Journal of Machine Learning for Modeling and Computing

Journal of Machine Learning for Modeling and Computing JMLMC publishes the latest research in deep learning, engineering, AI, neural networks and more!

The Journal of Machine Learning for Modeling and Computing provides researchers with a rigorous, peer-reviewed forum ded...
07/20/2026

The Journal of Machine Learning for Modeling and Computing provides researchers with a rigorous, peer-reviewed forum dedicated exclusively to the study of machine learning methods in scientific modeling and computation. Indexed in major databases including Clarivate, Scopus, EBSCO, and Google Scholar, the Journal of Machine Learning for Modeling and Computing ensures broad discoverability for work spanning real-world system modeling, novel numerical strategies, and the mathematical foundations of machine learning. Authors benefit from open access publishing options that maximize readership and citation potential across both the machine learning and scientific computing communities.

Publish with us: www.begellhouse.com/JMLMC

Editor-in-Chief: Dongbin Xiu (The Ohio State University)

🔬 New from Thermopedia: Deviant Density Enhancement in Nanofluids challenges the classical mixture rule for predicting n...
07/15/2026

🔬 New from Thermopedia: Deviant Density Enhancement in Nanofluids challenges the classical mixture rule for predicting nanofluid density, revealing that colloidal nanoparticle suspensions behave as three-phase systems rather than the conventional two-phase model.

Authored by Anusree Sen and Debjyoti Banerjee (Texas A&M University), this work introduces the "nano-fin effect" (nFE), a compressed interfacial layer of solvent molecules surrounding each nanoparticle that drives anomalous property enhancements, along with the newly proposed Sen-Banerjee number (SB), a dimensionless parameter for predicting when interfacial effects dominate nanofluid behavior. These insights carry implications for radiation shielding, industrial fluid pumping, and corrosion mitigation.

Anusree Sen's research on nanofluids extends beyond density modeling and into corrosion science: she recently won the Best Poster Award at the American Society of Thermal and Fluids Engineers (ASTFE)'s Conference for her poster, "Electrochemical Corrosion Response of Aluminum Substrates Exposed to Silica Nanofluids and Additives (Surfactant)," a well-deserved recognition of her work. 🏆

Read the full article to explore the nano-fin effect and the deviant density formulation:
đź”— https://thermopedia.com/content/10483/?utm_medium=email&utm_source=ctct

Where will you publish your next engineering breakthrough?Choosing the right journal is one of the most important decisi...
07/10/2026

Where will you publish your next engineering breakthrough?

Choosing the right journal is one of the most important decisions you'll make as a researcher. Beyond finding a journal that fits your work, it's important to understand the submission process, publishing options, and how you’ll be supported before, during, and after the publishing process.

Join us on Tuesday, July 22 for a free webinar, where we’ll dive deep into Begell House, Inc. Publishers's engineering publishing program.

“Publishing Your Engineering Research with Begell House: A Practical Guide”

đź“… Wednesday, July 22, 2026
🕛 12:00–1:00 PM EDT (New York)

REGISTER: https://us02web.zoom.us/webinar/register/WN_-U1WVwTGQa-ZvZEL0uNTig

Whether you're an early-career researcher preparing your first manuscript or an experienced author exploring new publishing partners, this is a great opportunity to learn about our trusted publications and why authors choose to publish Begell House Journals.

Even if you can’t join us live, register anyway! We’ll send you the recording and presentation slides after the event.

Our publications span thermal-fluids engineering, energy systems, computational sciences, aerospace, materials, chemical engineering, and interdisciplinary fields. Learn more at: https://www.begellhouse.com/

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