NSF HAMMER Engineering Research Center

I thought you'd enjoy this video of the desktop milling machine we've developed to support TechAMP from the MIT Department of Mechanical Engineering (MechE) and the NSF HAMMER Engineering Research Center. Great work by my graduate students Tyler Woodard and John Greene! https://lnkd.in/dc9aWE6U

I am thrilled to announce that I’ve been selected for the NSF Research Experience for Undergraduates (REU) at University of Wisconsin-Eau Claire this summer! I’ll be working with Dr. Ying Ma on a project focused on machine learning-enabled design of amorphous materials for lithium-ion batteries. Using ML force fields, we’ll model and optimize materials like Li₃OCl and SiO₂ to improve battery performance and efficiency, especially for applications like electric vehicles. Huge thank you to Dr. Ying Ma for the opportunity and to Dr. Rahul Gomes for all the support throughout the application process. I am excited to grow in the field of computational materials science, learn from amazing mentors, and contribute to meaningful research! #NSFREU #MaterialsScience #HPC

Excited to share our latest publication on real-time decision-making for Digital Twins in additive manufacturing, powered by data-driven and physics-based Model Predictive Control (MPC) and a time-series deep neural network called TiDE. The method enables • One-shot multi-step-ahead prediction of melt pool temperature and depth • Proactive control of laser power for quality assurance • Constraint handling to minimize defects like porosity in Directed Energy Deposition (DED) This work showcases the capability of machine learning in modeling complex systems which facilitates real-time decision making, bringing us closer to intelligent, self-adaptive manufacturing. Shout out to all the co-authors @Yi-Ping Chen, Vispi Karkaria, Ying-Kuan (Rick) Tsai-Kuan Tsai, @Faith Rolark, @Daniel Quispe, @Robert X. Gao and Jian Cao, for the collaboration, and the funding support from NSF HAMMER ERC https://hammer.osu.edu/. Read the paper here: https://lnkd.in/gsczp74Z. #DigitalTwin #AdditiveManufacturing #MPC #DeepLearning #SmartManufacturing #AIControl 

🏆 From hackathon winner to production-ready in record time! Just took 3rd place at Make OHI/O 2025 with Strain Seer - a tool that solves the no.1 problem with research software: sustainability. (👥 Keming's Strain Seer is the coding part of Team 40 at Make OHI/O 2025. Huge thanks to my partner Jalen Manu's non-coding work here: https://lnkd.in/e3N_kX2k) 🚀 Most hackathon projects die after the demo. Mine was just getting started! Built a fully functional app with live deployment in just 12 hours: https://lnkd.in/e-3rJUrX (wake it up if sleeping 😴) or view the demo PDF 🏞️ at https://lnkd.in/ehneGVZN 💎 What makes Strain Seer stand out: - 🐳 Cross-platform Docker images for both Intel and Apple devices - 📚 Researcher-friendly onboarding guide and dev docs - ✅ 100% test coverage with automated CI/CD - ❤️ MIT-licensed and actively maintained 🐙 Be sure to check out and star ⭐ the GitHub repo at https://lnkd.in/eK-dKgQU and use it as template for your next project! 💡 Working alongside brilliant minds at NSF HAMMER Engineering Research Center showed me what researchers really need. Special thanks to Dr. Glenn Daehn and Alex Bandar whose insights shaped my approach to building tools that don't just work today, but continue working tomorrow. 👷♀️ The real engineering challenge isn't just building something cool—it's creating something reliable that others can trust, depend, and build upon. 🤝 What's your approach to creating sustainable software? Let's connect! #SustainableSoftware #SoftwareEngineering #Docker #OpenSource #GitHub #ContinuousIntegration #ContinuousDelivery #ResearchTools #CrossPlatform #MakeOHIO #OhioState