Ansar Shah l Big Data | Research Excellence Award

Assoc. Prof. Dr. Ansar Shah l Big Data | Research Excellence Award

University of Southern Punjab Multan | Pakistan

Dr. Ansar Munir Shah is an Associate Professor of Computer Science with extensive experience in teaching, research, academic leadership, and curriculum development at undergraduate and graduate levels. Dr. Ansar Munir Shah holds a PhD in Computer Science from the University of Technology Phnom Penh, Cambodia, and is an HEC-approved PhD supervisor with strong academic credentials. Dr. Ansar Munir Shah has served in prominent academic roles at EM&E College (NUST), King Khalid University, and ISP Multan, earning multiple awards for committee service and academic excellence. Dr. Ansar Munir Shah’s research interests include wireless sensor networks, IoT, cloud computing, cybersecurity, and AI-driven network and data security.

Citation Metrics (Scopus)

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Citations
134

Documents
15

h-index
8

Citations

Documents

h-index


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Featured Publications

Big Data Meets Jugaad: Cultural Innovation Strategies for Sustainable Performance in Resource-Constrained Developing Economies
– Sustainability, 2025
DOI: 10.3390/su17157087
Dynamic and Integrated Security Model in Inter Cloud for Image Classification
– Foundation University Journal of Engineering and Applied Sciences, 2024
DOI: 10.33897/fujeas.v4i1.874
Efficient Energy and Delay Reduction Model for Wireless Sensor Networks
– Computer Systems Science and Engineering, 2023
DOI: 10.32604/csse.2023.030802
ILSM: Incorporated Lightweight Security Model for Improving QoS in WSN
– Computer Systems Science and Engineering, 2023
DOI: 10.32604/csse.2023.034951
Improved-Equalized Cluster Head Election Routing Protocol for Wireless Sensor Networks
– Computer Systems Science and Engineering, 2023
DOI: 10.32604/csse.2023.025449

Guru Guruswamy l Aerospace and Civil Engineering | Distinguished Scientist Award

Dr. Guru Guruswamy l Aerospace and Civil Engineering | Distinguished Scientist Award

NASA Ames Research Center | United States

Dr. Guru Guruswamy is a distinguished aerospace scientist with decades of leadership in computational aeroelasticity, multidisciplinary design, and high-performance computing. He holds a PhD from Purdue University, an ME from the Indian Institute of Science, and a BE from Bangalore University with top honors. His professional career spans senior scientific leadership at NASA Ames, consultancy in high-fidelity air-taxi simulations, and earlier roles in industry and national laboratories. Dr. Guru Guruswamy’s research interests include transonic aeroelasticity, fluid-structure-control interaction, and scalable HPC frameworks, supported by advanced skills in simulation software development and project oversight. A recipient of multiple NASA, AIAA, and academic honors, he continues to shape aerospace innovation through research, mentorship, and global technical leadership.

Citation Metrics (Scopus)

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Citations
1,471

Documents
103

h-index
20

Citations

Documents

h-index


View Scopus Profile

Featured Publications

A body-fitted structured grid approach to simulate breathing mode oscillations during parachute deployment


Aerospace Science and Technology, 2025

Grid topology for time-accurate deployment simulation of 2D parachutes using Navier–Stokes equations


Aerospace Science and Technology, 2023

High-fidelity flight simulation of small aircraft over tall buildings


Journal of Aerospace Engineering, 2022

Computation of gust-induced responses of an air taxi using Navier–Stokes equations


Aerospace Science and Technology, 2022

Active control of Dutch-roll oscillations of eVTOL aircraft


Aerospace Science and Technology, 2021

Angelos Athanasiadis | Machine Learning and AI Applications | Research Excellence Award

Mr. Angelos Athanasiadis | Machine Learning and AI Applications | Research Excellence Award

Aristotle University of Thessaloniki (AUTH) | Greece

Mr. Angelos Athanasiadis is a Ph.D. candidate in Electrical and Computer Engineering at Aristotle University of Thessaloniki, specializing in FPGA-based acceleration of Convolutional Neural Networks (CNNs) and heterogeneous computing systems. He holds an M.Eng. in Electronics and Computer Systems and an MBA with high distinction. His research focuses on energy-efficient FPGA architectures, full-precision CNN inference on reconfigurable hardware, drone-assisted monitoring systems, distributed embedded system emulation, and timing-accurate simulation of cyber-physical systems. Angelos has contributed to EU-funded research projects such as ADVISER and REDESIGN, and has gained industrial experience in embedded system development and R&D at Cadence Design Systems, EXAPSYS, and SEEMS PC. He developed a parameterizable high-level synthesis matrix multiplication library for AMD FPGAs and designed FUSION, an open-source framework integrating QEMU with OMNeT++ via HLA/CERTI for deterministic, sub-microsecond synchronized, multi-node emulation of heterogeneous computing systems. His work supports realistic prototyping of systems combining CPUs, GPUs, and FPGAs in accuracy-critical domains such as aerial monitoring and autonomous embedded platforms. With a strong foundation in both academic research and industrial applications, Angelos advances the field of FPGA-based acceleration and distributed embedded computing, bridging innovation with practical deployment.

Profile : Google Scholar

Featured Publications

Athanasiadis, A., Tampouratzis, N., & Papaefstathiou, I. (2025). An efficient open-source design and implementation framework for non-quantized CNNs on FPGAs. Integration, 102625.

Athanasiadis, A., Tampouratzis, N., & Papaefstathiou, I. (2025). Energy-efficient FPGA framework for non-quantized convolutional neural networks. arXiv preprint arXiv:2510.13362.

Athanasiadis, A., Tampouratzis, N., & Papaefstathiou, I. (2024). An open-source HLS fully parameterizable matrix multiplication library for AMD FPGAs. WiPiEC Journal – Works in Progress in Embedded Computing Journal, 10(2).

Katselas, L., Jiao, H., Athanasiadis, A., Papameletis, C., Hatzopoulos, A., … (2017). Embedded toggle generator to control the switching activity during test of digital 2D-SoCs and 3D-SICs. 2017 27th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS).

Katselas, L., Athanasiadis, A., Hatzopoulos, A., Jiao, H., Papameletis, C., … (2017). Embedded toggle generator to control the switching activity. 2017. (Conference details same as above; possible short version or extended abstract.)

Anatoly Vershinin | Algorithm Development | Best Researcher Award

Prof. Anatoly Vershinin | Algorithm Development | Best Researcher Award

Lomonosov Moscow State University | Russia

Professor Anatoly Vershinin is a distinguished computational mechanics researcher at Lomonosov Moscow State University, holding a Doctorate in Physical and Mathematical Sciences. Graduating with honors from the Faculty of Mechanics and Mathematics in 2006, he has been a core member of the Chair of Computational Mechanics since 2009. With an h-index of 11 and over 321 citations, Professor Vershinin has authored 51 journal articles, 4 books, and holds 33 patents, contributing significantly to numerical modeling, high-performance computing, and computational mechanics. His research focuses on numerical discretization methods for nonlinear partial differential equations and parallel algorithms for massively parallel computing systems, underpinning the industrial structural engineering software CAE Fidesys. He has led or contributed to 11 research projects and multiple consultancy initiatives in collaboration with institutes such as the Schmidt Institute of Physics of the Earth and Saudi Aramco Moscow Innovation Center. An active member of the International Program Committee for “Advanced Mechanics: Structure, Materials, Tribology,” he bridges academia and industry, driving innovations in structural analysis and computational methods. His contributions have earned recognition for advancing numerical methods, high-performance simulations, and practical engineering applications, establishing him as a leading figure in computational mechanics research.

Profiles : Scopus | Orcid | Research Gate

Featured Publications

Yarushina, V. M.; Podladchikov, Y. Y.; Vershinin, A. V. (2025). “A Micromechanical Model for Mineral Replacement Reactions and Associated Deformation: From Pore Clogging to Solid Volume Increase” in American Journal of Science.

Ampilov, Y. P.; Vershinin, A. V.; Kunchenko, D. S.; Petrovsky, K. A.; Safuanova, K. R. (2025). “Prediction of Thin-Layer Thickness Using Seismic Full-Waveform Modeling” in Moscow University Geology Bulletin.

Levin, V. A.; Vershinin, A. V. (2024). “CAE Fidesys as the Implementation of Fundamental Results of Computational Mechanics into Industry” in International Scientific Conference “Advanced Mechanics: Structure, Materials, Tribology”, Samarkand, Uzbekistan, 23-26 сентября 2024. Abstracts

Levin, V. A.; Vershinin, A. V.; Yakovlev, M. Ya; Levchegov, I. O.; Zhmurovsky, A. A. (2024). “Computed Tomography Based Stress-Strain Analysis of Heterogeneous Models of Rocks and Biological Tissues Using Unstructured Meshes” in Russian Physics Journal.

Vershinin, A.; Ampilov, Y.; Levin, V.; Petrovsky, K. (2024). “Full waveform modeling in seismic exploration based on a digital geological model using spectral element method on GPU” in 16th World Congress on Computational Mechanics and 4th Pan American Congress on Computational Mechanics.