Bhanu Shrestha | Computer Science and Artificial Intelligence | Best Researcher Award

Bhanu Shrestha | Computer Science and Artificial Intelligence | Best Researcher Award

Prof. Dr Bhanu Shrestha, Kwangwoon University, South Korea

Prof. Dr. Bhanu Shrestha is a distinguished academic in Electronic Engineering, with a Ph.D. from Kwangwoon University, Seoul, Korea. He has been active in various leadership roles, including Chairman of ICT-AES and Editor-in-Chief of the International Journal of Advanced Engineering. Dr. Shrestha has contributed extensively to research, with notable book publications and multiple awards, including the “Achievement Award” from IIBC Korea and “Best Paper Award” at ISSAC 214. His work spans various international conferences, focusing on advanced engineering, nanotechnology, and biosensor applications. ๐ŸŒ๐Ÿ“š๐Ÿ…๐Ÿ’ป๐Ÿง‘โ€๐Ÿ”ฌ

Publication Profile

Scopus

Education

Prof. Dr. Bhanu Shrestha has an extensive academic background in Electronic Engineering. He completed his Ph.D. in Electronic Engineering at Kwangwoon University, Seoul, Korea (2004-2008), after earning his M.S. in the same field at the same institution (2002-2004). Dr. Shrestha’s journey in engineering began with a B.S. in Electronic Engineering from Kwangwoon University (1994-1998). His years of dedication to education and research have contributed significantly to advancements in the field of electronics. โš™๏ธ๐ŸŽ“๐Ÿ“ก

Experience

Prof. Dr. Bhanu Shrestha is a distinguished leader in engineering, serving as Chairman of ICT-AES from 2022 to 2024. With a long tenure as the Editor-in-Chief of the International Journal of Advanced Engineering, he has shaped academic discourse in the field. His active involvement with the Nepal Engineering Council (NEC) and Nepal Engineersโ€™ Association (NEA) further cements his influence in Nepalโ€™s engineering community. Prof. Shrestha’s commitment to advancing engineering practices is evident through his leadership roles and active contributions to both national and international engineering platforms. ๐Ÿ› ๏ธ๐Ÿ“š๐Ÿ”ง๐ŸŒ

Honor & Awards

Prof. Dr. Bhanu Shrestha has received numerous prestigious awards throughout his career. Notably, he was honored with the โ€œAchievement Awardโ€ from IIBC Korea (2015) ๐Ÿ† and multiple โ€œBest Paper Awardsโ€ from ISSAC 214 and ICACT (2014) ๐Ÿ“„. He also earned the โ€œExcellent Paper Awardโ€ from the Korea Institute of Information Technology (2012) ๐Ÿ… and the โ€œCertificate of Honorary Citizenshipโ€ from the Mayor of Seong-buk, Seoul (2012) ๐Ÿ™๏ธ. His accolades extend to Nepal, where he received the presidential “Nepal Vidhyabhusan Padak โ€˜Kaโ€™” Gold Medal (2009) ๐Ÿฅ‡, and several honors for his contributions to Taekwondo and Hapkido ๐Ÿฅ‹.

Research Focus

Prof. Dr. Bhanu Shrestha’s research focuses on advanced computational techniques, particularly in the intersection of artificial intelligence (AI) and engineering. He explores areas such as machine learning, metaheuristics, and optimization methods applied to real-world challenges in fields like medical imaging (e.g., SPECT-MPI cardiovascular disease classification), traffic accident prediction, and network security. His work also extends to customer churn prediction in telecom industries and network security improvements. Shrestha’s contributions aim to enhance system efficiency, prediction accuracy, and security across diverse technological and engineering domains. ๐Ÿง ๐Ÿ’ปโš™๏ธ๐Ÿฉบ๐Ÿ“ก

Editorial and Conference

Prof. Dr. Bhanu Shrestha has made significant contributions to the field of engineering through his active involvement in international conferences like ISGMA 2015 and the International Conference on ICT & Digital Convergence (2018) ๐ŸŒ๐Ÿ“ก. His dedication to global collaboration is evident in his participation in these events. Additionally, his editorial roles highlight his commitment to maintaining high-quality research output ๐Ÿ“š๐Ÿ“. Prof. Dr. Shrestha continues to play a crucial role in advancing engineering through his global outreach, fostering innovation, and contributing to the growth of academic knowledge in his field. ๐ŸŒŸ๐Ÿ’ก

Publication Top Notes

Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation

CorrectionSpecial Issue on Data Analysis and Artificial Intelligence for IoT

Correction to: A Proposed Waiting Time Algorithm for a Prediction and Prevention System of Traffic Accidents Using Smart Sensors (Electronics, (2022), 11, 11, (1765), 10.3390/electronics11111765)

Levy Flight-Based Improved Grey Wolf Optimization: A Solution for Various Engineering Problems

Leveraging metaheuristics with artificial intelligence for customer churn prediction in telecom industries

A Study on Improving M2M Network Security through Abnormal Traffic Control

Generative Adversarial Networks with Quantum Optimization Model for Mobile Edge Computing in IoT Big Data

 

Mohammad Ali Saniee Monfared | Computer Science and Artificial Intelligence | Best Researcher Award

Mohammad Ali Saniee Monfared | Computer Science and Artificial Intelligence | Best Researcher Award

Assoc. Prof. Dr Mohammad Ali Saniee Monfared , Alzahra university, Iran

Assoc. Prof. Dr. Mohammad Ali Saniee Monfared is an accomplished academic and industry expert with over 20 years of experience. ๐ŸŒ๐Ÿ”ง With a Ph.D. in Manufacturing and Mechanical Engineering from the University of Birmingham, UK (1997), and dual MSc degrees in System Engineering and Industrial Engineering, he bridges academia and industry seamlessly. ๐Ÿ“Š๐Ÿ›  He has worked in tire, automotive, electronics, and cosmetic manufacturing. His expertise spans risk assessment, predictive analytics, and reliability engineering, highlighted by groundbreaking projects in Iran’s gas and steel industries. ๐Ÿš€๐Ÿ“‰ A passionate educator, he teaches advanced courses in reliability, stochastic processes, and maintenance planning. ๐ŸŽ“โœจ

Publication Profile

google scholar

Qualification

Assoc. Prof. Dr. Mohammad Ali Saniee Monfared is a seasoned professional with over 20 years of experience spanning industry and academia ๐ŸŒŸ๐Ÿ“š. He excels at transforming complex engineering challenges into predictive analytics solutions ๐Ÿ“Šโš™๏ธ. Dr. Monfared is known for crafting statistical models to address intricate problems and developing testbeds to verify and validate these solutions using advanced machine learning techniques ๐Ÿค–๐Ÿ“. His expertise lies in bridging theoretical concepts with practical applications, delivering impactful results. Dr. Monfaredโ€™s dedication to innovation and structured problem-solving makes him a highly respected figure in his field ๐Ÿš€โœจ.

Education

Assoc. Prof. Dr. Mohammad Ali Saniee Monfared is a distinguished academic with a Ph.D. from the University of Birmingham, UK (1997) in Manufacturing and Mechanical Engineering ๐ŸŽ“โš™๏ธ. He earned his first MSc in Industrial Engineering & Operations Research from Sharif University in Tehran, Iran (1991) ๐Ÿ“Š๐Ÿ‡ฎ๐Ÿ‡ท, and his second MSc in System Engineering from the University of Regina, Canada (1994) ๐ŸŒ๐Ÿ”ง. With extensive expertise in engineering and operations, Dr. Monfared has significantly contributed to his field through research and teaching. His international education underscores his commitment to advancing knowledge and innovation in engineering disciplines ๐ŸŒŸ๐Ÿ“š.

Experienceย 

Assoc. Prof. Dr. Mohammad Ali Saniee Monfared boasts diverse industrial experience, including 8 years in tire and rubber manufacturing, 2 years in the automotive sector, 2 years in electronics, and 2 years in cosmetic and soap production ๐Ÿญ๐Ÿš—๐Ÿ“Ÿ๐Ÿงผ. Now a respected academic, he teaches graduate courses such as Reliability Engineering, Advanced Maintenance Planning, Stochastic Processes, and RCM ๐Ÿ“š๐Ÿ”ง. His undergraduate teachings include Engineering Statistics, Inventory Planning, and Advanced Operations Research ๐Ÿ“Š๐Ÿ“. Dr. Monfaredโ€™s rich professional background enriches his lectures, combining practical expertise with academic excellence, making him a vital contributor to engineering education ๐ŸŒŸ.

Recent Projects with Industriesย 

Assoc. Prof. Dr. Mohammad Ali Saniee Monfared showcases exceptional problem-solving and industry relevance in his recent projects. ๐ŸŒŸ His groundbreaking “Multi-perspective Risk Assessment in the Gas Industry” (2021-2023) analyzed a city gate station from 12 stakeholder viewpoints, a first in the field. ๐Ÿšง๐Ÿ“Š In 2022, he developed an innovative risk-based maintenance model for a 35-year-old city gate station, enhancing safety and mitigating catastrophic risks. ๐Ÿ”งโš™๏ธ Additionally, his 2020 project on reliability-based maintenance for a seal gas compressor improved reliability by 15% using a redundancy model. ๐Ÿš€๐Ÿ“ˆ These achievements highlight his ingenuity and commitment to advancing engineering practices. ๐Ÿ‘จโ€๐Ÿ”ฌโœจ

Research Focus

Assoc. Prof. Dr. Mohammad Ali Saniee Monfared’s research primarily focuses on network analysis, reliability, and optimization, with applications spanning academic performance, power grids, water distribution systems, and road networks. ๐Ÿ–ง๐Ÿ” His work explores vulnerability assessment using complex network theory ๐ŸŒ, optimization techniques โš™๏ธ, and adaptive systems ๐Ÿ“ˆ. Dr. Monfared’s interdisciplinary contributions include advancing sensor placement for contamination detection ๐Ÿšฐ, controlling multi-electron dynamics in molecular systems ๐Ÿงฌ, and developing frameworks for manufacturing automation ๐Ÿค–. His research integrates statistical mechanics, evolutionary algorithms, and time-series analysis to enhance system reliability and efficiency ๐Ÿ”ฌ๐Ÿ“Š. His impactful publications reflect innovative solutions in engineering and science. ๐Ÿš€โœจ

Publication Top Notes

Network DEA: an application to analysis of academic performance

Topology and vulnerability of the Iranian power grid

A complex network theory approach for optimizing contamination warning sensor location in water distribution networks

Comparing topological and reliability-based vulnerability analysis of Iran power transmission network

Controlling the multi-electron dynamics in the high harmonic spectrum from N2O molecule using TDDFT

Design of integrated manufacturing planning, scheduling and control systems: a new framework for automation

Fuzzy adaptive scheduling and control systems

A new adaptive exponential smoothing method for non-stationary time series with level shifts

An improved evolutionary algorithm for handling many-objective optimization problems

Road networks reliability estimations and optimizations: A Bi-directional bottom-up, top-down approach