ME.
2025
2025
October 2025 · Learning the Language of Atoms: Generative Pretraining Transformers (GPT) for Materials and Molecules
Bakar Institute of Digital Materials for the Planet (BIDMaP) Seminar, University of California, Berkeley.
January 2025 · Role of Large Language Models in Biological Discovery
Terasaki Talks, Terasaki Institute for Biomedical Innovation, Los Angeles, CA.
2024
2024
October 2024 · How Generative Pretraining Transformers (GPT) Have Transformed Scientific Computation
Oden Institute Seminar, The University of Texas at Austin.
October 2024 · Foundational Models
AI for Multidisciplinary Exploration and Discovery (AIMED) Workshop on Heterogeneous Catalysis, Big Ten Conference Center, Rosemont, IL.
July 2024 · Invited talk
Gordon Research Conference on Computational Materials Science and Engineering: The Role of Theories, Simulation, and Machine Learning in Materials Discovery, Sunday River, Newry, ME.
February 2024 · Robust Representation Learning with Transformers for Engineering Problems
Boeing Distinguished Researcher and Scholar Seminar (B-DRASS), Engineers Week, The Boeing Company.
2023
2023
November 2023 · Machine Learning in Nanopore Sequencing and Design
Black Forest Nanopore Meeting (BFNM), Freiburg im Breisgau, Germany.
October 2023 · Large Language Molecular Representation and Learning
M2D2 (Molecular Modeling and Drug Discovery) Reading Group, Valence Labs (online).
2021
2021
December 2021 · Plenary talk: Mechanics Meets Artificial Intelligence
GIST Symposium on Artificial Intelligence, South Korea.
May 2021 · Two Dimensional Materials for Water Desalination and DNA Detection: Can Machine Learning Help?
Nanopore Online Meeting.
February 2021 · Mechanics Meet Artificial Intelligence
Mechanical Engineering Departmental Seminar Series, Rice University.
January 2021 · Deep Reinforcement Learning in Material Discovery for Energy Applications
ARPA-E Seminar Series on AI in Material Discovery.
2020
2020
December 2020 · How AI Can Discover and Engineer Biology: From Antibody Design To Cryo-EM Super Resolution
NSF AI Institute: AI-Driven Discoveries in Biophysics.
December 2020 · Artificial Intelligence in Heat Transfer
NSF Workshop on Frontiers of Heat Transfer (online).
October 2020 · Orbital Graph Convolutional Neural Network for Material Property Prediction
New York Academy of Sciences: AI for Materials.
October 2020 · Artificial Intelligence in Mechanical Engineering
Woodruff School of Mechanical Engineering Departmental Seminar, Georgia Institute of Technology.
September 2020 · Machine Learning and Artificial Intelligence in Mechanical Engineering
Mechanical Engineering, Penn State.
May 2020 · Introduction to Machine Learning and Reinforcement Learning for Precision Engineers
ASPE Spring Meeting.
January 2020 · From Protein Sequences to Clinical Data: How Deep Learning Can Bridge the Gap with Functional Mapping?
Gordon Research Conference on Protein Folding and Dynamics, Galveston, TX.
2019
2019
November 2019 · Orbital Graph Convolution for Molecular Property Prediction
MolSSI Workshop, University of Maryland, College Park.
November 2019 · Artificial Intelligence in Mechanical Engineering
ASME Department Head Meeting, Salt Lake, UT.
October 2019 · Introduction to Machine Learning for Precision Engineers
Precision Engineering Annual Conference, Pittsburgh, PA.
October 2019 · Deep Learning of Transport Phenomena and Material Discovery
Michigan State University Machine Learning Seminar Series, Lansing, MI.
September 2019 · Deep Learning of Transport Phenomena and Material Discovery
University of Pittsburgh Mechanical Engineering Seminar, Pittsburgh, PA.
June 2019 · Learning Spatio-Temporal Convective Transport Using GAN
MLSE Conference, Georgia Institute of Technology, Atlanta, GA.
May 2019 · Learning Spatio-temporal Convection with Deep Generative Models
Foundational and Applied Data Science for Molecular and Material Science and Engineering, Lehigh University.
April 2019 · Machine Learning in Molecular Systems: From Conformational Changes in GPCRs to Small Molecule Discovery
Theoretical and Computational Biophysics Seminar, University of Illinois at Urbana-Champaign.
April 2019 · Creative Robots with Deep Reinforcement Learning
Robotics Institute, Carnegie Mellon University.
February 2019 · Deep Learning Convective Transport
Machine Learning in Computational Fluid Dynamics and Solid Mechanics, Los Alamos National Laboratory (Santa Fe).
2018
2018
December 2018 · Conditional Generative Adversarial Deep Neural Networks for Spatio-temporal Coarse Graining
Sorbonne University, Paris, France.
April 2018 · Deep Learning Transport Phenomena and Material Discovery
Materials Science and Engineering, University of Washington, Seattle.
April 2018 · Deep Learning Transport Phenomena and Material Discovery
Bioengineering, Mechanical and Chemical Engineering, Lehigh University.
March 2018 · Deep Learning Transport Phenomena and Material Discovery
Mechanical and Industrial Engineering, University of Illinois at Chicago.
February 2018 · Deep Learning Transport Phenomena and Material Discovery
Mechanical Engineering, Stevens Institute of Technology.
February 2018 · Deep Learning Transport Phenomena and Material Discovery
Mechanical and Aerospace Engineering, Syracuse University.
February 2018 · Deep Learning Transport Phenomena and Material Discovery
Mechanical Engineering, Carnegie Mellon University.
January 2018 · Machine Learning Aided Computational Drug and Material Discovery
Chemical and Biomolecular Engineering, Nanyang Technological University.
January 2018 · Deep Learning Transport Phenomena and Molecular Discovery
Energy, Environmental, and Chemical Engineering, Washington University.
2016
2016
September 2016 · Nanopores for Water Desalination and DNA Sequencing
Mechanical Engineering, Stanford University.
June 2016 · Insights into Opiate Binding and Activation of μ-Opioid Receptors
4th Annual Blue Waters Symposium, Sunriver Resort, OR.
May 2016 · Mechanism of μ-Opioid Receptor Deactivation
Chem-H Postdoctoral Retreat, Sonoma Valley.
April 2016 · Programming Graphene Nanopore with DNA Origami for DNA Sequencing
BCATS (Biomedical Computation at Stanford), Stanford University.
2015
2015
November 2015 · Functionality of Mechano-Sensitive Channel and TRPV1 Proteins
AFOSR Basic Research Initiative, Urbana, IL.
Lab news archive
Lab news archive
September 2020 · Congratulations to Rishikesh Magar and MReza for the acceptance of their paper in Physical Review Materials
July 2020 · Congratulations to Zhonglin (Johnny) and Vince for the acceptance of their paper in ACS Energy Letters.
March 2020 · Archived announcement: Professor Farimani was scheduled to speak at NSF workshop on New Frontiers of Thermal Transport in Orlando, Florida.
February 2020 · Professor Farimani co-organized an NSF workshop on Exuberance of Machine Learning in Transport Phenomena in Dallas, TX.
December 2019 · Our paper in Nano Letters has been featured in many news outlets : CMU, Phys.ORG, AzoCleantech, PopularMechanics, Nanowerk.
November 2019 · Congratulations to Zhonglin (Johnny) and Vince for the acceptance of their paper in Nano Letters
August 2019 · Prof. Farimani was an instructor for AI summer school hosted by Autodesk AI division in Toronto.
July 2019 · Prof. Farimani chaired the Mechanical Engineering track of Machine Learning in Science and Engineering at Georgia Tech .
April 2019 · Congratulations to Nina Prakash and Bryant Porras for winning Summer Undergraduate Fellowship. Keep up the great work!
January 2019 · Juan and Jason joined our team, welcome!
December 2018 · Professor Farimani presented lab research at CECAM workshop in Paris, France.
October 2018 · Vince and Nina joined our team, welcome!
October 2018 · MAIL is ready to go! with 8 new computers equipped with Nvidia 1080 ti graphic cards! Happy Machine Learning!
October 2018 · Seven master students joined MAIL, welcome all aboard! Check out our team growing
August 2018 · Professor Farimani taught Machine Learning and Artificial Intelligence
Earlier research and media
Earlier research and media
Our deep learning transport paper was highlighted in Nature Physics
Amir Barati Farimani was featured on the NVIDIA news for my Ebola Antibody design project.
Amir Barati Farimani received Stanly I. Weis Best Thesis award in ME department, UIUC.
Amir Barati Farimani was recognized as distinguished graduate student at Mechanical Engineering at University of Illinois at Urbana-Champaign
Amir Barati Farimani began his postdoctoral research at Professor Vijay Pande’s lab at Stanford, in Chemistry Department
Our work on water desalination with MoS2 nanopore in Nature Communications has been featured in multiple news outlets including:
Amir Barati Farimani was featured in the department of Mechanical Science and Engineering at University of Illinois
Our work on DNA sequencing using MoS2 nanopore in ACS Nano was highlighted in the following News/journal outlets:
2. UIUC News
3. NSF
4. AirForce Office of Scientific Research
5. ScienceDaily
6. Physics News
Our work on Graphene Field Effect Transistor in Nano Letters was highlighted in the following News outlets
3. Phys.Org
Google Sites
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