Imtiaz Ahmad | Computer Science | Best Researcher Award

Posted on 28/08/202428/08/2024 by ScienceFather

Imtiaz Ahmad | Computer Science | Best Researcher Award

Mr Imtiaz Ahmad, Hazara University Mansehra, Pakistan

Based on the provided information, Mr. Imtiaz Ahmad demonstrates significant potential as a candidate for the “Best Researcher Award.” Here’s an assessment of his qualifications:

Publication profile

Orcid

Educational Background

Mr. Imtiaz Ahmad holds a Master of Science in Computer Science from Hazara University Mansehra, graduating with an impressive CGPA of 3.71/4.00. His thesis focused on developing an adaptive and priority-based data aggregation and scheduling model for wireless sensor networks, showcasing his ability to tackle complex problems in this area. His Bachelor’s degree in Information Technology from the University of Malakand further laid the foundation for his technical expertise, although his CGPA of 2.95/4.00 was more modest. Nonetheless, his final year project on an online hospital management system reflects his ability to apply academic knowledge to real-world problems.

Research Contributions

Mr. Ahmad has made meaningful contributions to the field of computer science, particularly in wireless sensor networks and mobile edge computing. His publication in the Knowledge-Based Systems journal on adaptive and priority-based data aggregation and scheduling for wireless sensor networks is a strong indicator of his research capabilities. Additionally, his work on mobility prediction-based adaptive task migration in mobile edge computing, published in VFAST Transactions on Software Engineering, highlights his focus on cutting-edge issues in computer science. These publications in reputable journals underline his research aptitude and commitment to advancing the field.

Professional Experience

Mr. Ahmad has accumulated valuable teaching and technical experience through various roles. As a visiting lecturer at Hazara University and a computer science lecturer at other institutions, he has been responsible for planning and delivering lectures, assessing student work, and supervising final year projects. His involvement in these educational roles suggests a deep engagement with the academic community and a commitment to nurturing future researchers. His previous internship at Hazara University, where he addressed technical issues and assisted in setting up multimedia for conferences, adds to his practical experience.

Awards and Certifications

Mr. Ahmad has been recognized for his research potential early in his academic career, receiving the Best Student Researcher Award from the Department of Computer Science at Hazara University in 2020. Additionally, he was awarded a laptop through the Prime Minister’s Laptop Scheme for high achievers, which is a testament to his academic excellence. His professional certifications, including Microsoft Office Specialist and vocational training in computers, further bolster his technical skill set.

Conclusion

In conclusion, Mr. Imtiaz Ahmad’s solid academic background, impactful research publications, teaching experience, and recognized achievements make him a strong candidate for the “Best Researcher Award.” His work in wireless sensor networks and mobile edge computing is both relevant and innovative, positioning him well for continued contributions to the field of computer science. Therefore, he is indeed suitable for consideration for this prestigious award.

Publication top notes

Adaptive and Priority-Based Data Aggregation and Scheduling Model for Wireless Sensor Network

A Mobility Prediction Based Adaptive Task Migration in Mobile Edge Computing

Huilong Fan | Computer Science | Best Researcher Award

Posted on 24/06/202424/06/2024 by ScienceFather

Dr Huilong Fan | Computer Science | Best Researcher Award

assistant researcher at University of Electronic Science and Technology of China

Huilong Fan is a research assistant at the University of Electronic Science and Technology of China, born in December 1992, and residing in Changsha, Hunan. He specializes in Edge Computing and Artificial Intelligence.

profile

Scopus

Academic Background:

Ph.D. in Computer Science and Technology, Central South University (2019-2023)
- Major: Satellite multi-intelligence collaborative computing, digital twins, swarm intelligence negotiation, multi-intelligence deep reinforcement learning, online scheduling, artificial intelligence, machine learning.
Master in Computer Science and Technology, Guizhou University (2015-2018)
- Major: Medical big data, big data analysis and prediction, deep learning, multi-label data classification, natural language processing.
Bachelor in Network Engineering, Nanyang Institute of Technology (2010-2014)
- Major: Computer Networks, Principles of Computer Composition, Operating Systems, Algorithm Design.

Professional Experience:

Data Analyst, Beijing Ark Hospital (June 2014-Sept 2015; Dec. 2023-Present)
- Responsibilities: Data cleaning, analysis, and visualization, system development and maintenance, research on satellite networks, collaborative computing, and edge computing.
R&D Engineer, Hunan Lisen Data Technology Co Ltd (June 2018-Sept 2019)
- Responsibilities: Algorithm design, multi-platform software architecture design, software development, database management, interface development and design.

Projects and Leadership:

Led projects on mixed integer programming for multi-process production scheduling, satellite and management software R&D, and real-time analysis methods for large-scale multi-source data based on supercomputing.
Participated in significant research such as intelligent analysis technology for TFDS images and resource allocation technology based on collaborative perception.

Awards and Patents:

Second prize in scientific and technological progress (2020)
First prize in the Guizhou Province Innovation and Entrepreneurship Competition (2016)
National third prize in the ‘Internet +’ College Students Innovation and Entrepreneurship Competition (2016)
Invention Patents: Multi-agent Space-based Information Network Task Scheduling Method (2021), Dynamic Reconfigurable Space-based Information Network Simulation and Computing System (2022).

Skills:

Proficient in software architecture design, Java, Python, C, and other programming languages.
Experienced in leading R&D teams and writing research project applications.

Research Focus in Computer Science:

Huilong Fan’s research in Computer Science spans several advanced and interdisciplinary areas, primarily focusing on:

Satellite Multi-Intelligence Collaborative Computing:
- Developing systems that allow multiple intelligent agents to work together effectively in satellite networks.
- Utilizing collaborative algorithms to improve the efficiency and reliability of satellite communications and operations.
Digital Twins:
- Creating digital replicas of physical systems to simulate and analyze their real-world counterparts.
- Applying digital twin technology to monitor, diagnose, and optimize satellite and network operations.
Swarm Intelligence Negotiation:
- Investigating algorithms that enable decentralized agents to coordinate and negotiate within a swarm.
- Using swarm intelligence for tasks such as resource allocation and scheduling in dynamic environments.
Multi-Intelligence Deep Reinforcement Learning:
- Developing deep learning models that enable multiple intelligent agents to learn and adapt to complex environments.
- Applying these models to solve problems in satellite networks and edge computing.
Online Scheduling:
- Researching methods for real-time scheduling of tasks and resources in dynamic and distributed systems.
- Focusing on optimizing the allocation of contact windows in satellite communication networks.
Artificial Intelligence and Machine Learning:
- Applying AI and ML techniques to solve complex problems in big data analysis, prediction, and decision-making.
- Emphasizing multi-label data classification and natural language processing for diverse applications.
Medical Big Data:
- Analyzing and predicting trends in medical data using big data technologies.
- Developing models for deep learning and multi-label classification to enhance medical data interpretation and application.
Graph-Driven Resource Allocation:
- Utilizing graph theory and cooperative game theory to optimize resource allocation in Internet of Things (IoT) and satellite networks.
- Developing adaptive scheduling algorithms for real-time and dynamic environments.

Through his extensive research, Huilong Fan aims to push the boundaries of what is possible in satellite communication, edge computing, and AI, contributing significantly to advancements in these fields.

Publication Top Notes:

Dynamic Network Resource Autonomy Management and Task Scheduling Method Li, X., Yang, J., Fan, H.
Mathematics, 2023, 11(5), 1232. Citations: 6
A novel multi-satellite and multi-task scheduling method based on task network graph aggregation Fan, H., Yang, Z., Zhang, X., Long, J., Liu, L.
Expert Systems with Applications, 2022, 205, 117565. Citations: 15
A Spatio-Temporal Graph Neural Network Approach for Traffic Flow Prediction Li, Y., Zhao, W., Fan, H.
Mathematics, 2022, 10(10), 1754. Citations: 6
Quantum Digital Signature with Continuous-Variable Deng, X., Zhao, W., Shi, R., Ding, C., Fan, H.
International Journal of Theoretical Physics, 2022, 61(5), 144. Citations: 3

Syed MuhammadMohsin | Computer Science Award | Best Researcher Award

Posted on 12/06/202412/06/2024 by ScienceFather

Syed MuhammadMohsin | Computer Science Award | Best Researcher Award

Mr. Syed MuhammadMohsin, Syed Muhammad Mohsin, Pakistan

👨‍🎓 Syed Muhammad Mohsin, a dedicated PhD scholar at COMSATS University Islamabad, Pakistan, focuses on energy-efficient cloud technologies. With expertise in computer science and a solid academic background, including MS and BS degrees, he has published extensively in renowned journals and presented at international conferences. Mohsin’s research delves into topics like IoT network security, renewable energy forecasting, and smart grid management. Alongside his scholarly pursuits, he serves as an Assistant Technical Officer at the Pakistan Atomic Energy Commission and holds visiting lecturer positions at various universities. His multifaceted skills encompass coding, network administration, and project management.

Publication Top Notes

Orcid

Google Scholor

Education

Mr.Syed Muhammad Mohsin, a dedicated scholar , embarked on his academic journey by earning a Bachelor’s degree in Computer Science from Virtual University of Pakistan. He furthered his knowledge with a Master’s degree from the same institution, delving into the intricacies of Service Oriented Architecture for Cloud of Things. Driven by his passion for research, he pursued a PhD from COMSATS University Islamabad, focusing on energy-efficient cloud migration. His academic odyssey, complemented by numerous publications and professional experiences, reflects his unwavering commitment to advancing knowledge in computer science and technology.

Research Focus

Mr.Syed Muhammad Mohsin is a highly accomplished PhD scholar specializing in the field of energy-efficient cloud computing. With a strong background in computer science and extensive experience in academia and industry, Mohsin’s research focus lies at the intersection of green computing and intelligent migration strategies for traditional energy sources. His work, highlighted by numerous publications and contributions to prestigious conferences, demonstrates a deep understanding of emerging technologies like IoT, AI, and blockchain, applied to energy forecasting, network optimization, and security. Mohsin’s expertise and dedication make him a valuable asset in shaping the future of sustainable computing.

Publication Top Notes

A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids
- Authors: S. Aslam, H Herodotou, SM Mohsin, N Javaid, N Ashraf, S Aslam
- Journal: Renewable and Sustainable Energy Reviews
- Cited by: 355
- Year: 2021
AI-empowered, blockchain and SDN integrated security architecture for IoT network of cyber physical systems
- Authors: S Latif, S. A., XianWen, F. B., Iwendi, C., Wang, F. L., Mohsin, S. M., Han …
- Journal: Computer Communications
- Cited by: 163
- Year: 2021
A fair pricing mechanism in smart grids for low energy consumption users
- Authors: K Aurangzeb, S Aslam, SM Mohsin, M Alhussein
- Journal: IEEE Access
- Cited by: 49
- Year: 2021
A comprehensive review of computing paradigms, enabling computation offloading and task execution in vehicular networks
- Authors: A Waheed, MA Shah, SM Mohsin, A Khan, C Maple, S Aslam, …
- Journal: IEEE Access
- Cited by: 45
- Year: 2022
Energy forecasting using multiheaded convolutional neural networks in efficient renewable energy resources equipped with energy storage system
- Authors: K Aurangzeb, S Aslam, SI Haider, SM Mohsin, S Islam, HA Khattak, …
- Journal: Transactions on Emerging Telecommunications Technologies
- Cited by: 32
- Year: 2022
Performance analysis of hybridization of heuristic techniques for residential load scheduling
- Authors: Z Iqbal, N Javaid, SM Mohsin, SMA Akber, MK Afzal, F Ishmanov
- Journal: Energies
- Cited by: 29
- Year: 2018
Deep learning based techniques to enhance the performance of microgrids: a review
- Authors: S Aslam, H Herodotou, N Ayub, SM Mohsin
- Conference: 2019 International Conference on Frontiers of Information Technology (FIT …)
- Cited by: 27
- Year: 2019

Vipin Bansal | Computer Science Award | Academic Summit Impact Award

Posted on 11/06/202411/06/2024 by ScienceFather

Mr. Vipin Bansal | Computer Science Award | Academic Summit Impact Award

Mr. Vipin Bansal, Cognizant, India

Vipin Bansal is an accomplished Senior Engineering Manager specializing in AI and ML solutions. 📊 His expertise spans computer vision, anomaly detection, and AI-based healthcare innovations. He is proficient in deploying scalable AI models and cloud-based solutions using platforms like AWS and Azure. ☁️ Vipin’s work includes impactful projects in autonomous driving, healthcare, and commercial applications. 🚗 He is pursuing a PhD in Explainable AI and has authored significant research in the field. 📜 Passionate about leading teams and driving technological advancements, he continues to excel in the dynamic tech landscape. 💼

Publication Profile

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Education 🎓

Vipin is pursuing a PhD in Explainable AI from Chandigarh University and holds a Master’s in Computer Applications from Birla Institute of Technology, Ranchi. 🧑‍🎓

Work Experience 💼

Vipin has served as a Senior Engineering Manager at Cognizant, focusing on computer vision AI solutions and cloud infrastructure. He also worked at Molnlycke HealthCare on business applications and at Altran on autonomous driving technologies and data quality analysis. His earlier roles include leading mobile app development at Imagination Technology and architecting m-commerce solutions at Aricent. 🚗

Research Focus 📚🔬

Vipin Bansal’s research focuses on the application of generative AI techniques for medical imaging, specifically in detecting diabetic retinopathy. His work, showcased in a detailed review published in “Results in Optics,” emphasizes leveraging advanced AI models to improve diagnostic accuracy in ophthalmology. Collaborating with Amit Jain and Navpreet Kaur Walia, Bansal explores the potential of AI to revolutionize disease detection, highlighting the role of technology in enhancing healthcare outcomes. His research aligns with the domains of medical AI and computer vision, contributing significantly to the field of healthcare technology and artificial intelligence. 🧠👁️💡

Publication Top Notes

Diabetic retinopathy detection through generative AI techniques: A review

Fang Hou | Computer Science | Best Researcher Award

Posted on 10/06/202410/06/2024 by ScienceFather

Fang Hou | Computer Science | Best Researcher Award

Ms Fang Hou,Utrecht university,Netherlands

🌟 Fang Hou is a dedicated Ph.D. candidate specializing in empirical software engineering, focusing on software ecosystem trust and quality. With over a decade of experience in international banking IT, she brings a wealth of practical knowledge to her research. Fang’s work on the TrustSECO project aims to establish trust within software frameworks through sentiment analysis and opinion mining. She has presented her findings at various prestigious conferences and contributed to notable publications. Fang’s commitment to enhancing software security and trustworthiness underscores her passion for improving global software systems. As a teaching assistant at Utrecht University, she shares her expertise in software ecosystem security. 🖥️🔍

Publication profile

google scholar

Research focus

Fang Hou is deeply immersed in the realm of Empirical Software Engineering, with a specific focus on understanding and enhancing trust within software ecosystems. Through extensive research and practical experience, Fang delves into the technical intricacies of software trust and quality assurance. Their dedication to this field is evident through a comprehensive exploration of trust evaluation methodologies and sentiment analysis tools development. Fang’s work not only contributes to the theoretical understanding of software ecosystems but also strives to implement practical solutions for securing and fortifying global software systems. 🌐🔍