Aditya Balu
Data Scientist • Iowa State University

1111 Woi Rd
0035A Roy J Carver Colab
Ames, IA 50014
Email: baditya@iastate.edu
I am a Data Scientist at Translational AI Center @ Iowa State University, specializing in deep learning and GPU algorithms for Computer Aided Engineering. My research interests span the intersection of machine learning, high-performance computing, and computational mechanics.
Research Interests
My research focuses on developing novel methodologies that enhance traditional engineering workflows through artificial intelligence and high-performance computing. Key areas include:
- Physics-informed Machine Learning: Integrating domain knowledge with data-driven approaches
- GPU Computing: Acceleration of computational methods for engineering applications
- Neural PDE Solvers: Data-driven solutions for partial differential equations
- Decentralized Learning: Communication-efficient distributed machine learning
- Scientific Machine Learning: Applying ML to improve scientific computations
Current Position
- Data Scientist, Translational AI Center (TrAC), Iowa State University
Education
- Ph.D. in Mechanical & Computer Engineering (Co-major), Iowa State University (2016-2020)
- Dissertation: Deep Learning & GPU algorithms for Computer Aided Engineering
- Advisors: Prof. Adarsh Krishnamurthy & Prof. Soumik Sarkar
- B.E. (Hons.) in Mechanical Engineering, Birla Institute of Technology and Science, Pilani (2010-2014)
Professional Experience
Prior to my current academic roles, I worked as:
- Postdoctoral Research Associate, Iowa State University (May 2020 - Dec 2021)
- Machine Learning Co-op, Ansys Inc., Pittsburgh, PA (July 2018 - Dec 2018)
- Design Engineer - I, FMC Technologies (now TechnipFMC), Hyderabad, India (July 2014 - July 2016)
I currently have over 1500 citations and an h-index of 18. My work spans across machine learning for computational mechanics, deep learning for engineering applications, and GPU acceleration of scientific computing algorithms.
Check out my research projects (To be updated), publications, and CV for more details!
news
Mar 10, 2024 | New NSF Grant on AI-enabled Atomic Force Microscopy |
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Feb 15, 2024 | Our paper “DIMAT: Decentralized Iterative Merging-and-Training for Deep Learning Models” accepted to CVPR 2024! |
Jan 20, 2024 | Excited to announce our NSF EAGER award on “LLM-Powered Framework for G-Code Comprehension and Retrieval” ($200,000)! |
Dec 05, 2023 | Our paper on “Neural PDE Solvers for Irregular Domains” accepted to Computer-Aided Design journal! |
Oct 15, 2023 | Our team was a finalist in the NSF NAMRC Bluesky Manufacturing Competition for our work on “Conversational AI as a game-changer in manufacturing”! |
selected publications
- Slice-100K: A multimodal dataset for extrusion-based 3D printingIn Neural Information Processing Systems (NeurIPS), 2024Datasets and Benchmarks Track