Ehsan Mansouri | Machine learning | Best Researcher Award

Mr. Ehsan Mansouri | Machine learning | Best Researcher Award

Researcher, Inha University, South Korea

🧑‍💻 Ehsan Mansouri is a passionate software engineer and researcher specializing in cloud computing, machine learning, and data science. With a strong background in software engineering, he is committed to pushing the boundaries of technology to solve complex problems. Ehsan is currently a researcher at the Industrial Science and Technology Research Institute, Inha University, South Korea, where he explores innovative solutions in optimization and human-computer interaction.

Publication Profile

Google Scholar

Strengths for the Award

  1. Strong Educational Background: Ehsan Mansouri holds a Master’s degree in Software Engineering, specializing in cloud computing and optimization algorithms. His thesis focused on improving server efficiency in cloud environments, demonstrating his deep understanding of cutting-edge technology.
  2. Diverse Research Interests and Experience: His research spans multiple areas, including Machine Learning, Data Science, Cloud Computing, and Human-Computer Interaction, reflecting a broad and interdisciplinary approach. This is complemented by his experience as a researcher at Inha University and software engineer roles in both academic and private sectors.
  3. Publication Record: Mansouri has an impressive record of peer-reviewed publications, with multiple articles in reputable journals like Buildings, Journal of Forecasting, and Steel and Composite Structures. His works cover a range of topics from machine learning applications to software development for thermal analysis, illustrating his versatility as a researcher.
  4. Technical Proficiency: Proficient in various programming languages and machine learning frameworks, Mansouri has the technical skills required for developing innovative solutions. His expertise in data processing and visualization further enhances his research capabilities.
  5. Active Research Projects: Mansouri is actively involved in current research projects, such as developing machine learning models for predicting shear capacity of composite beams, highlighting his ongoing contributions to the field.

Areas for Improvement

  1. Focus on Core Research Strengths: While Mansouri has a broad range of research interests, a more concentrated focus on a specific niche area might help solidify his standing as an expert in that domain. This would enhance his recognition and impact in a highly specialized field.
  2. Increased Collaboration and Networking: Engaging in more international collaborations and expanding his network beyond his current institutions could amplify his research visibility and impact. This could include presenting at more international conferences and participating in cross-institutional research projects.
  3. Further Development of Communication Skills: Although Mansouri has achieved a high TOEFL score, enhancing his speaking skills (currently at 20/30) could improve his ability to present research findings effectively and engage with the global academic community more fluently.

 

Education

🎓 Master of Science in Software Engineering from Azad University of Birjand, Iran, where Ehsan developed a new data replication algorithm in cloud computing using particle swarm optimization. He also holds a Bachelor of Science in Software Engineering from the University of Birjand, Iran. His early education was at the National Organization for Development of Exceptional Talents (NODET) in Birjand, Iran.

Experience

💼 Ehsan has held various positions, including Researcher at Inha University, South Korea, and Software Engineer Expert at Birjand University of Medical Sciences and Butia’s Intelligent Sense of Communication in Iran. His experience ranges from software engineering to implementing innovative research projects in academia and private sectors.

Research Focus

🔍 Ehsan’s research interests include Machine Learning, Data Science, Cloud Computing, Human-Computer Interaction, Optimization, Data Grid, and Time Series Analysis. He is driven by a passion for creating efficient, scalable, and intelligent systems that enhance user experience and computational performance.

Awards and Honors

🏆 Ehsan Mansouri has achieved notable recognition in his field for his innovative work in cloud computing and data replication strategies, contributing significantly to enhancing server efficiency and optimization techniques in computational environments.

Publication Top Notes

📚 Ehsan has published several impactful papers in leading journals, including the Journal of Forecasting, Buildings, Steel and Composite Structures, and the Journal of Sustainability. His research contributions have been recognized and cited widely by peers in the field.

Ferreira, F.P.V., Jeong, S.H., Mansouri, E., Shamass, R., Tsavdaridis, K., Martins, C.H., De Nardin, S. (2024). Five Machine Learning Models Predicting the Global Shear Capacity of Composite Cellular Beams with Hollow-Core Units. Buildings. Link. Cited by: [2 articles].

Adnan, R.M., Mostafa, R.R., Dai, H.L., Mansouri, E., Kisi, O., Zounemat‐Kermani, M. (2024). Comparison of Improved Relevance Vector Machines for Streamflow Predictions. Journal of Forecasting, 43(1). Link. Cited by: [1 article].

Jeong, S.H., Mansouri, E., Ralston, N., Hu, J.W. (2024). An Advanced Software Interface to Make OpenSees for Thermal Analysis of Structures More User-Friendly. Steel and Composite Structures, 51(2). Link. Cited by: [3 articles].

Sabzekar, M., Mansouri, E., Deldari, A. (2023). A Data Replication Algorithm for Improving Server Efficiency in Cloud Computing Using PSO and Fuzzy Systems. Computer and Knowledge Engineering, 6(12), 1-14. Link. Cited by: [5 articles].

Mansouri, E., Manfredi, M., Hu, J.W. (2022). Environmentally Friendly Concrete Compressive Strength Prediction Using Hybrid Machine Learning. Journal of Sustainability, 14(20), 12990. Link. Cited by: [4 articles].

Conclusion

Ehsan Mansouri is a strong candidate for the Research for Best Researcher Award, given his robust educational background, diverse research interests, impressive publication record, and technical expertise. To further strengthen his candidacy, focusing on core research areas, expanding international collaborations, and refining communication skills would be beneficial. Overall, Mansouri demonstrates significant potential and contributions to the field of computer science and software engineering.

Avirup Roy | Machine Learning |Machine Learning Research Award

Mr. Avirup Roy | Machine Learning |Machine Learning Research Award

PhD Student, Michigan State University, United States

Dr. Avirup Roy is a dedicated researcher and engineer specializing in networked embedded and wireless systems. Currently pursuing his PhD at Michigan State University, his work focuses on developing self-learning mechanisms for embedded hardware systems with limited computational resources. With a solid foundation in electronics and communication engineering, Avirup has gained extensive experience in both academia and industry, contributing to projects ranging from smart malaria detection to automated power management systems. His technical skills span machine learning, embedded systems, cloud computing, and web development. Beyond his professional life, Avirup is passionate about Indian classical music, photography, and swimming. 🌟📚🎵📷🏊‍♂️

Profile

ORCID

 

Education🎓

Michigan State University, East Lansing, MI, US PhD in Electrical and Computer Engineering (2020-Present). Dissertation: Self-learning mechanisms for Embedded hardware systems with limited computational resources. GPA: 3.75/4Maulana Abul Kalam Azad University of Technology, Kolkata, WB, India Bachelor of Technology (BTech) in Electronics and Communication Engineering (2013-2017)

Experience💼

Graduate Research Assistant, Michigan State University (Sep 2020 – Jul 2023),Developed an android and website application for smart malaria detection involving cloud database integration. Graduate Teaching Assistant, Michigan State University (Aug 2023 – Present), Instructed and graded labs for Embedded Cyber-physical Systems, VLSI Systems, and Digital Control courses. ICER Cloud Computing Fellow, Michigan State University (Sep 2023 – Present), Implemented Azure cloud resources in semi-supervised federated learning for embedded devices. Programmer Analyst, Cognizant Technology Solutions (Dec 2017 – Jul 2020), Developer and support analyst for ASP.NET based applications of MetLife Inc. Intern, Calcutta Electric Supply Corporation (CESC) Limited (Jul 2016 – Aug 2016), Worked on automated power management systems using SCADA communication. Intern, Bharat Sanchar Nigam Limited (BSNL) (Jun 2015 – Aug 2015), Explored general trends in wireless communication. Undergraduate Researcher, Maulana Abul Kalam Azad University of Technology (2015-2016), Presented research at various international conferences and served as the vice-president of SPIE Student Chapter.

Research Interests🔍

Embedded Machine Learning: Focused on developing efficient learning algorithms for resource-constrained devices.
Networked Embedded Systems: Exploring self-learning mechanisms and their applications in real-world scenarios.
Cloud Computing: Leveraging cloud resources for semi-supervised federated learning.
VLSI Systems: In-depth study and teaching of Very-Large-Scale Integration systems.
Cyber-Physical Systems: Research on embedded systems interacting with physical processes.

Awards🏆

National Social Entrepreneurship Programme (2014): Secured 2nd position for the ‘Hand-Made Paper Industry’ project.
SPIE Smart Structures and Non-destructive Evaluation Conference (2016): Presented research in Las Vegas, Nevada.
EAPE Conference (2015): Presented research on emerging areas of photonics and electronics.
Graduate Fellowships: Awarded multiple fellowships during PhD for research and teaching excellence.

Publications

Semi-Supervised Learning Using Sparsely Labelled Sip Events for Online Hydration Tracking Systems
A. Roy, H. Dutta, A. K. Bhuyan, and S. K. Biswas, 2023, International Conference on Machine Learning and Applications (ICMLA).
Cited by: 3 articles.

An On-Device Learning System for Estimating Liquid Consumption from Consumer-Grade Water Bottles and Its Evaluation
Roy, A., Dutta, H., Griffith, H., & Biswas, S., 2022, Sensors.
Cited by: 5 articles.