Hojjatollah shokri kaveh | Numerical Linear Algebra | Best Researcher Award

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Mr. Hojjatollah shokri kaveh | numerical Linear Algebra | Best Researcher Award

PhD student | Shahid beheshti university | Iran

Short Bio 📚

I am Hojjatollah Shokri Kaveh, a mathematics researcher specializing in solving partial differential equations and numerical linear algebra. My research focuses on inverse problems and numerical algorithms, with a keen interest in programming.

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Education 🎓

I completed my Master’s degree at Amirkabir University of Technology under the supervision of Prof. Hojjatollah Adibi, graduating with a score of 16.50 in February 2017. Currently, I am pursuing a Ph.D. at Shahid Beheshti University of Tehran under the guidance of Prof. Masoud Hajarian.

Experience 💼

I have gained valuable teaching experience over the years. I served as a teacher at Ostadbank in Tehran for 2 years and later at Aloostad for 3 years, further enhancing my communication and pedagogical skills.

Research Interests 🧮

My research interests encompass a wide range of topics in mathematics and computer science, including MATLAB, Python, and C programming, data analysis and visualization, numerical linear algebra, numerical algorithms, partial differential equations, and inverse problems. I am passionate about applying computational methods to solve real-world mathematical challenges.

Awards 🏆

In recognition of my academic achievements, I secured the second rank in the doctoral entrance exam, highlighting my dedication and proficiency in mathematics and related fields.

Publications 📝

“Numerical Solution of Inverse Problems in Partial Differential Equations using Iterative Algorithms.” Journal of Computational Mathematics, 2022. Link

“Efficient Algorithms for Data Visualization in MATLAB: A Comparative Study.” International Journal of Numerical Analysis and Modeling, 2021. Link

“Application of Numerical Linear Algebra in Image Processing: A Case Study.” Journal of Mathematical Imaging and Vision, 2020. Link

“Advancements in Computational Methods for Solving Elliptic Partial Differential Equations.” Numerical Algorithms, 2019. Link

“Python Programming for Scientific Computing: A Practical Guide.” Journal of Computational Science, 2018. Link

 

 

Eugene Syriani | Software Engineering | Best Researcher Award

Posted on by Academic achievements

Prof Dr. Eugene Syriani | Software Engineering | Best Researcher Award

Professor | Univeristy of Montreal | Canada

 

Short Bio 🌟

Eugene Syriani is a distinguished Full Professor in the Department of Computer Science and Operations Research (DIRO) at Université de Montréal, a position he has held since June 2023. His academic journey and research contributions span across software engineering, model-driven engineering, simulation, and collaborative development environments, focusing particularly on digital twins of cyber-physical and biological systems.

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SCOPUS

Education 📚

Eugene Syriani completed his foundational education at McGill University, where he earned his B.Sc. in Mathematics and Computer Science in 2006. His passion for advancing the field led him to pursue a Ph.D. in Computer Science at McGill University, which he successfully completed in 2011. Following his Ph.D., he continued his research as a Postdoctoral Research Fellow at McGill University from May to August 2011, marking the beginning of his academic career.

Experience 💼

Eugene Syriani has held various academic positions, demonstrating his commitment to education and research:

Full Professor
Université de Montréal, Canada
Since June 2023

Associate Professor
Université de Montréal, Canada
June 2017 – May 2023

Invited Professor
Università degli Studi dell’Aquila, Italy
September 2018 – December 2018

Assistant Professor
Université de Montréal, Canada
June 2014 – May 2017

Adjunct Professor
University of Alabama, USA
June 2014 – December 2016

Assistant Professor
University of Alabama, USA
August 2011 – June 2014

Lecturer
McGill University, Canada
September 2008 – May 2011

This extensive academic experience has shaped Eugene Syriani’s expertise and leadership in the field of computer science, particularly in software engineering and model-driven engineering.

Research Interest 🧠

Eugene Syriani’s research interests are diverse and impactful, covering several key areas within computer science:

  • Software Engineering: His work focuses on software design and empirical software engineering, addressing fundamental aspects of software development processes.
  • Model-Driven Engineering: Eugene explores domain-specific modeling and model transformation techniques, aiming to enhance the efficiency and accuracy of software design.
  • Simulation: He engages in research related to discrete-event simulation and simulation-based design, essential for understanding and optimizing complex systems.
  • Automation and Generative Techniques: Eugene investigates automation and code generation methods to streamline software development and improve productivity.
  • Collaborative Development Environments: He explores innovative approaches to facilitate collaboration among software developers, enhancing teamwork and project outcomes.
  • Digital Twins of Cyber-Physical and Biological Systems: Eugene’s recent focus involves digital twins, which are virtual representations of physical systems, integrating computational models with real-world data to enhance understanding, prediction, and optimization.

His multidisciplinary approach and innovative research methodologies contribute significantly to advancing these areas of study, addressing contemporary challenges in computer science and engineering.

Publication 📄

Eugene Syriani has authored numerous influential publications in peer-reviewed journals, highlighting his contributions to the academic community:

Requirements for Modelling Tools for Teaching, Software & Systems Modeling, 2024 (accepted)

From two-way to three-way: Domain-specific model differencing and conflict detection, Journal of Object Technology, 2023

Model consistency as a heuristic for eventual correctness, Journal of Computer Languages, 2023

Real-time Collaborative Multi-Level Modeling by Conflict-Free Replicated Data Types, Software & Systems Modeling, 2023

DSMCompare: Domain-Specific Model Differencing for Graphical Domain-Specific Languages, Software & Systems Modeling, 2022

Recommending Metamodel Concepts during Modeling Activities with Pre-Trained Language Models, Software & Systems Modeling, 2022

A generic approach to detect design patterns in model transformations using a string-matching algorithm, Software & Systems Modeling, 2022

 

 

Puranam Revanth Kumar | Artificial Intelligence and Machine Learning | Best Researcher Award

Posted on by Academic achievements

Dr.Puranam Revanth Kumar | Artificial Intelligence and Machine Learning | Best Researcher Award

Assistant Professor Malla Reddy University, Hyderabad, India. 

Dr. Puranam Revanth Kumar is an Assistant Professor at Malla Reddy University, Hyderabad, specializing in Artificial Intelligence and Machine Learning. His research focuses on image processing, deep learning, and biomedical imaging, with significant contributions to neuroimaging. He holds a Ph.D. in Electronics and Communication Engineering from ICFAI University, Hyderabad.

profile

Google Scholar

📚 Education

  • Ph.D., Electronics and Communication Engineering, ICFAI University, Hyderabad, India, 2019-2024.
  • M.Tech, Control and Instrumentation, AMRITA University, Coimbatore, India, 2017-2019.
  • B.Tech, Electronics and Instrumentation, GITAM University, Hyderabad, India, 2012-2016.

👨‍💼 Experience

  • Assistant Professor, Department of Artificial Intelligence and Machine Learning, Malla Reddy University, Hyderabad, India (2024-present).
  • LabVIEW Software Trainee, Optomech Engineers Pvt. Ltd., Hyderabad, India (2018-2019).

🔍 Research Interests

Dr. Kumar’s research interests include image processing, deep learning, machine learning, neuroimaging, biomedical imaging, and artificial intelligence applications in healthcare.

🏆 Award

  • Deep Learning Award, NPTEL.
  • Machine Learning Award, Coursera.
  • MATLAB on-ramp Award, MathWorks.

📄 Publications

Rui Zhang | Natural Language Processing| Best Paper Award

Posted on by Academic achievements

Mrs.Rui Zhang | Natural Language Processing| Best Paper Award

Zhang Rui is a dedicated researcher currently pursuing a doctoral degree in Computer Software and Theory at the University of Chinese Academy of Sciences. With a solid foundation in Information Management and Systems from Xi’an University of Architecture and Technology, Zhang specializes in Python programming and advanced machine learning frameworks like Pytorch. His research focuses on natural language processing, automatic text intelligence, and innovative applications such as code comment generation and program repair. Zhang has contributed significantly to scientific data management and analysis, with published papers and extensive project leadership experience in constructing digital platforms for data integration and knowledge sharing.

Profiles

Scopus

🎓Educational Background 

2018.9-Present: Pursuing doctoral studies in Computer Software and Theory at the University of Chinese Academy of Sciences. 2014.9-2018.7: Completed undergraduate studies in Information Management and Information Systems at Xi’an University of Architecture and Technology.

 🖥️Professional Skills

Proficient in Python, with expertise in machine learning and deep learning frameworks including Pytorch. Specializes in natural language processing, automatic text intelligence, code comment generation, and automatic program repair.

📝 Academic Contributions 

Published Papers: Internationally recognized contributions in text summarization, code generation, and data management across various domains of resource science and technology.Intern Experience: Hands-on involvement in image processing interfaces, data management, and analysis for scientific applications.

🏆 Awards and Recognitions 

Awarded multiple prizes for academic excellence and innovation, including top honors in mathematical modeling competitions and scholarships for outstanding performance.

🌟 Self-Evaluation 

Demonstrates keen insight, a relentless pursuit of knowledge, innovative spirit, effective communication, and strong teamwork skills.

Publications

Design of an Isolated Circuit Breaker with Robust Interruption Capability for DC Microgrid Protection

Authors: Xu, X., Chen, W., Zhang, S., Li, Z., Zhang, B.

Journal: IEEE Transactions on Industrial Electronics, 2021, 68(12), pp. 12408–12417

Exploring a particle-size-reduction strategy of YAG phosphor via a chemical breakdown method

Authors: Chen, H., Ju, L., Zhang, L., Qiu, K., Yin, L.

Journal: Journal of Rare Earths, 2021, 39(8), pp. 938–945

Short-Circuit Capability Prediction and Failure Mode of Asymmetric and Double Trench SiC MOSFETs

Authors: Deng, X., Li, X., Li, X., Li, Z., Zhang, B.

Journal: IEEE Transactions on Power Electronics, 2021, 36(7), pp. 8300–8307

Enhancement of defect detectability in pneumatic pressure equipment using an automatic detection technique in ECPT

Authors: Zhang, B., Cheng, Y., Yin, C., Chen, K., Malek, H.

Journal: Journal of Testing and Evaluation, 2021, 49(1), JTE20180724

Improved Model on Buried-Oxide Damage Induced by Total-Ionizing-Dose Effect for HV SOI LDMOS

Authors: Yuan, Z., Qiao, M., Li, X., Li, Z., Zhang, B.

Journal: IEEE Transactions on Electron Devices, 2021, 68(4), pp. 2064–2070

An analytical model on the gate control capability in p-GaN Gate AlGaN/GaN high-electron-mobility transistors considering buffer acceptor traps

Authors: Wang, F., Chen, W., Sun, R., Zhou, Q., Zhang, B.

Journal: Journal of Physics D: Applied Physics, 2021, 54(9), 095107

A low turn-on voltage AlGaN/GaN lateral field-effect rectifier compatible with p-GaN gate HEMT technology

Authors: Wang, F., Chen, W., Wang, Z., Zhou, Q., Zhang, B.

Journal: Semiconductor Science and Technology, 2021, 36(3), 034004

Hybrid silica-carbon bilayers anchoring on FeSiAl surface with bifunctions of enhanced anti-corrosion and microwave absorption

Authors: Tian, W., Zhang, X., Guo, Y., Jian, X., Deng, L.

Journal: Carbon, 2021, 173, pp. 185–193

Voltage Coupling Enhancement for Transient Gate Overvoltage Suppression of Insulated Gate Trigger Thyristor in Ultrahigh di/dt Pulse Applications

Authors: Liu, C., Chen, W., Sun, R., Li, Z., Zhang, B.

Journal: IEEE Transactions on Power Electronics, 2021, 36(3), pp. 3346–3353

Surface passivation of applying an organic-inorganic hybrid coatings toward significantly chemically stable iron powder

Authors: Zhang, L., Zheng, Q., Yin, L., Xie, J., Deng, L.

Journal: Colloids and Surfaces A: Physicochemical and Engineering Aspects, 2021, 610, 125910