Jan Drgona
@drgona.bsky.social
Associate professor @JohnsHopkins, data scientist @PNNLab. Formerly at @KU_Leuven, @ClimateChangeAI. #SciML #PIML #control #energy #sustainability
Reposted by Jan Drgona
Join us in advancing data science and AI research! The Johns Hopkins Data Science and AI Institute Postdoctoral Fellowship Program is now accepting applications for the 2026–2027 academic year. Apply now! Deadline: Jan 23, 2026. Details and apply: apply.interfolio.com/179059
December 19, 2025 at 1:29 PM
Join us in advancing data science and AI research! The Johns Hopkins Data Science and AI Institute Postdoctoral Fellowship Program is now accepting applications for the 2026–2027 academic year. Apply now! Deadline: Jan 23, 2026. Details and apply: apply.interfolio.com/179059
Excited about the future of scientific machine learning under these DOE investments into our new Scidac institute called Learning Accelerated Domain Sciences (LEADS).
JHU is part of the new Learning Accelerated Domain Sciences (LEADS) Institute! DOE-funded, LEADS focuses on reshaping how AI supports scientific discovery. ROSEI's @drgona.bsky.social and Enrique Mallada, as well as Mahyar Fazlyab are involved. #HopkinsEnergy energyinstitute.jhu.edu/johns-hopkin...
Johns Hopkins Joins DOE’s New AI-Powered Scientific Discovery Institute - Johns Hopkins - Ralph O’Connor Sustainable Energy Institute
Johns Hopkins is part of the new multi-institution Learning Accelerated Domain Sciences (LEADS) Institute, a Department of Energy-funded collaborative initiative focused...
energyinstitute.jhu.edu
December 11, 2025 at 4:37 PM
Excited about the future of scientific machine learning under these DOE investments into our new Scidac institute called Learning Accelerated Domain Sciences (LEADS).
I am traveling to CDC 2025 in Rio today!
If you are also attending, consider joining our workshop:
Physics-Informed Learning for Control: Theory and Practice
Tuesday, December 9
Room Oceania VII
Rio de Janeiro – CDC 2025
Workshop information: sites.google.com/view/2025cdc...
If you are also attending, consider joining our workshop:
Physics-Informed Learning for Control: Theory and Practice
Tuesday, December 9
Room Oceania VII
Rio de Janeiro – CDC 2025
Workshop information: sites.google.com/view/2025cdc...
December 6, 2025 at 3:17 PM
I am traveling to CDC 2025 in Rio today!
If you are also attending, consider joining our workshop:
Physics-Informed Learning for Control: Theory and Practice
Tuesday, December 9
Room Oceania VII
Rio de Janeiro – CDC 2025
Workshop information: sites.google.com/view/2025cdc...
If you are also attending, consider joining our workshop:
Physics-Informed Learning for Control: Theory and Practice
Tuesday, December 9
Room Oceania VII
Rio de Janeiro – CDC 2025
Workshop information: sites.google.com/view/2025cdc...
I will be at the INFORMS this week.
I will be talking about a unifying perspective on Scientific Machine Learning for learning to optimize and learning to control, which is being materialized in the Neuromancer library:
github.com/pnnl/neuroma...
If you want to chat, send me a message :)
I will be talking about a unifying perspective on Scientific Machine Learning for learning to optimize and learning to control, which is being materialized in the Neuromancer library:
github.com/pnnl/neuroma...
If you want to chat, send me a message :)
GitHub - pnnl/neuromancer: Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control. - GitHub - pnnl/neuromancer: Pyto...
github.com
October 26, 2025 at 3:03 PM
I will be at the INFORMS this week.
I will be talking about a unifying perspective on Scientific Machine Learning for learning to optimize and learning to control, which is being materialized in the Neuromancer library:
github.com/pnnl/neuroma...
If you want to chat, send me a message :)
I will be talking about a unifying perspective on Scientific Machine Learning for learning to optimize and learning to control, which is being materialized in the Neuromancer library:
github.com/pnnl/neuroma...
If you want to chat, send me a message :)
Reposted by Jan Drgona
ROSEI is excited to unveil its first ever annual report, highlighting a year of rapid growth, groundbreaking research, and expanding impact! Explore the report and learn more about how the future of sustainable energy starts at JHU 🌎🔋💡 #HopkinsEnergy
Report: energyinstitute.jhu.edu/annual-repor...
Report: energyinstitute.jhu.edu/annual-repor...
October 16, 2025 at 4:00 PM
ROSEI is excited to unveil its first ever annual report, highlighting a year of rapid growth, groundbreaking research, and expanding impact! Explore the report and learn more about how the future of sustainable energy starts at JHU 🌎🔋💡 #HopkinsEnergy
Report: energyinstitute.jhu.edu/annual-repor...
Report: energyinstitute.jhu.edu/annual-repor...
It was an absolute pleasure to give a talk at the Computing and Sustainability Seminar, hosted by MIT Laboratory for Information and Decision Systems (LIDS).
You can watch the recording here: www.youtube.com/watch?v=W9Lo...
You can watch the recording here: www.youtube.com/watch?v=W9Lo...
2025 LIDS Computing and Sustainability Seminar: Jan Drgona (Johns Hopkins University)
YouTube video by MIT Laboratory for Information and Decision Systems (MIT LIDS)
www.youtube.com
October 3, 2025 at 12:49 PM
It was an absolute pleasure to give a talk at the Computing and Sustainability Seminar, hosted by MIT Laboratory for Information and Decision Systems (LIDS).
You can watch the recording here: www.youtube.com/watch?v=W9Lo...
You can watch the recording here: www.youtube.com/watch?v=W9Lo...
NeuroMANCER v1.5.6 is out!
We have four new examples:
1, Learning neural differential algebraic equations via the operator splitting method
2, Learning mixed-integer neural policies via DPC
3, Grid-responsive DPC for building energy systems
4, DPC with prediction preview horizon
We have four new examples:
1, Learning neural differential algebraic equations via the operator splitting method
2, Learning mixed-integer neural policies via DPC
3, Grid-responsive DPC for building energy systems
4, DPC with prediction preview horizon
GitHub - pnnl/neuromancer: Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control. - GitHub - pnnl/neuromancer: Pyto...
github.com
September 26, 2025 at 4:01 PM
NeuroMANCER v1.5.6 is out!
We have four new examples:
1, Learning neural differential algebraic equations via the operator splitting method
2, Learning mixed-integer neural policies via DPC
3, Grid-responsive DPC for building energy systems
4, DPC with prediction preview horizon
We have four new examples:
1, Learning neural differential algebraic equations via the operator splitting method
2, Learning mixed-integer neural policies via DPC
3, Grid-responsive DPC for building energy systems
4, DPC with prediction preview horizon
We’re excited to announce the 2nd Workshop on Physics-Informed Machine Learning at CDC 2025 in Rio de Janeiro on December 9th!
🔗 Workshop details: sites.google.com/view/2025cdc...
📝 Register here: cdc2025.ieeecss.org/registration
(Early registration ends soon!)
🔗 Workshop details: sites.google.com/view/2025cdc...
📝 Register here: cdc2025.ieeecss.org/registration
(Early registration ends soon!)
Home
Abstract
sites.google.com
August 29, 2025 at 3:28 PM
We’re excited to announce the 2nd Workshop on Physics-Informed Machine Learning at CDC 2025 in Rio de Janeiro on December 9th!
🔗 Workshop details: sites.google.com/view/2025cdc...
📝 Register here: cdc2025.ieeecss.org/registration
(Early registration ends soon!)
🔗 Workshop details: sites.google.com/view/2025cdc...
📝 Register here: cdc2025.ieeecss.org/registration
(Early registration ends soon!)
Our paper on "Learning Neural Differential Algebraic Equations via Operator Splitting" was accepted to the IEEE CDC.
If you don't have the time to read the full paper, check the paper summary with the Google Colab example at:
drgona.github.io/NeuralDAEs/
If you don't have the time to read the full paper, check the paper summary with the Google Colab example at:
drgona.github.io/NeuralDAEs/
Learning Neural Differential Algebraic Equations via Operator Splitting
Learning Neural Differential Algebraic Equations via Operator Splitting.
drgona.github.io
July 24, 2025 at 3:08 PM
Our paper on "Learning Neural Differential Algebraic Equations via Operator Splitting" was accepted to the IEEE CDC.
If you don't have the time to read the full paper, check the paper summary with the Google Colab example at:
drgona.github.io/NeuralDAEs/
If you don't have the time to read the full paper, check the paper summary with the Google Colab example at:
drgona.github.io/NeuralDAEs/
NeuroMANCER v1.5.4 is out!
github.com/pnnl/neuromancer
🆕 What's New in v1.5.4
💻 New Examples:
Function Encoders (FE) is an algorithm for learning neural network-based basis functions. Two new examples include the use of FE for function approximation and FE-Neural ODEs.
github.com/pnnl/neuromancer
🆕 What's New in v1.5.4
💻 New Examples:
Function Encoders (FE) is an algorithm for learning neural network-based basis functions. Two new examples include the use of FE for function approximation and FE-Neural ODEs.
GitHub - pnnl/neuromancer: Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control. - GitHub - pnnl/neuromancer: Pyto...
github.com
July 3, 2025 at 5:00 PM
NeuroMANCER v1.5.4 is out!
github.com/pnnl/neuromancer
🆕 What's New in v1.5.4
💻 New Examples:
Function Encoders (FE) is an algorithm for learning neural network-based basis functions. Two new examples include the use of FE for function approximation and FE-Neural ODEs.
github.com/pnnl/neuromancer
🆕 What's New in v1.5.4
💻 New Examples:
Function Encoders (FE) is an algorithm for learning neural network-based basis functions. Two new examples include the use of FE for function approximation and FE-Neural ODEs.
🚀 Less than two weeks to go until the 2025 American Control Conference in Denver, Colorado!
I’m excited for a packed schedule this year—with talks, a tutorial, a workshop, and most importantly, the chance to reconnect with friends and colleagues. 😊
sites.google.com/view/acc-phy...
I’m excited for a packed schedule this year—with talks, a tutorial, a workshop, and most importantly, the chance to reconnect with friends and colleagues. 😊
sites.google.com/view/acc-phy...
LinkedIn
This link will take you to a page that’s not on LinkedIn
lnkd.in
June 25, 2025 at 2:16 PM
🚀 Less than two weeks to go until the 2025 American Control Conference in Denver, Colorado!
I’m excited for a packed schedule this year—with talks, a tutorial, a workshop, and most importantly, the chance to reconnect with friends and colleagues. 😊
sites.google.com/view/acc-phy...
I’m excited for a packed schedule this year—with talks, a tutorial, a workshop, and most importantly, the chance to reconnect with friends and colleagues. 😊
sites.google.com/view/acc-phy...
The spring semester is over, and my new course, "Introduction to Machine Learning and Control for Building Energy Systems," @jhu.edu is now complete.
The material, including lecture slides and code examples, is freely available on GitHub.
github.com/drgona/ML_an...
The material, including lecture slides and code examples, is freely available on GitHub.
github.com/drgona/ML_an...
GitHub - drgona/ML_and_control_buildings_energy
Contribute to drgona/ML_and_control_buildings_energy development by creating an account on GitHub.
github.com
June 12, 2025 at 5:53 PM
The spring semester is over, and my new course, "Introduction to Machine Learning and Control for Building Energy Systems," @jhu.edu is now complete.
The material, including lecture slides and code examples, is freely available on GitHub.
github.com/drgona/ML_an...
The material, including lecture slides and code examples, is freely available on GitHub.
github.com/drgona/ML_an...
Are you planning to attend the American Control Conference 2025 in Denver?
Consider joining our Workshop on Physics-Informed Machine Learning in Control: An Introduction, Opportunities, and Challenges
📅 Date: July 7, 2025
📍 Denver, Colorado
🔗 workshop details sites.google.com/view/acc-phy...
Consider joining our Workshop on Physics-Informed Machine Learning in Control: An Introduction, Opportunities, and Challenges
📅 Date: July 7, 2025
📍 Denver, Colorado
🔗 workshop details sites.google.com/view/acc-phy...
Home
Abstract
sites.google.com
April 25, 2025 at 11:44 AM
Are you planning to attend the American Control Conference 2025 in Denver?
Consider joining our Workshop on Physics-Informed Machine Learning in Control: An Introduction, Opportunities, and Challenges
📅 Date: July 7, 2025
📍 Denver, Colorado
🔗 workshop details sites.google.com/view/acc-phy...
Consider joining our Workshop on Physics-Informed Machine Learning in Control: An Introduction, Opportunities, and Challenges
📅 Date: July 7, 2025
📍 Denver, Colorado
🔗 workshop details sites.google.com/view/acc-phy...
I am seeking a postdoctoral researcher to work on Scientific Machine Learning for Real-Time Decision Making.
📧 Interested candidates should send their CVs to my email: [email protected]
Please see the job description below for more information.
www.linkedin.com/hiring/jobs/...
📧 Interested candidates should send their CVs to my email: [email protected]
Please see the job description below for more information.
www.linkedin.com/hiring/jobs/...
LinkedIn Login, Sign in | LinkedIn
Login to LinkedIn to keep in touch with people you know, share ideas, and build your career.
www.linkedin.com
April 18, 2025 at 3:10 PM
I am seeking a postdoctoral researcher to work on Scientific Machine Learning for Real-Time Decision Making.
📧 Interested candidates should send their CVs to my email: [email protected]
Please see the job description below for more information.
www.linkedin.com/hiring/jobs/...
📧 Interested candidates should send their CVs to my email: [email protected]
Please see the job description below for more information.
www.linkedin.com/hiring/jobs/...
NeuroMANCER v1.5.3 is out!
github.com/pnnl/neuroma...
What is new?
🤖 NeuroMANCER-GPT Assistant
🐍 Python 3.11 Version Support
🏫 Building Control Comparison Example: Safe Reinforcement Learning vs Differential Predictive Control
💻 Improved Node Class
github.com/pnnl/neuroma...
What is new?
🤖 NeuroMANCER-GPT Assistant
🐍 Python 3.11 Version Support
🏫 Building Control Comparison Example: Safe Reinforcement Learning vs Differential Predictive Control
💻 Improved Node Class
GitHub - pnnl/neuromancer: Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control. - GitHub - pnnl/neuromancer: Pyto...
github.com
February 26, 2025 at 9:59 PM
NeuroMANCER v1.5.3 is out!
github.com/pnnl/neuroma...
What is new?
🤖 NeuroMANCER-GPT Assistant
🐍 Python 3.11 Version Support
🏫 Building Control Comparison Example: Safe Reinforcement Learning vs Differential Predictive Control
💻 Improved Node Class
github.com/pnnl/neuroma...
What is new?
🤖 NeuroMANCER-GPT Assistant
🐍 Python 3.11 Version Support
🏫 Building Control Comparison Example: Safe Reinforcement Learning vs Differential Predictive Control
💻 Improved Node Class
Reposted by Jan Drgona
Our final #EWeek2025 post highlights Ján Drgoňa, who recently joined Hopkins as an associate professor in the Department of Civil and Systems Engineering! He was asked "How could your research make a future impact in the fight against climate change?" #HopkinsEnergy
February 21, 2025 at 5:01 PM
Our final #EWeek2025 post highlights Ján Drgoňa, who recently joined Hopkins as an associate professor in the Department of Civil and Systems Engineering! He was asked "How could your research make a future impact in the fight against climate change?" #HopkinsEnergy
Reposted by Jan Drgona
Internship opportunity: Spatiotemporal Graph applications for Smart Buildings⚡⚡⚡ working closely with me, starting in early 2025. Considering applying or/and sharing this with your network please. Apply here: forms.gle/N3kwFxM3yEhS... LinkedIn ad here: www.linkedin.com/feed/update/...
December 21, 2024 at 7:41 PM
Internship opportunity: Spatiotemporal Graph applications for Smart Buildings⚡⚡⚡ working closely with me, starting in early 2025. Considering applying or/and sharing this with your network please. Apply here: forms.gle/N3kwFxM3yEhS... LinkedIn ad here: www.linkedin.com/feed/update/...
Reposted by Jan Drgona
New ROSEI researcher Q&A with @drgona.bsky.social just went live! He discussed how a project as an undergraduate shaped his passion for energy-efficient building controls, and why joining the Hopkins energy community was a "no-brainer." #HopkinsEnergy
Story: energyinstitute.jhu.edu/rosei-resear...
Story: energyinstitute.jhu.edu/rosei-resear...
ROSEI Researcher Q&A: Ján Drgoňa - Johns Hopkins - Ralph O’Connor Sustainable Energy Institute
This article is part of a series featuring Q&As with Ralph O’Connor Sustainable Energy Institute (ROSEI)-affiliated researchers. Next up is Ján...
energyinstitute.jhu.edu
January 3, 2025 at 4:15 PM
New ROSEI researcher Q&A with @drgona.bsky.social just went live! He discussed how a project as an undergraduate shaped his passion for energy-efficient building controls, and why joining the Hopkins energy community was a "no-brainer." #HopkinsEnergy
Story: energyinstitute.jhu.edu/rosei-resear...
Story: energyinstitute.jhu.edu/rosei-resear...
In our latest NeuroMANCER release, we have two new examples demonstrating the use of Finite Basis Kolmogorov-Arnold Networks (FBKANs) for function approximation.
1D FBKAN example
colab.research.google.com/github/pnnl/...
#Neuromancer, #PNNL, #SciML, #KANs
1D FBKAN example
colab.research.google.com/github/pnnl/...
#Neuromancer, #PNNL, #SciML, #KANs
Google Colab
colab.research.google.com
November 25, 2024 at 5:02 PM
In our latest NeuroMANCER release, we have two new examples demonstrating the use of Finite Basis Kolmogorov-Arnold Networks (FBKANs) for function approximation.
1D FBKAN example
colab.research.google.com/github/pnnl/...
#Neuromancer, #PNNL, #SciML, #KANs
1D FBKAN example
colab.research.google.com/github/pnnl/...
#Neuromancer, #PNNL, #SciML, #KANs