Wajid Ali | Technology Management | Emerging Research Star Award

Wajid Ali | Technology Management | Emerging Research Star Award

Lecturer at International Islamic University Islamabad Pakistan

Dr. Wajid Ali is an emerging scholar in Technology Management with an interdisciplinary background in engineering and management sciences. With a PhD in Management Sciences (Technology Management) from the International Islamic University, Islamabad (2025), Dr. Ali has made significant research contributions in the domain of Artificial Intelligence (AI) readiness, organizational performance, and innovation strategy. His scholarly work spans over seven peer-reviewed publications and systematic literature reviews, highlighting his deep commitment to bridging engineering principles with management innovation. Beyond academia, Dr. Ali’s professional journey includes hands-on industrial experience in mechanical maintenance and instructional roles in top Pakistani universities. His blend of academic prowess and technical expertise makes him a rising leader in AI-based transformation in public and private sectors. A strong advocate for interdisciplinary growth, he continues to contribute to research and teaching that advances technology-driven management solutions for emerging economies.

Publication Profile

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Education

Dr. Wajid Ali holds a Ph.D. in Management Sciences with a focus on Technology Management from the International Islamic University, Islamabad (2025), where he maintained a CGPA of 3.50/4.00. He earned his MS in Engineering Management from The University of Lahore in 2019 with a CGPA of 3.40/4.00 and a B.Sc. in Mechanical Engineering & Technology in 2016. Earlier, he completed a D.A.E in Mechanical Technology from the Punjab Board of Technical Education in 2012 with a commendable 75% and received a Diploma in Computer Science in 2011 with an 81% score. He also cleared the Class Three Boiler Engineer examination in 2018 and obtained his SSC (Science Group) in 2009. This solid academic foundation across engineering, management, and computing reflects Dr. Ali’s diverse capabilities and underpins his research in AI-driven technological innovation and efficiency in organizations.

Experience

Dr. Wajid Ali has over six years of professional experience blending academia and industry. He has served as a visiting lecturer at the International Islamic University Islamabad and Fatima Jinnah Women’s University Rawalpindi for two years, where he taught across Management Sciences, Engineering, and Social Sciences. His responsibilities extended to administrative duties, test supervision, seminar organization, and curriculum planning. Additionally, Dr. Ali boasts 3 years and 8 months of practical experience as a mechanical maintenance technician. His industrial tenure includes critical outage projects at renowned power plants like Kot Addu Power Company (KAPCO), Roush Power Plant, Fuji Kabir Wala Power Plant, and others. From 2016 to 2018, he was engaged in operational and maintenance roles at SKAIKHU Sugar Mills LTD. His internships at KAPCO and GENCO-3 further enriched his engineering experience. This multidisciplinary exposure shapes his innovative and grounded research in AI readiness and performance optimization.

Awards and Honors

While formal awards have not been explicitly listed in his profile, Dr. Wajid Ali’s rapid progression through academic ranks, strong publication record, and diverse professional experience are indicative of his emerging stature in the field of technology management research. He has gained recognition through publication in reputed journals such as Data Science and Management, Journal of Business and Management Research, and International Journal of Business and Management Sciences. His contribution as a co-author in collaborative research projects reflects his growing academic network and influence. His teaching roles at top institutions and involvement in cross-functional academic initiatives also highlight institutional trust in his expertise. Given his Ph.D. completion in 2025 and multiple publications during the doctoral phase, Dr. Ali is a compelling candidate for the Emerging Research Star Award, which aims to celebrate promising early-career researchers who demonstrate leadership and innovation potential.

Research Focus

Dr. Wajid Ali’s research centers on Artificial Intelligence (AI) Readiness, Technology Management, and Organizational Performance. His investigations aim to uncover how public sector and transformational organizations can strategically prepare for and leverage AI integration. Through expert surveys, literature reviews, and empirical models, he explores critical success factors influencing AI adoption, cost efficiency, and the mediating role of control systems. His work also delves into emotional intelligence, team dynamics, and their impact on project success—bridging human factors with technological transitions. Dr. Ali’s interdisciplinary approach combines engineering management tools with data-driven strategic planning. His growing body of work addresses both theoretical frameworks and practical challenges facing institutions undergoing digital transformation. As organizations worldwide increasingly adopt AI, Dr. Ali’s research offers timely, actionable insights into readiness metrics, cost control, and innovative strategies that optimize performance in both emerging and established economies.

Publication Top Notes

Laws Governed Role Of Artificial Intelligence And Machine Learning In Supply Chain Management

Factors influencing readiness for artificial intelligence: a systematic literature review

THE DETERMINANTS OF CONSUMERS’ONLINE SHOPPING BEHAVIOUR: AN EMPIRICAL ASSESSMENT

Empowering Small and Medium Enterprises Performance Through Dynamic Marketing Strategies and Innovations

The influence of emotional intelligence and team building on project success

Exploring Artificial Intelligence Readiness Framework for Public Sector Organizations: An Expert Opinion Methodology

Assessment of community perceptions on drinking water quality and its implications for human health in Islamabad, Pakistan: A comprehensive analysis

Critical Artificial Intelligence Readiness Factors in Context of Public Sector Organizations: An Expert Opinion Survey

Sandeep Jain | Engineering and Technology | Best Researcher Award

Sandeep Jain | Engineering and Technology | Best Researcher Award

Dr Sandeep Jain, Sungkyunkwan University, Republic of Korea, South Korea

Dr. Sandeep Jain is a metallurgical engineer and researcher with expertise in machine learning applications in alloy design, lightweight materials, and high-entropy alloys. He holds a Ph.D. (2023) and M.Tech. (2017) from IIT Indore and a B.E. in Mechanical Engineering (2013). Currently a Postdoctoral Researcher at Sungkyunkwan University, South Korea, Dr. Jain focuses on designing multicomponent alloys and optimizing manufacturing processes. He has published extensively, including works on machine learning-driven phase prediction and flow stress modeling. Dr. Jain is a guest editor, reviewer for leading journals, and recipient of prestigious awards like the Global Best Achievement Award 2024. 🧪🤖🌍

Publication Profile

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Education

Dr. Sandeep Jain is a dedicated scholar with a robust academic background in engineering. 🎓 He earned his Ph.D. (2017-2023) and M.Tech (2015-2017) in Metallurgical Engineering and Materials Science from the prestigious Indian Institute of Technology Indore, achieving impressive CGPAs of 8.67 and 8.75, respectively. 📘✨ His journey in engineering began with a B.E. in Mechanical Engineering from MBM Engineering College, Jodhpur (2009-2013), where he secured a commendable 68% score. 🔧📚 Dr. Jain’s academic excellence reflects his passion for materials science and mechanical engineering, laying a solid foundation for impactful contributions to his field. 🚀🔬

Research Experience

Dr. Sandeep Jain, currently a Postdoctoral Researcher at Sungkyunkwan University, South Korea 🇰🇷, specializes in designing lightweight multicomponent alloys and optimizing injection molding processes using machine learning 🤖. As a Research Associate at IIT Delhi 🇮🇳, he analyzed the mechanical and creep behavior of Ni-based superalloys and pioneered sustainable rose gold plating methods 🌟. His tenure at IIT Indore included designing lightweight Ni-based alloys and conducting advanced phase equilibria studies 🔬. Dr. Jain’s expertise extends to simulation tools like ANSYS Fluent, XRD, and EBSD, contributing to innovative and sustainable material development 🌍.

Teaching Experience

Dr. Sandeep Jain has an extensive teaching background in materials science and engineering. As a Teaching Assistant at the Indian Institute of Technology Indore (Dec 2017–Nov 2022 and July 2015–June 2017), he contributed to courses like Solidification and Phase Field Modelling, Computational Methods for Materials, and Physical Metallurgy. His expertise also spans practical modules, including Mechanical Workshop, Casting and Welding Lab. Earlier, he served as a Guest Faculty at Govt. Engineering College, Ajmer (Aug 2013–June 2014), teaching Material Science, Engineering Mechanics, Strength of Materials, and more. Dr. Jain’s dedication to education blends technical knowledge with hands-on experience. 🎓🛠️📚

Awards / Fellowships

Dr. Sandeep Jain has earned prestigious accolades for his outstanding achievements in academia and research. In 2024, he was honored with the Global Best Achievement Awards 🎖️🌟, recognizing his contributions to his field. His academic journey has been supported by prestigious fellowships, including the Ph.D. Fellowship 🧑‍🎓📚 and the M.Tech. Fellowship 🎓🔬, both awarded by the Ministry of Human Resource Development (MHRD), Government of India. These honors highlight his dedication, innovation, and excellence in advancing knowledge and contributing to societal progress. Dr. Jain’s achievements continue to inspire and set benchmarks for aspiring scholars worldwide. 🚀📖

Research Focus

Dr. Sandeep Jain’s research focuses on the development and application of machine learning techniques to predict mechanical properties in lightweight alloys and high entropy alloys. His studies include hardness prediction, flow stress, phase prediction, and the influence of processing methods like friction stir processing. These investigations aim to enhance the performance of advanced materials such as Al-Mg-based alloys and CoCrFeNiV high entropy alloys. His work bridges the gap between experimental studies and computational simulations, contributing valuable insights into alloy design and optimization. 🌟🔍📊

Publication Top Notes

A Machine Learning Perspective on Hardness Prediction in Advanced Multicomponent Al-Mg Based Lightweight Alloys