My name is Mehdi Ghasemi (in Persian "مهدی قاسمی"). I was born in Iran - Tehran in February 1980 and grew up there. I graduated from the Amirkabir University of Technology with a bachelor degree, August 2002, then finished my masters degree in Tarbiat Modares University, August 2004. After graduating from my master's program I was working for IPM as a researcher between April 2004 and March 2005, then more than three years for Omigaman as a web developer and analyst. In January 2006, I married my lovely wife, Bahareh Esfahbod.
I received my Ph.D. in the University of Saskatchewan, Department of Mathematics and Statistics under the supervision of Professor S. Kuhlmann (Universität Konstanz) and Professor M. Marshall in August 2012.
I was a postdoctoral researcher at the University of Konstanz, Germany, Nanyang Technological University, Singapore, and a MITACS fellow at the University of Saskatchewan from September 2012 to August 2017.
Currently, I am employed by the Government of Saskatchewan, Canada, as a data scientist and affiliated with the University of Saskatchewan as an adjunct professor.
This is a link to my latest Curriculum Vitæ.
The followings are some of the major scientific libraries I have implemented for python.
- M. Ghasemi, M. Infusino, S. Kuhlmann, and M. Marshall, Moment Problem for Symmetric Algebras of Locally Convex Spaces, IEOT 90(3), 29, (2018).
- M. Alaghmandan, M. Ghasemi, Seminormed ∗-subalgebras of l∞(X), JMAA 455(1), 212-220, (2017).
- M. Ghasemi, S. Kuhlmann, and M. Marshall, Moment Problem in Infinitely Many Variables, Israel J. Math 212(2), 1012, (2016).
- M. Ghasemi and M. Marshall, Lower bounds for a polynomial on a basic closed semialgebraic set using geometric programming, arXiv:1311.3726 [math.OC].
- M. Ghasemi, S. Kuhlmann, and M. Marshall, Application of Jacobi’s Representation Theorem to locally multiplicatively convex topological R-Algebras, J. Funct. Anal. 266:2 1041-1049, (2014), DOI:10.1016/j.jfa.2013.09.001.
- M. Ghasemi, J. B. Lasserre, and M. Marshall, Lower bounds on the global minimum of a polynomial, Comput. Optim. Appl. 56(1) (2013), DOI:10.1007/s10589-013-9596-x.
- M. Ghasemi and S. Kuhlmann, Closure of the cone of sums of 2d-powers in real topological algebras, J. Funct. Anal. 264:1 413-427, (2013), DOI:10.1016/j.jfa.2012.10.018.
- Ph.D. Thesis, Polynomial Optimization and Moment Problem, University of Saskatchewan.
- M. Ghasemi, M. Marshall, and S. Wagner, Closure of the cone of sums of 2d-powers in certain weighted l1- seminorm topologies, Canad. Math. Bull. 57 289-302 (2014), DOI:10.4153/CMB-2012-043-9.
- M. Ghasemi and M. Marshall, Lower bounds for polynomials using geometric programming, SIAM J. Optim. 22(2) 460-473, (2012), DOI:10.1137/110836869.
- M. Ghasemi, S. Kuhlmann, and E. Samei, The moment problem for continuous positive semidefinite linear functionals, Arch. Math. 100 43-53, (2012), DOI:10.1007/s00013-012-0460-5.
- M. Ghasemi and M. Marshall, Lower bounds for a polynomial in terms of its coefficients, Arch. Math. 95 343-353, (2010), DOI:10.1007/s00013-010-0179-0.
- M. Ghasemi and M. Moniri, Beatty sequences and the arithmetical hierarchy, LNL. 26, Logic in Tehran, ASL 126-133, (2006).
- M.Sc. Thesis, Integer Parts of Real Arithmetic Progressions and Computability, Tarbiat Modares Uni. Supervisor: Prof. M. Moniri.
- E. Hesamifard, H. Takabi, M. Ghasemi, R.N. Wright, Privacy-preserving Machine Learning as a Service, Proceedings on Privacy Enhancing Technologies (3), 123-142, (2018).
- E. Hesamifard, H. Takabi, M. Ghasemi, C. Jones, Privacy-preserving Machine Learning in Cloud, Proceedings of the 2017 on Cloud Computing Security Workshop, 39-43, (2017).
- A. K. Dalai, S. Shahkarami, M. Ghasemi and J. Soltan, CO2 Adsorption on Activated Carbon: Equilibrium, and Kinetics of Fixed-Bed Isothermal Adsorption, submitted.
- E. Hesamifard, H. Takabi, M. Ghasemi, CryptoDL: Towards Deep Learning over Encrypted Data, Annual Computer Security Applications Conference (ACSAC 2016), LA, CA (2016).
- E. Hesamifard, H. Takabi, M. Ghasemi, Privacy Preserving Multi-party Machine Learning with Homomorphic Encryption, 29th Annual Conference on Neural Information Processing Systems (NIPS), (2016).