With artificial intelligence poised to assist in profound scientific discoveries that will change the world, Cornell is leading a new $11.3 million center focused on human-AI collaboration that uses... Read more about New center merges math, AI to push frontiers of science
Dr. Bouklas joined the Cornell MAE faculty in January 2018. Prior to that, he was a postdoctoral researcher at the Institute of Mechanical Engineering at EPFL, Switzerland, following a postdoctoral appointment at the Oden Institute, University of Texas at Austin. He received his PhD in Engineering Mechanics from the Aerospace Engineering and Engineering Mechanics department at the University of Texas at Austin in 2014, and obtained his Diploma in Mechanical Engineering from the Aristotle University of Thessaloniki, Greece in 2008.
Dr. Bouklas' research focuses in the fields of theoretical and computational solid mechanics. Developing theoretical frameworks and advanced computational methods, he aims to improve the fundamental understanding of materials and structures, and enhance the predictive capabilities in relevant engineering applications. He is interested in the fundamental study of soft materials, active materials and biomaterials, fracture and instabilities, as well as multiscale modeling in coupled multi-physical systems. A recent thrust in his lab targets machine learning (ML)-enabled constitutive models and solutions of PDEs using a combination of data and guiding physical principles.
Mechanics of materials, solid mechanics, continuum mechanics and thermodynamics, computational mechanics
- Fuhg, J.N. and Bouklas, N., 2022. On physics-informed data-driven isotropic and anisotropic constitutive models through probabilistic machine learning and space-filling sampling. Computer Methods in Applied Mechanics and Engineering, 394, p.114915.
- Fontenele, F.F., Andarawis-Puri, N., Agoras, M. and Bouklas, N., 2022. Fiber plasticity and loss of ellipticity in soft composites under non-monotonic loading. International Journal of Solids and Structures, p.111628.
- Kadeethum, T., O’Malley, D., Fuhg, J.N., Choi, Y., Lee, J., Viswanathan, H.S. and Bouklas, N., 2021. A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks. Nature Computational Science, 1(12), pp.819-829.
- Mulderrig, J., Li, B. and Bouklas, N., 2021. Affine and non-affine microsphere models for chain scission in polydisperse elastomer networks. Mechanics of Materials, 160, p.103857.
- Kim, J., Mailand, E., Ang, I., Sakar, M.S. and Bouklas, N., 2021. A model for 3D deformation and reconstruction of contractile microtissues. Soft Matter, 17(45), pp.10198-10209.
- Li, B. and Bouklas, N., 2020. A variational phase-field model for brittle fracture in polydisperse elastomer networks. International Journal of Solids and Structures, 182, pp.193-204.
Selected Awards and Honors
- AFOSR Young Investigator Program award, 2022
- Presenter Fellowship, U.S. National Committee for Theoretical and Applied Mechanics (USNC/TAM) , 2021
- Greek Diaspora Fellowship Program, 2019
- Travel Award from the Center for Mechanics of Solids, Structures and Materials, University of Texas at Austin 2014
- Hellenic Professional Society of Texas Scholarship 2014
- John & Mary Wheeler Endowed Graduate Fellowship in Engineering, UT Austin 2012
- Cockrell School of Engineering Graduate Scholarship, UT Austin 2009
- B.S. & M.Eng. Aristotle University of Thessaloniki, Greece, 2008
- Ph.D. University of Texas at Austin, 2014