I am a professor in Mechanical Engineering and Director of the Institute for Computational Mathematical Engineering (

I received my PhD in Italy from the Politecnico di Bari in 2005 and have worked for several years at the Center for Turbulence Research (NASA Ames & Stanford) before joining the faculty at Stanford in 2007. Since 2014 I am the Director of the PSAAP Center at Stanford, funded by the US Department of Energy: a $20M research Center focused on multiphysics simulations, uncertainty quantification and exascale computing (

In 2010, I received the Presidential Early Career Award for Scientists and Engineers (PECASE) award from the President Obama. in the last couple of years, I received best paper awards from AIAA, ASME IMECE and Turbo Expo Conferences.

Over the years, my interests in research and teaching have touched many topics, but always revolved around the use of computing and data to solve problems in energy, biomedicine, aerodynamics, design.

Administrative Appointments

  • Director, ICME Institute for Computational and Mathematical Engineering (2018 - Present)
  • Visiting Professor, Ecole Centrale Paris (2016 - 2016)
  • Director, Exascale Computaing Engineering Center - PSAAP II (2014 - Present)
  • Visiting Professor, Technical University of Munich (2011 - 2011)
  • Director, TFSA Thermal and Fluid Sciences Industrial Affiliates Program (2010 - 2018)
  • Professor, Mechanical Engineering Department, Stanford (2007 - Present)
  • Postdoctoral Fellow, Mechanical Engineering Department, Stanford (2005 - 2007)
  • Research Engineer, CTR, Center for Turbulence Research (1998 - 2005)
  • Research Scientist, CIRA, Italian Center for Aerospace Research (1993 - 1998)

Honors & Awards

  • TUM Ambassador, Technical University of Munich (2018)
  • ASME IMECE Best Paper Award, ASME (2017)
  • Jefferson Goblet Award, Best Paper, AIAA (2017)
  • Turbo Expo Best Paper Award, ASME (2016)
  • William R. and Inez Kerr Bell Faculty Scholar, Stanford University (2014)
  • Gold Medal Honoring Italians Abroad, City of Piano di Sorrento (Italy) (2013)
  • Presidential Early Career Award for Scientists and Engineers, The White House & US Department of Energy (2010)
  • Humboldt Fellowship, Humboldt Research Fellowship Program (2009)
  • Terman Fellow, Stanford University (2007)

Boards, Advisory Committees, Professional Organizations

  • Associate Editor, Computers and Fluids (2018 - Present)
  • Associate Editor, Flow, Turbulence & Combustion (2015 - Present)
  • Associate Editor, Journal of Computational Physics (2014 - Present)
  • Co-Chair, APS Division of Fluid Dynamics Conference (2014 - 2014)
  • AdCom, Advisory Committee to the Chair, Mechanical Engineer Department, Stanford (2013 - 2018)
  • Associate Editor, ASME Applied Mechanics Review (2013 - 2017)
  • General Chair (elected), AIAA XVI Non-Deterministic Approaches (2013 - 2013)
  • Technical Chair (elected), AIAA XV Non-Deterministic Approaches (2013 - 2013)
  • Associate Fellow, AIAA (2012 - Present)
  • Member, SIAM, ASME, AIAA, APS (2010 - Present)
  • Non-Deterministic Approaches Technical Committee, AIAA (2010 - Present)
  • Member of the Board of Directors, Cascade Technologies Inc (2000 - Present)

Program Affiliations

  • Institute for Computational and Mathematical Engineering (ICME)

Professional Education

  • PhD, Politecnico di Bari, Italy, Mechanical Engineering (2005)
  • MS, University di Napoli, Italy, Aeronautical Engineering (1993)
  • BS, University di Napoli, Italy, Aeronautical Engineering (1992)


  • ES Shaqfeh, G Iaccarino, P Shah. "United States Patent App. 15/435,112 Methods and Systems for Simulating Nanoparticle Flux", Leland Stanford Junior University, Sep 14, 2017

Current Research and Scholarly Interests

Computing and data for energy, health and engineering

Challenges in energy sciences, green technology, transportation, and in general, engineering design and prototyping are routinely tackled using numerical simulations and physical testing. Computations barely feasible two decades ago on the largest available supercomputers, have now become routine using turnkey commercial software running on a laptop. Demands on the analysis of new engineering systems are becoming more complex and multidisciplinary in nature, but exascale-ready computers are on the horizon. What will be the next frontier? Can we channel this enormous power into an increased ability to simulate and, ultimately, to predict, design and control? In my opinion two roadblocks loom ahead: the development of credible models for increasingly complex multi-disciplinary engineering applications and the design of algorithms and computational strategies to cope with real-world uncertainty.
My research objective is to pursue concerted innovations in physical modeling, numerical analysis, data fusion, probabilistic methods, optimization and scientific computing to fundamentally change our present approach to engineering simulations relevant to broad areas of fluid mechanics, transport phenomena and energy systems. The key realization is that computational engineering has largely ignored natural variability, lack of knowledge and randomness, targeting an idealized deterministic world. Embracing stochastic scientific computing and data/algorithms fusion will enable us to minimize the impact of uncertainties by designing control and optimization strategies that are robust and adaptive. This goal can only be accomplished by developing innovative computational algorithms and new, physics-based models that explicitly represent the effect of limited knowledge on the quantity of interest.

Multidisciplinary Teaching

I consider the classical boundaries between disciplines outdated and counterproductive in seeking innovative solutions to real-world problems. The design of wind turbines, biomedical devices, jet engines, electronic units, and almost every other engineering system requires the analysis of their flow, thermal, and structural characteristics to ensure optimal performance and safety. The continuing growth of computer power and the emergence of general-purpose engineering software has fostered the use of computational analysis as a complement to experimental testing in multiphysics settings. Virtual prototyping is a staple of modern engineering practice! I have designed a new undergraduate course as an introduction to Computational Engineering, covering theory and practice across multidisciplanary applications. The emphasis is on geometry modeling, mesh generation, solution strategy and post-processing for diverse applications. Using classical flow/thermal/structural problems, the course develops the essential concepts of Verification and Validation for engineering simulations, providing the basis for assessing the accuracy of the results.


  • PSAAP Project, Stanford

    PSAAP Stands for Predictive Science Academic Alliance Program; this is a large research project funded by the US Department of Energy and the National Nuclear Security Administration (



2018-19 Courses

All Publications