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MP
Michael Paleos
Mid-level Mechanical Engineering Researcher specializing in HPC simulation and ML surrogates
Pittsburgh, PAGraduate Student Researcher - NASA Transformational Tools & Technologies (TTT) project3 years experienceMid-LevelAerospace & DefenseManufacturingAdditive Manufacturing
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About
At Pitt, built and productionized a deep-learning (LSTM) surrogate thermal solver integrated into the ExaCA simulation pipeline for NASA partner teams, enabling same-day parametric studies (16x speedup, ~5% error) with guardrails and FEM-based validation. Presents this work at major conferences (SFF 2023, TMS 2024) and emphasizes practical, end-to-end workflows and reliability over paper accuracy.
Experience
Graduate Student Researcher - NASA Transformational Tools & Technologies (TTT) projectUniversity of Pittsburgh
Master’s Thesis Research InternHellenic Research Center for Metals
Research InternHellenic Research Center for Metals
SecretaryAmerican Hellenic Educational Progressive Association (AHEPA)
Peer ReviewerAdditive Manufacturing Journal
Team LeadGreenTech Challenge
Education
University of Pittsburghmaster, Mechanical Engineering (2025)
National Technical University of Athensmaster, Materials Engineering (2022)
Key Strengths
- Took an ML surrogate from research prototype to production use by NASA partner teams
- Integrated surrogate into existing ExaCA workflow to minimize user friction and drive adoption
- Delivered major performance gains (16x faster simulations) with quantified accuracy (~5% error)
- Built reliability guardrails with validation checks and safe fallback to full-fidelity FEM solver
- Strong real-time troubleshooting via staged logging/diagnostics to isolate failures quickly
- Applies domain knowledge to catch subtle issues missed by generic metrics (cooling-rate regime affecting nucleation); improved model with weighted loss and targeted diagnostics
- Effective technical communication to mixed audiences; leads with outcomes and practical workflow
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