Lecturer and Researcher at Woldia University, Ethiopia.
Mr. Yitayal Siyoum is a dedicated mechanical engineering lecturer and incinerator engineer with a strong academic foundation and diversified research experience. Known for his analytical thinking, strong problem-solving skills, and commitment to innovation, he has developed a comprehensive background in manufacturing, additive manufacturing, and precision engineering. His career spans both academic and industrial environments, combining theoretical knowledge with practical expertise in materials science, CNC programming, and mechanical systems operation. As a lecturer at Woldia University, he teaches a variety of courses in manufacturing and industrial engineering while actively advising both undergraduate and master’s research projects. He also brings hands-on engineering experience from his work with UNOPS, where he was responsible for plant design, installation, and maintenance. His professional journey reflects a blend of technical excellence, teaching acumen, and research proficiency. With a passion for academic advancement, he is currently pursuing a Ph.D. at the University of Genova, Italy, with a proposed research focus on machine learning-driven modeling of metallic microstructures for energy systems. Mr. Siyoum is a proactive team player, an articulate communicator, and a dependable academician aiming to make meaningful contributions to the global engineering research community.
📝Publication Profile
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🎓Education
Mr. Yitayal Siyoum has pursued a progressive academic trajectory in mechanical and manufacturing engineering. He is currently undertaking a Doctor of Philosophy (Ph.D.) in Mechanical, Energy, and Management Engineering at the University of Genova, Italy (2025–2028). His research is conducted under the Department of Mechanical, Energetics, Management, and Transport Engineering, with a specialization in Processing Technologies and Systems. His proposed research focuses on machine learning–driven modeling of metallic microstructures for energy system state estimation—an interdisciplinary approach combining computational intelligence with advanced materials engineering. Prior to his doctoral studies, Mr. Siyoum completed a Master of Science in Mechanical (Manufacturing) Engineering at Bahir Dar University, Bahir Dar Institute of Technology, Ethiopia, from December 2020 to November 2022. His master’s thesis addressed the microstructural analysis and mechanical property optimization of bio-implant materials, utilizing wire-cut Electrical Discharge Machining (EDM) and Artificial Neural Networks (ANN) enhanced by advanced optimization algorithms including Jaya, Genetic, and Teaching–Learning-Based Algorithms. He also holds a Bachelor of Science in Mechanical (Manufacturing) Engineering from Debre Markos University, Ethiopia, completed in 2018. His academic foundation began with a comprehensive education in Natural Sciences at Shendi Secondary School in Womberma, Ethiopia, completed in 2013. His educational pathway reflects a consistent dedication to technical excellence and applied research.
💼Professional Experience
Mr. Yitayal Siyoum has a dynamic professional career that includes both academic and industrial roles. Since November 2022, he has served as a Lecturer and Researcher at Woldia University, Ethiopia, where he teaches undergraduate and graduate courses in manufacturing and industrial engineering. His teaching portfolio includes courses such as welding, metal forming, manufacturing systems, CAD/CAM/CIM, metrology, and materials handling. He actively supervises thesis work and guides students in project development.
From March 2019 to October 2020, he worked as an Assistant Lecturer at the same institution, providing instructional support in core engineering subjects like Engineering Dynamics and Workshop Practice. Prior to his academic career, Mr. Siyoum worked briefly as a Mechanical Engineer (Incinerator Engineer) at UNOPS, Ethiopia, from January to March 2019. In this role, he focused on the design, installation, and operation of plant machinery, contributing to public health through environmentally safe waste disposal systems.
His career demonstrates a balanced combination of theoretical teaching, laboratory management, and hands-on industrial engineering experience. His deep understanding of mechanical systems, manufacturing practices, and engineering education makes him a valuable contributor to both academia and industry.
🔬Research Interest
Mr. Yitayal Siyoum’s research interests are deeply rooted in advanced manufacturing technologies and engineering optimization. He is particularly focused on additive manufacturing, where he investigates design and fabrication strategies for creating sustainable materials. His work in this area includes the development of composite materials and small-scale 3D printing machines.
In precision manufacturing, he explores the automation of machining systems that function without human intervention while maintaining precise tolerance levels. His research also integrates machine learning algorithms to enhance adaptive machining, welding, and 3D printing processes, particularly for additive manufacturing applications.
Additionally, Mr. Siyoum is interested in the design and management of production processes, including life cycle assessments (LCA), sustainability analysis, and technical-economic feasibility studies for new products. His research extends to industrial quality, safety, and efficient process design, bridging academic theory with real-world applications.
Overall, his multidisciplinary interests aim to advance the field of mechanical engineering by leveraging computational tools, AI, and sustainable technologies. His academic path and project involvement demonstrate a strong commitment to addressing current and future challenges in advanced manufacturing systems.
Research Skills
Mr. Yitayal Siyoum has cultivated a comprehensive skill set in engineering research, particularly in the areas of manufacturing, materials science, and computational analysis. He is proficient in designing and conducting experimental studies in additive manufacturing, including the optimization of process parameters using machine learning and artificial neural networks (ANN).
He has hands-on experience with microstructure analysis, mechanical property evaluation, and composite material design. Mr. Siyoum also engages in precision machining studies, such as wire-cut EDM, and uses optimization algorithms including Genetic Algorithms, Jaya Algorithm, and Teaching Learning-based Optimization.
In computational and simulation work, he is skilled in tools such as AutoCAD, SolidWorks, Fusion 360, ANSYS, ProCAST, and Deform 3D. His coding experience includes MATLAB, C++, and basic Java, making him capable of modeling physical systems and developing simulation environments.
Moreover, his background in life cycle assessment (LCA), feasibility studies, and quality control gives him an applied perspective on industrial processes. Mr. Siyoum’s ability to plan, schedule, and meet research deadlines, combined with his teaching and supervisory experience, make him an effective researcher and academic collaborator.
🏆Awards and Honors
Mr. Yitayal Siyoum has demonstrated academic excellence throughout his educational journey, earning top marks and distinctions that reflect his diligence and expertise. He completed his Master of Science in Mechanical (Manufacturing) Engineering with an outstanding GPA of 3.92 out of 4.00 at Bahir Dar University. His high academic achievement is further evidenced by his Bachelor’s degree performance at Debre Markos University, where he graduated with a GPA of 3.59.
During his undergraduate and postgraduate studies, he actively participated in academic clubs, such as the Mechanical Engineering Club, and provided voluntary teaching assistance to community high school and preparatory students in mathematics and physics. He was also involved in mentoring junior university students in programming and technical drawing.
Mr. Siyoum has received recognition for his leadership, mentorship, and contribution to university-level applied research projects. His work in engineering education and hands-on internships has earned him commendations from colleagues and supervisors alike. These accolades reflect his strong moral character, commitment to service, and consistent pursuit of academic and professional excellence.
📈Author Metrics
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Total Documents Published: 4
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Total Citations: 3 (cited by 3 documents)
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h-index: 1 (The h-index of 1 indicates that at least 1 of the author’s publications has been cited at least once).
📌Publications Top Notes
1. A review of current research and prospects of fused deposition modelling: application, materials, performance, process variables, parameter optimization, and numerical study
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Authors: Yitayal Belew Siyoum, Fikir Gashaw Kindie & Mebratu Assefa Gebeyehu
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Year: 2025
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Journal: International Journal of Advanced Manufacturing Technology
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Citation: Siyoum Y. B., Kindie F. G., & Gebeyehu M. A. (2025). A review of current research and prospects of fused deposition modelling: application, materials, performance, process variables, parameter optimization, and numerical study. Int J Adv Manuf Technol, 138, 1675–1711.
2. Parameter optimization for enhancing mechanical properties of wood‑plastic composites using artificial neural network with genetic algorithm and Taguchi method
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Authors: Teshager Awoke Yeshiwas, Yitayal Belew Siyoum, Atalay Bayable Tiruneh & Tantigegn Kassahun Adamu
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Year: 2025
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Journal: Wood Materials Science & Engineering
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Citation: Yeshiwas T. A., Siyoum Y. B., Tiruneh A. B., & Adamu T. K. (2025). Parameter optimization for enhancing mechanical properties of wood‑plastic composites using artificial neural network with genetic algorithm and Taguchi method. Wood Mater Sci Eng.
3. Comparative optimization of wire‑cut EDM parameter for enhancing surface finish and machining time on stainless steel: a machine learning, genetic algorithms, teaching–learning based optimization, and multi-objective Jaya approach
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Authors: Yitayal Belew Siyoum, Fikir Gashaw Kindie, Mebratu Assefa Gebeyehu, Sewale Enyew Chanie, Teshager Awoke Yeshiwas & Yilkal Azene Zelalem
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Year: 2025
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Journal: International Journal of Advanced Manufacturing Technology
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Citation: Siyoum Y. B., Kindie F. G., Gebeyehu M. A., Chanie S. E., Yeshiwas T. A., & Zelalem Y. A. (2025). Comparative optimization of wire‑cut EDM parameter for enhancing surface finish and machining time on stainless steel: a machine learning, genetic algorithms, teaching–learning‑based optimization, and multi-objective Jaya approach. Int J Adv Manuf Technol, 137, 5339–5362.
4. Optimization of wire‑cut EDM parameters using artificial neural network and genetic algorithm for enhancing surface finish and material removal rate of charging handlebar machining from mild steel AISI 1020
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Authors: Sewale Enyew Chanie, Teshome Mulatie Bogale & Yitayal Belew Siyoum
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Year: 2025
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Journal: International Journal of Advanced Manufacturing Technology
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Citation: Chanie S. E., Bogale T. M., & Siyoum Y. B. (2025). Optimization of wire‑cut EDM parameters using artificial neural network and genetic algorithm for enhancing surface finish and material removal rate of charging handlebar machining from mild steel AISI 1020. Int J Adv Manuf Technol, 136, 3505–3523.
🧾Conclusion
Mr. Yitayal Siyoum stands out as a committed academician and researcher whose work bridges theoretical knowledge with practical innovation. His background in mechanical engineering—spanning additive manufacturing, precision machining, and machine learning—reflects a passion for addressing industrial and societal challenges through advanced technologies. As a lecturer, he excels in mentoring students and translating complex concepts into real-world applications. His research focus on sustainable material design and intelligent manufacturing systems positions him at the forefront of engineering advancement. Currently pursuing a Ph.D. at the University of Genova, he aims to deepen his understanding of metallic microstructures and energy systems through machine learning. His academic drive, collaborative spirit, and diverse skill set make him a strong candidate for research teams, academic collaborations, and interdisciplinary initiatives. Mr. Siyoum’s unwavering commitment to learning, innovation, and professional growth underscores his goal to contribute meaningfully to the engineering field and to society at large.