Clayton Easter, Ph.D.

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Background in mechanical engineering and material science. Extensive experience in development and full-scale manufacturing environments, foreign and domestic. Developed novel products for military and private sector applications. Highly experienced in DOE, FA, metrology, analysis, and modeling and simulation of mechanical and thermal systems.

Ph.D. in Engineering (2010)

B.S. in Mechanical Engineering (2005)

Experience

Honeywell

Manufacturing Engineer

  • Senior engineer facilitating a MEMS sensors manufacturing line (pressure, flow, humidity sensors).
  • Responsible for researching and modeling/simulating new processes for semiconductor manufacturing (front-end and back-end).
  • Developed new metrology/inspection methods including material thickness/uniformity, strength, surface characterization and defect detection. Lead metrology engineer for all manufacturing.
  • Developed empirical models for optically characterizing novel materials developed in-house.
  • Advised management on the investment in capital equipment (>$1mil).
  • Authored and qualified manufacturing recipes for dozens of tools across all products, including fabrication, metrology and inspection. Responsible for fab-wide metrology calibration and maintenance.
  • Trained and responsible for overseeing ~20 personnel, including engineers, techs and operators.
  • Manufacturing consultant for new product development and MES (IT) teams.

DLP @ Texas Instruments

Process Development Engineer, WLP Assembly Group

  • Senior engineer for development of the digital-mirror-device (DMD).
  • Responsible for modeling/simulating new electronics packaging processes focusing on mechanical strength, thermal and surface characterization.
  • Experienced in most back-end microelectronics package processing (bond, singulation, die attach, wire bond, encapsulation, parametric test).
  • Authored, qualified and transferred to production new tools/recipes for various processes. Responsible for training techs/operators on new processes and tools.
  • Advised management on new purchases for capital equipment and materials, as well as facilitating business relationships with new and established vendors/suppliers.

U.S. Air-Force (Radiance Defense Technologies)

Graduate Researcher

  • Developed prototype piezoelectric sensors for U.S. Air Force applications.
  • Responsible for concept, design, modeling/simulation, mask layout, front-end and back-end fabrication, and device testing.
  • Developed spin-coating and annealing techniques for novel piezoelectric ceramic thin-films (PZT and PZT nanoparticle composites).
  • Delivered a proof-of-concept according to military requirements.
  • Publications included in the Journal of Microelectromechanical Systems (JMEMS) and ASME International Mechanical Engineering Congress and Exhibition (IMECE) 2006, 2007 and 2008.

American Journal Experts (AJE)

Academic Editor (contracted, ongoing)

  • Reviewed and edited academic manuscripts including but not limited to journal publications, dissertations and academic letters.
  • Edited manuscripts for native and non-native English speakers originating from ~20 different nations, covering a vast range of scientific and engineering fields of study.

Accdon

Scientific Editor (contracted, ongoing)

  • Reviewed and edited academic manuscripts mainly intended for journal publication.
  • Advised manuscript authors on the ideas and evidence presented, suggesting improvements as needed for both scientific content and grammatical structure.
Skills
  • FMEA, DOE, FEA, GR&R, SPC, FDC, 6-sigma, technical writing and communication.
  • AutoCAD (Mask design), Solidworks (mechanical modeling and assemblies), Coventor, COMSOL, ANSYS, SAP, MES, Adobe Creator, Microsoft (Office, Windows), LaTeX, JMP, Minitab, MathCAD, Linux/Unix, Github, VirtualBox/VMWare, Docker, SQL, general computer and network troubleshooting.
  • Programming in Python, Ruby, Javascript, Haskell, g-code and shell scripting; ML with pytorch and tensorflow.
  • Experience with operating, training and fine-tuning large language models (LLMs) for local deployment.