Commencement of seminar series - inaugural lecture by the ERA chair Prof V. Harmandaris

Date: 5 November 2020

Title: Computational Science and Engineering of Complex Materials: The SimEA ERA Chair Initiative


The ERA Chair project “Modeling and Simulation for Engineering Applications” (SimEA), funded by EU, refers to a new initiative at CaSToRC of CyI, regarding the challenges and opportunities arising when advanced computing and data science are utilised to solve engineering problems. The research team, led by ERA Chair Prof. V. Harmandaris, will work on the development of mathematical and computational methodologies for complex molecular systems, with important applications in nano/bio technology.

The team will pursue a program of research excellence and innovation by applying and developing mathematical and computational methods, including multiscale modeling, physics-based and/or data-driven molecular models, uncertainty quantification, and machine learning methods, integrated with High-Performance Computing, for tackling challenging problems in different application areas related to Computational Science and Engineering.  Examples include a broad range of systems/materials of great scientific and technological interest, such as nanocomposites, polymers, graphene-based nanostructured materials, proteins, and biomolecular systems.

In this inaugural seminar of the seminar series under the SimEA, we will give an overview of the main objectives and research topics of the SimEA. Our vision is to create a regional and national hub for advanced computing and its applications at CyI, collaborating with academia and the private sector, across several research areas, such as: (a) Multi-scale Modelling and Simulations of Nanostructured Materials, (b) Data-driven Machine Learning Approaches for Modelling Across Scales, (c) Modelling of Biomolecular Systems for Biotechnology Applications, (d) Statistical Inference for Uncertainty Quantification and Model Selection.



Webinar: Bottom-up Approach - From Model Molecular Systems to Complex Polymer Materials
by Dr. Petra Bacova, Post-doctoral researcher, SimEA project, The Cyprus Institute

Date: Tuesday, 24 November 2020


Following the lecture of Prof. Harmandaris, a postdoctoral SimEA fellow Dr. Petra Bacova will shed further light on the computational design of advanced materials. The main focus will be on the complex polymer materials, addressing three main questions: WHY these materials are interesting, WHAT their composition is and HOW we can model their properties computationally.





Presentations by our PhD students who have recently joined the SimEA research team. Here, they present their MSc research projects and give an overview of the research that they will be conducting during their PhD at The Cyprus Institute.

Date: Tuesday, 8 December 2020


The Optimization Algorithm in Machine Learning
by Eleftherios Christofi, PhD Student, SimEA project, The Cyprus Institute In this weminar


The last two decades have marked a rapid and significant growth of the Artificial Intelligence field. Deep learning using artificial neural networks became an essential tool for a vast number of applications fields. The structure of deep learning relies on basic concepts from several mathematical fields, such as linear algebra, calculus, optimization, statistics. This presentation is an introduction to the mathematical background of deep learning. In particular, we focus on the optimization algorithm widely used, namely the stochastic gradient descent. We study and compare the behaviour of different variants of this algorithm under various circumstances and summarize their strengths and weaknesses. The goal of this presentation is to provide the viewer with the knowledge to comprehend the training procedure of a neural network.


Development of an algorithm and software for computing Pareto fronts with a gradient-based method, with applications in aerodynamics
by Nikolaos Patsalides, PhD Student, SimEA project, The Cyprus Institute


This diploma thesis proposes, develops and evaluates a low-cost algorithm and software for computing Pareto fronts with a gradient-based method, i.e. a method that uses the gradient of the cost functions, by implementing the algorithm in aerodynamic shape optimization. It is based on a method that successively computes points on the front, by properly forcing all objectives to equality constraints, apart from one that becomes the target to be minimized. After the description of the algorithm's steps, applications in aerodynamic shape optimization of an airfoil are presented. Two- and three-objective problems are solved, with bounded design variables and equality or inequality constraints.



Fostering innovation with HPC, advanced simulations and AI and Big Data
by Christos Christodoulou, Managing Coordinator - Innovation Scout, SimEA, CaSToRC, The Cyprus Institute

Date: Tuesday, 12 January 2021


The computation-based science and technology research center (CaSToRC) has recently become a National Competence Center in HPC and the host of the prestigious SimEA ERA Chair project that aims to expand the research activities of the center and forge innovative collaborations with industry.

In this talk, Christos, the Innovation Scout of SimEA, will talk about the Management and Innovation Office (MIO) established at CaSToRC, as a structural change aiming to promote the innovation strategy of the center. He will also talk about the core competences of the SimEA team and of CaSToRC, and how the industrial and governmental sector can use HPC to achieve breakthroughs in areas like energy and environment, design of novel materials, digitalization of industry, circular economy, oil and gas production, medicine, and financial risk assessment.



High Performance Computing in Structural Biology
by Assistant Prof. Daskalakis Vangelis, leader of the Computational Environmental Modeling (CEM) Group, Department of Environmental Science and Technology (EST) at the Cyprus University of Technology (CUT)

Date: Tuesday, 19 January 2021


Structural biology is a branch of molecular biology, biochemistry, and biophysics with the focus on the molecular structure of biological macromolecules (like proteins and membranes). A key question of Structural Biology is how these macromolecules acquire their structures. A combination of methodologies like Molecular Dynamics and Markov state modeling that is supported by High Performance Computing (HPC) leads to an ideal description of macromolecule conformations and dynamics at all-atom resolution. The latter is a valuable information in Structural Biology. In this seminar two key HPC projects will be presented that relate to: (A) the out-break of the novel coronavirus (SARS-CoV-2) that causes the respiratory tract disease COVID-19 and the dynaics of two key viral proteins that can potentially be used as drug-targets or source of epitope vaccines, and (B) the delicate balance between light harvesting and photoprotective modes of the Light Harvesting Complexes of Photosystem II, that can potentially be used as models for artificial photosynthesis.



Computer Simulation Aspects of Nanoparticle and Nanodevice Design 

by Staff Scientist, "Nanoparticles by Design” Unit leader at OIST Graduate University, Japan, Visiting Assistant Professor at the Particle Technology Laboratory at ETH Zürich, Prof. Panagiotis Grammatikopoulos

Date: Tuesday, 26 January 2021


Cluster beam deposition (CBD) is a term that collectively describes various physical methods of nanoparticle synthesis by nucleation and growth from a supersaturated atomic vapour. It provides a solvent- and effluent-free method to design monodisperse multifunctional nanoparticles with tailored characteristics that can be subsequently deposited on a desired substrate or device in the soft-landing regime under ultra-high vacuum.

In this talk, I will explain the main mechanisms that control the basic properties of individual nanoparticles such as size, shape, or chemical ordering, based on various setups of CBD sources. Moving to a coarser scale, I will bring up examples where larger structures can be designed using nanoparticles as their functional building blocks, such as novel sensors and energy storage devices. To date, CBD faces two main limitations that need to be overcome for real-world applications: (i) limited yield, and (ii) precise structural control. The main thesis of this talk is that both challenges can be tackled by in-depth theoretical understanding of both the thermodynamics and kinetics of nucleation & growth. To this end, atomistic computer modelling can be an invaluable tool, complementing experimental fabrication and guiding future source design.