محمد صدیق منش

رزومه

Education

-      Master’s - 2014

University : Qazvin Azad University | Qazvin, Qazvin Province

Filed : Information Technology- Computer Network

Subject : Improve the Lifetime of Wireless Sensor Network LEACH Algorithm

-      PhD – 2021

University: Science and Research branch, Islamic Azad University, Tehran

Filed : Information Technology, ITSM

Subject: Design of efficient hybrid algorithm from genetic-fuzzy energy in hierarchical routing management and distributed clustering in wireless sensor-based IoT

Skills

-       Python Programming: Advanced proficiency with a focus on data analysis and algorithm development.

-       Data Mining & Analysis: Experienced in extracting insights from large datasets using advanced techniques.

-       Machine Learning & Deep Learning: Skilled in predictive modeling for time series data, utilizing tools like TensorFlow.

-       Tools & Technologies: Proficient with Rapid Miner, Tableau, and TensorFlow for data analysis and visualization.

-       Blockchain Technology: Familiar with blockchain principles and applications, including smart contracts and decentralized applications.

-       Algorithmic Trading & AI Bots: Experienced in developing trading algorithms and AI bots for financial market trading.

-       Wireless Sensor Networks: Knowledgeable in designing and implementing wireless sensor networks for various applications.

Summary

A seasoned Information Technology specialist with extensive experience in Python programming, focusing on data analysis and algorithm development. Boasts a successful track record in data mining and utilizing advanced machine learning and deep learning techniques for time series forecasting, leveraging leading tools such as Rapid Miner, Tableau, and TensorFlow. Interested in and knowledgeable about blockchain technology, including its fundamental principles and applications, algorithmic trading, and the development of artificial intelligence bots for financial market trading. Additionally, experienced in designing and implementing wireless sensor networks, offering innovative solutions to complex challenges. Possesses a high ability to collaborate with teams and communicate effectively, combined with a commitment to continuous improvement and learning, making me a valuable asset to any organization.

Books

-      A Sedighimanesh, M Sedighimanesh, "Fuzzy Theories and Applications", Avaie Zistan, Iran, Qom, 2018.

-      M Sedighimanesh, A Sedighimanesh, "How to Develop, Implement and run ITIL V3 Best Practices", Avaie Zistan, Iran, Qom, 2018.

-      J Baqeri, A Sedighimanesh, M Sedighimanesh,"Security and stability of operating systems", ElhamNor, Iran, Qom, 2015.

-      A Sedighimanesh, M Sedighimanesh, J Baqeri, "Standards of Security and Stability in Computer Programs", ElhamNor, Iran, Qom, 2015.

-      M Sedighimanesh, A Sedighimanesh, J Baqeri, "Computer Software Vulnerabilities and Solutions to It", ElhamNor, Iran, Qom, 2015.

-      M Sedighimanesh, A Sedighimanesh, "Blockchain and its applications”, ElhamNor, Iran, Qom, 2019.

-      M Sedighimanesh, A Sedighimanesh,” Ethereum and smart contract”, ElhamNor, Iran, Qom, 2019.

-      M Sedighimanesh, A Sedighimanesh ,”Data Mining with RapidMiner - Scoring, Validation and Tools ”, ElhamNor, Iran, Qom, 2020.

-      M Sedighimanesh, A Sedighimanesh ,”Data Mining with RapidMiner - Data Modeling” ElhamNor, Iran, Qom, 2020.

-      M Sedighimanesh, A Sedighimanesh ,”Data Mining with RapidMiner - Data Access, Combining and Clearing”, ElhamNor, Iran, Qom, 2020.

-      A Sedighimanesh, M Sedighimanesh,” Data Science - Data science process, data exploration, classification, regression methods”, ElhamNor, Iran, Qom, 2021.

-      A Sedighimanesh, M Sedighimanesh,” Data Science - Association Analysis, Clustering, Model Evaluation”, ElhamNor, Iran, Qom, 2021.

-      M Sedighimanesh, A Sedighimanesh,” Data Science - Text Mining, Deep Learning, Recommending Engines”, ElhamNor, Iran, Qom, 2021.

-      M Sedighimanesh, A Sedighimanesh,” Data Science - Time series prediction, anomaly detection, feature selection”, ElhamNor, Iran, Qom, 2021.


Publications

-      M. sedighimanesh, H. Zandhessami, M. Alborzi, M. Khayyatian, “Reducing Energy Consumption in Sensor-Based Internet of Things Networks Based on Multi-Objective Optimization Algorithms”, Journal of Information Systems and Telecommunication (JIST), 2022

-      M. sedighimanesh, H. Zandhessami, M. Alborzi, M. Khayyatian, “Energy Efficient Routing-Based Clustering Protocol Using Computational Intelligence Algorithms in Sensor-Based IoT”, Journal of Information Systems and Telecommunication (JIST), 2021

-      M. Sedighimanesh, and A. Sedighimanesh, “Reducing Energy Consumption of the SEECH Algorithm in Wireless Sensor Networks Using a Mobile Sink and Honey Bee Colony Algorithm,” The Law, State and Telecommunications Review / Revista de Direito, Estado e Telecomunicações, 2018.

-      M. Sedighimanesh, and A. Sedighimanesh, “Improve the lifetime of wireless sensor networks using a mobile Sink and combine fuzzy algorithms in clustering time,” Electrical Engineering & Electromechanics, 2018.

-      M. Sedighimanesh, and A. Sedighimanesh, “Enhancing the lifetime of EEHRP algorithm in wireless sensor network using a fuzzy algorithm,” Electrical Engineering & Electromechanics, 2018.

-      Mohammad Sedighimanesh*, Hesam Zand Hesami and Ali Sedighimanesh, “Routing algorithm based on clustering for increasing the lifetime of sensor networks using Meta-heuristic bee algorithms,” International Journal of Sensors, Wireless Communications and Control, 2019.

-      Mohammad Sedighimanesh*, Hesam Zand Hesami and Ali Sedighimanesh “Honeybee hybrid Algorithm - Harmony in Clustering and Routing in Wireless Sensor Networks,” International Journal of Sensors, Wireless Communications and Control, 2019.

-      J Baqeri, A Sedighimanesh, M Sedighimanesh, “Increase the Lifetime of Wireless Sensor Networks using Hierarchical Clustering with Cluster Topology Preservation,” International Journal of Wireless & Mobile Networks (IJWMN), 2016. 

-      M Sedighimanesh, A Sedighimanesh, J Baqeri, “An improved LEACH-Algorithm for increasing Wireless Sensor Networks lifetime,” International Journal of Wireless & Mobile Networks (IJWMN), 2016.

-      M Sedighimanesh, A Sedighimanesh, J Baqeri, “Increase the lifetime of wireless sensor networks by minimizing energy consumption when selecting Cluster Head uses meta-heuristic algorithms,” International Journal of Computer Networks and Communications Security (IJCNCS), 2016.

-      M Sedighimanesh, A Sedighimanesh, J Baqeri, “Collect, study and preparation of standards for security and stability in desktop applications,” International Journal of Computer Networks and Communications Security (IJCNCS), 2016.

-      M Sedighimanesh, A Sedighimanesh, N Ashghaei, “The impact of self-service technology on customer satisfaction of online stores,” International Journal of Scientific & Technology Research, 2017.

-      A Sedighimanesh, M Sedighimanesh, N Ashghaei, “Studying the effect of brands and internet WOM advertisement on customer purchase,” International Journal of Scientific & Technology Research, 2017.

-      A Sedighimanesh, M Sedighimanesh, J Baqeri, “Improving wireless sensor network lifetime using layering in hierarchical routing,” 2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI), 2015.

 

Submitted for Publication:

-      Song Tingting, Mohammad Sedighimanesh, Ali Sedighimanesh, Saeed kosari, Jana Shafi, Mehdi Gheisari, Hemn Barzan Abdalla, Ahmad Jalili, Energy Consumption Improvement in Big Data Generated from IoT Sensor Networks Using an Ensemble Learning Model Based on Type-1 and Type-2 Fuzzy Logic and Genetic Algorithms

-       Huxiong Li, Ali Sedighimanesh, Mohammad Sedighimanesh, Mehdi Gheisari, Xiuqing Wang, Saeid Pirasteh, Cheng-Chi Lee, An optimal cluster-based routing protocol using TLBO with the learning experience of others for wireless sensornetworks

-      Mohammad Sedighimanesh, Ali Sedighimanesh, Mehdi Gheisari, Optimizing Hyperparameters for Customer Churn Prediction with PSO-Enhanced Composite Deep Learning Techniques