Student at OUTR, india

Anuradha Rani Choudhury is a dedicated and aspiring researcher currently pursuing her Master of Technology at OUTR, Bhubaneswar, with an impressive CGPA of 9.20. She holds a Bachelor’s degree in Technology from ITER, Bhubaneswar, and has demonstrated strong technical acumen through impactful projects in machine learning, including sentiment analysis and disease prediction models, both achieving high accuracy. With certifications in machine learning, web development, and Android development, she exhibits a strong foundation in diverse technological domains. Anuradha has actively participated in seminars and workshops, showcasing her commitment to continuous learning. Her proficiency in programming languages such as Python, Java, and C, along with web technologies, complements her research skills. Additionally, her involvement in extracurricular activities like sports, NCC, and student leadership reflects a well-rounded personality. While she is at an early stage in her research journey, Anuradha shows promising potential for future contributions to the field of technology and applied sciences.

Professional Profile

🎓 Education of Anuradha Rani Choudhury

Anuradha Rani Choudhury has built a strong academic foundation in the field of technology and engineering. She is currently pursuing her Master of Technology (M.Tech) at Odisha University of Technology and Research (OUTR), Bhubaneswar, maintaining an excellent CGPA of 9.20 (2023–2025). She previously earned her Bachelor of Technology (B.Tech) from ITER, Bhubaneswar, graduating with a CGPA of 7.73 in 2022. Her earlier academic journey includes completing 12th grade (Science) from Stewart Science College, Cuttack under the CHSE Board, scoring 57.5%, and her 10th grade from D.A.V. Public School, Berhampur under the CBSE Board, where she achieved a commendable 83.6%. Her academic progression highlights her consistent dedication and growth in technical education.

💼 Professional Experience of Anuradha Rani Choudhury

Anuradha Rani Choudhury has gained valuable hands-on experience through academic projects and certified training programs in the fields of machine learning, data science, and software development. She successfully led a Sentiment Analysis project in 2024, where she implemented advanced models such as Naïve Bayes, Logistic Regression, SVM, and Neural Networks, achieving an outstanding . In 2023, she developed a Disease Prediction Model using patient physiological data, which delivered an impressive . Additionally, Anuradha has completed certification-based training in Machine Learning (Project Mantra), Web Development (Verzeo), and Android Development (Pixaflip Technologies). Her participation in workshops and seminars, along with her technical proficiency in languages like Python, Java, and SQL, further reflects her readiness for research and real-world problem-solving in the tech industry.

🔬 Research Interest of Anuradha Rani Choudhury

Anuradha Rani Choudhury’s research interests lie primarily in the dynamic fields of Machine Learning, Artificial Intelligence, and Data Science, with a strong inclination toward applying these technologies in healthcare and human-centered applications. She is passionate about exploring predictive modeling, sentiment analysis, and disease diagnosis systems that leverage advanced algorithms to generate actionable insights from complex data. Her academic projects reflect her enthusiasm for building intelligent systems capable of improving decision-making and automation. Anuradha is also interested in the integration of deep learning and neural networks to enhance model accuracy and efficiency. As she progresses in her academic and professional journey, she aims to contribute to impactful, real-world solutions through innovative and ethically grounded research in intelligent technologies.

🏅 Awards and Honors of Anuradha Rani Choudhury

Anuradha Rani Choudhury has been recognized for her diverse talents and active participation in both academic and extracurricular arenas. She earned the 2nd prize in poem writing at the Ganjam Kalaparishad in 2017, showcasing her creative expression and literary flair. In the same year, she also secured the 2nd prize in athletics at D.A.V. Public School, reflecting her athletic spirit and commitment to physical excellence. Additionally, she holds the prestigious NCC “A” Certificate (2013–2015), highlighting her discipline, leadership, and dedication to national service. These honors demonstrate her well-rounded personality, balancing academic rigor with artistic and physical achievements.

Conclusion

Anuradha Rani Choudhury is a promising emerging researcher with a solid academic background, project experience in machine learning, and proactive engagement in technical skill development. However, to be highly competitive for the Best Researcher Award, particularly at national or international levels, she would benefit from Publishing research papers. Involving in long-term, original research with measurable impact. Demonstrating broader research influence and leadership.

📚 Publications Top Noted

Title: Real-time Face Mask Detection in Nuclear Power Plants: A Deep Learning Framework Using Hybrid CNN-MobileNetV2 Architecture
Authors: S.R. Panda, A.R. Choudhury, A.K. Mishra, S. Mohanty, S. Mishra
Year: 2025
Citation: 0
Published In: Intelligent Computing Techniques and Applications, pp. 87–91
Title: A Comparative Analysis of Deep Learning Techniques for Face Mask Detection System in Nuclear Power Plant
Authors: S.R. Panda, A.R. Choudhury, A.K. Mishra
Year: 2025
Citation: 0
Published In: 2025 10th International Conference on Signal Processing and Communication
Title: Enhancing Lung Cancer Detection by Leveraging Machine Learning Algorithms
Authors: A.R. Choudhury, S.R. Panda, A.K. Mishra, J. Routray
Year: 2025
Citation: 0
Published In: 2025 10th International Conference on Signal Processing and Communication
Title: Deep Learning Based Automated Lung Cancer Detection from CT Scan Leveraging Transfer Learning
Authors: A.R. Choudhury, J. Rautray, P. Mishra, M. Kandpal, S.S. Dalai
Year: 2025
Citation: 0
Published In: Procedia Computer Science, Volume 258, Pages 2748–2759
Title: Face Mask Detection System for Safety Assurance in Nuclear Power Facilities from Harmful and Hazardous Substance Using Convolutional Neural Network and Image Processing
Authors: S.R. Panda, A.R. Choudhury, A.K. Mishra
Year: 2025
Citation: 0
Published In: International Journal of Computer Applications 975, 8887

Denesh Sooriamoorthy | Engineering and Technology | Best Researcher Award

Posted on 24/06/202524/06/2025 by Research Hypothesis

Dr. Denesh Sooriamoorthy | Engineering and Technology | Best Researcher Award

Senior Lecturer at Asia Pacific University of Technology & Innovation (APU), Malaysia

Ir. Ts. Dr. Denesh Sooriamoorthy is a dynamic early-career researcher and Senior Lecturer at the Asia Pacific University of Technology & Innovation (APU), Malaysia. With a Ph.D. in Engineering from the University of Nottingham, his research expertise spans electric vehicle battery systems, biomedical signal processing, artificial intelligence, and robotics. Despite having only three years of post-PhD experience, Dr. Denesh has already published over 25 Scopus-indexed papers—including five in Q1 journals—authored and edited academic books, and secured research funding exceeding RM775,000. He maintains an impressive citation record (h-index of 9 on Google Scholar and 8 on Scopus) and actively supervises multiple postgraduate students. His work bridges academia and industry through innovative projects and collaborative initiatives, reflecting a commitment to impactful, interdisciplinary research.

Professional Profile

🎓 Education of Denesh Sooriamoorthy

Dr. Denesh Sooriamoorthy has a strong academic foundation rooted in engineering and education. He earned his Ph.D. in Engineering from the prestigious University of Nottingham in 2022, where he focused on cutting-edge research in biomedical systems and intelligent technologies. Prior to that, he completed his Master of Engineering (MEng Hons.) in Mechatronic Engineering, graduating with First Class Honours from the same university in 2016. To further enhance his academic and pedagogical skills, he obtained a Postgraduate Certificate in Teaching and Learning from Taylor’s University Malaysia in 2022. His academic journey reflects a commitment to both technical excellence and educational innovation.

💼 Professional Experience of Denesh Sooriamoorthy

Dr. Denesh Sooriamoorthy has rapidly built a distinguished professional career in academia and research. He is currently serving as a Senior Lecturer at the Asia Pacific University of Technology & Innovation (APU) since September 2023, where he contributes to teaching, research, and postgraduate supervision. Prior to this role, he was a Lecturer and Work-Based Learning (WBL) Coordinator at Taylor’s University Malaysia from January 2021 to August 2023. In these roles, Dr. Denesh played a vital part in integrating industry-driven education models and advancing applied research initiatives. His experience also includes mentoring students, managing interdisciplinary projects, and fostering academic-industry partnerships—showcasing a strong blend of leadership, innovation, and academic excellence at an early stage of his career.

🔬 Research Interests of Denesh Sooriamoorthy

Dr. Denesh Sooriamoorthy’s research interests lie at the intersection of engineering intelligence, biomedical systems, and sustainable technologies. He is particularly focused on electric vehicle battery management systems, with a specialization in state of charge estimation using machine learning and neural networks. His work also delves into biomedical signal processing, notably the use of electrical impedance models for non-invasive cardiovascular diagnostics. In addition, Dr. Denesh is actively engaged in robotics, artificial intelligence, and multi-agent systems, aiming to solve real-world problems through smart automation and predictive analytics. His interdisciplinary approach integrates AI, mechatronics, and embedded systems, driving innovations in healthcare, energy storage, and intelligent transportation.

🏆 Awards and Honors of Denesh Sooriamoorthy

Dr. Denesh Sooriamoorthy has garnered notable recognition for his impactful contributions to research and academia. While still in the early stages of his career, he has successfully secured multiple prestigious research grants totaling over RM775,000 from renowned bodies such as CREST, MRANTI, Katapult Asia, and APU RDIG, reflecting trust in his innovative capabilities and leadership potential. His publications in high-impact Q1 journals, coupled with active roles in book authorship and editorial contributions, further underscore his academic excellence. In addition, his appointment as Work-Based Learning (WBL) Coordinator at Taylor’s University highlights institutional acknowledgment of his educational leadership. These achievements position Dr. Denesh as a promising and respected figure in the engineering and research community.

🧾 Conclusion

Ir. Ts. Dr. Denesh Sooriamoorthy is highly suitable for the Best Researcher Award (Early-Career Category). His rapid research productivity, Q1 journal contributions, funding success, and graduate supervision demonstrate excellence in research, academic leadership, and industry engagement.

📚 Publications Top Noted

Title: Artificial Neural Networks, Gradient Boosting and Support Vector Machines for Electric Vehicle Battery State Estimation: A Review
Authors: A. Manoharan, K.M. Begam, V.R. Aparow, D. Sooriamoorthy
Year: 2022
Citations: 227
Title: Electric Vehicle Battery Pack State of Charge Estimation Using Parallel Artificial Neural Networks
Authors: A. Manoharan, D. Sooriamoorthy, K.M. Begam, V.R. Aparow
Year: 2023
Citations: 91
Title: A Novel Electrical Impedance Function to Estimate Central Aortic Blood Pressure Waveforms
Authors: D. Sooriamoorthy, S.A. Shanmugam, M.A. Juman
Year: 2021
Citations: 72
Title: A Study on the Effect of Electrical Parameters of Zero-Dimensional Cardiovascular System on Aortic Waveform
Authors: D. Sooriamoorthy, A.L.H. Wee, A. Shanmugam, K.J. Ghee, P.C. Ooi, M. Nafea
Year: 2020
Citations: 29
Title: A Study on Transfer Function to Estimate the Central Aortic Blood Pressure Waveform
Authors: B.V. Leonard, D. Sooriamoorthy
Year: 2023
Citations: 27
Title: Performance Analysis on Artificial Neural Network Based State of Charge Estimation for Electric Vehicles
Authors: M. Aaruththiran, K.M. Begam, V.R. Aparow, D. Sooriamoorthy
Year: 2021
Citations: 26
Title: Study on Artificial Neural Network Optimization for Electric Vehicle Battery State of Charge Estimation
Authors: A. Manoharan, K.M. Begam, D. Sooriamoorthy, V.R. Aparow
Year: 2023
Citations: 21
Title: A Homogeneous Meta-Learning LSTM-RNN Ensemble Method for Electric Vehicle Battery State of Charge Estimation
Authors: R.H. Wong, A. Manoharan, D. Sooriamoorthy, N.B. Sarif
Year: 2023
Citations: 21
Title: Multi-Agent Robot Motion Planning for Rendezvous Applications in a Mixed Environment with a Broadcast Event-Triggered Consensus Controller
Authors: N. Sariff, Z.H. Ismail, A.S.H.M. Yasir, D. Sooriamoorthy, P.N.A.F.S. Mahadzir
Year: 2023
Citations: 16
Title: Balancing Accuracy and Efficiency: A Homogeneous Ensemble Approach for Lithium-Ion Battery State of Charge Estimation in Electric Vehicles
Authors: R.H. Wong, D. Sooriamoorthy, A. Manoharan, N. Binti Sariff, Z. Hilmi Ismail
Year: 2024
Citations: 3

Wajid Ali | Technology Management | Emerging Research Star Award

Posted on 30/05/202530/05/2025 by Research Hypothesis

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

Google Scholar

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

Jari Kaivo-oja | Tech Innovations | Excellence in Research Award

Posted on 19/05/202519/05/2025 by Research Hypothesis

Jari Kaivo-oja | Tech Innovations | Excellence in Research Award

Prof. Dr Jari Kaivo-oja, University of Turku, Finland

Prof. Dr. Jari Kaivo-oja is a globally recognized expert in foresight, innovation, and sustainable development. Currently serving as Research Director at the Finland Futures Research Centre (University of Turku) and Professor at Kazimieras Simonavičius University, Lithuania, he is widely respected for his multidisciplinary research impact. With more than two decades of academic leadership, Dr. Kaivo-oja has advanced the understanding of futures studies, digital transformation, and strategic sustainability. His work bridges theory and practice, offering critical insights for public policy, industry innovation, and academic strategy. He has been involved in European Commission initiatives and has significantly influenced regional innovation systems. Known for integrating socio-economic foresight with actionable frameworks, his thought leadership guides both academic and practical change. Dr. Kaivo-oja’s scholarship is evidenced by numerous high-impact publications, awards, and global collaborations. His visionary approach makes him a fitting and distinguished nominee for the Excellence in Research Award.

Publication Profile

Google Scholar

Orcid

Scopus

Education

Dr. Kaivo-oja’s academic foundation is built on a strong interdisciplinary background. He earned his Doctorate in Administrative Sciences from the University of Tampere, focusing on policy foresight and regional development. He also holds a Licentiate of Administrative Sciences, and a Master’s degree in Regional Science and International Economics, integrating economic theory with public administration and innovation management. Additionally, he completed specialized postgraduate studies in Development Studies, expanding his competence in global socio-economic challenges and policy dynamics. His academic training equips him to analyze complex systems involving governance, technology, and sustainability. His educational journey reflects a persistent pursuit of excellence and relevance, aligning academic theory with real-world impact. These diverse academic credentials form the backbone of his comprehensive and integrative research approach, enabling him to effectively lead interdisciplinary projects and provide strategic foresight to governments, academia, and industry alike.

Experience

With over 25 years of research and academic leadership, Prof. Kaivo-oja has contributed extensively to European and international science and policy communities. As Research Director at the Finland Futures Research Centre, he leads projects on foresight, green transition, and socio-economic transformation. He also serves as a Research Professor at Kazimieras Simonavičius University, Lithuania, and Adjunct Professor at the University of Vaasa, specializing in technology foresight and digitalization. Dr. Kaivo-oja has been a policy advisor and research partner for high-level institutions including the European Commission, Nordic Innovation Centre, OECD, and Finnish Innovation Fund (Sitra). He has successfully led numerous foresight studies, policy planning efforts, and scenario-based strategies. His collaborations span academia, public administration, and industry, promoting systems thinking and knowledge transfer. His ability to connect theoretical insights with practical implementation has made him a sought-after expert in strategic foresight and innovation systems.

Awards and Honors

Prof. Dr. Kaivo-oja has received numerous recognitions that underscore his outstanding research and scholarly impact. He was honored with the Promising Young Economist Scholarship early in his career, reflecting his innovative contributions to regional science. His scholarly publications have earned prestigious accolades such as the ISPIM Best Paper Award and the Emerald Literati Network Award for Excellence, recognizing exceptional academic publishing. In 2023, he received the AIRA (Academy of International Research Awards) honor for outstanding contributions in foresight and innovation. Additionally, he has been celebrated multiple times by the University of Turku with the Active Publisher Award, acknowledging consistent high-quality research output. These accolades reflect his sustained academic excellence, thought leadership, and international reputation. Each award represents a milestone in a career marked by interdisciplinary breakthroughs and practical applications of research, reinforcing his candidacy for the Excellence in Research Award.

Research Focus

Prof. Kaivo-oja’s research agenda bridges foresight studies, innovation management, and sustainable development. His work advances the understanding of long-term socio-economic transformation by integrating digitalization, ecological economics, and strategic planning. A central focus lies in developing tools and models for anticipatory governance, policy foresight, and resilient innovation systems. He applies these methodologies across areas such as climate change adaptation, regional competitiveness, and entrepreneurial ecosystems. With a systems-theoretical approach, his studies generate practical foresight for governments, cities, and corporations navigating uncertain futures. He is also a pioneer in combining weak signal analysis, Delphi methods, and scenario planning to guide strategic decisions in volatile environments. His integrative foresight methodologies support transitions to more sustainable, inclusive, and digitally driven societies. Prof. Kaivo-oja’s contributions continue to shape both academic discourse and real-world policies, positioning him at the forefront of transformative research with global relevance.

Publication Top Notes

Wild cards, weak signals and organisational improvisation

Human factors and ergonomics in manufacturing in the industry 4.0 context–A scoping review

Technological turbulence and greening of team creativity, product innovation, and human resource management: Implications for sustainability

Evaluating synergies and trade-offs among Sustainable Development Goals (SDGs): Explorative analyses of development paths in South Asia and Sub-Saharan Africa

The VUCA approach as a solution concept to corporate foresight challenges and global technological disruption

Linking analyses and environmental Kuznets curves for aggregated material flows in the EU

Relationships of the dimensions of sustainability as measured by the sustainable society index framework

Khalifa Aliyu Ibrahim | Engineering and Technology | Best Researcher Award

Posted on 21/03/202521/03/2025 by Research Hypothesis

Khalifa Aliyu Ibrahim | Engineering and Technology | Best Researcher Award

Mr Khalifa Aliyu Ibrahim, Cranfield University, United Kingdom

Mr. Kamilu A. Ibrahim is a dedicated researcher and academic with expertise in AI-driven high-frequency power electronics. Currently pursuing a PhD at Cranfield University, he has a strong background in physics, energy, and power systems. His research focuses on sustainable energy solutions, incorporating artificial intelligence and machine learning. With numerous publications in reputable journals and conferences, Mr. Ibrahim has made significant contributions to renewable energy, hydrogen systems, and power electronics. His academic career includes roles as a lecturer and research assistant, demonstrating his passion for knowledge dissemination. Recognized for his excellence, he has received prestigious scholarships and awards.

Publication Profile

Google Scholar

Education

Mr. Kamilu A. Ibrahim is currently pursuing a PhD in AI-driven design of high-frequency power electronics at Cranfield University, where he explores innovative approaches to sustainable energy and power systems. He previously earned a Master of Science in Energy Systems and Thermal Processes from Cranfield University (2020-2021), gaining expertise in energy efficiency, renewable energy, and thermal management. Further advancing his research skills, he completed a Master’s by Research (M.Res.) in Energy and Power (2022-2023), focusing on advanced power systems and their optimization. His academic journey began with a Bachelor of Science in Physics from Kaduna State University (2013-2016), where he built a strong foundation in physical sciences and energy applications. Throughout his education, Mr. Ibrahim has demonstrated a commitment to innovation in power electronics, artificial intelligence, and sustainable energy solutions. His multidisciplinary background equips him with the technical and analytical skills essential for driving advancements in renewable energy and intelligent power systems. 🎓⚡🔋

Experience

Mr. Kamilu A. Ibrahim has a strong background in research, teaching, and project management, with a focus on power systems, renewable energy, and AI applications. Since 2022, he has been working as a Research Assistant at Cranfield University, contributing to cutting-edge studies in AI-driven high-frequency power electronics. Prior to this, he served as a Lecturer at Kaduna State University from 2021 to 2022, where he taught physics and energy-related courses while mentoring students in research projects. From 2020 to 2021, he was a Lecturer at Nuhu Bamalli Polytechnic, Zaria, where he played a key role in curriculum development and academic instruction in energy systems. Throughout his career, Mr. Ibrahim has combined his expertise in energy and artificial intelligence to drive innovation in sustainable energy solutions. His experience spans teaching, publishing research in top-tier journals, and collaborating on interdisciplinary projects, making significant contributions to the advancement of renewable energy technologies.

Awards and Honors

Mr. Kamilu A. Ibrahim has been recognized for his academic excellence and research contributions through several prestigious awards and honors. He received the Petroleum Technology Development Fund Scholarship (2021), a highly competitive award supporting outstanding researchers in energy and power systems. In 2020, he was also honored with the Merit-based Foreign Scholarship, which enabled him to pursue advanced studies in energy systems and AI-driven power electronics. In addition to these distinguished scholarships, Mr. Ibrahim has earned multiple certificates of completion from various specialized training programs, focusing on sustainable energy, artificial intelligence applications in power systems, and cutting-edge advancements in high-frequency electronics. His commitment to continuous learning and innovation has positioned him as a leader in his field, contributing significantly to research in renewable energy, hydrogen storage, and machine learning applications. These achievements underscore his dedication to academic excellence and groundbreaking contributions to the future of energy technologies.

Publication Top Notes

📊 Revolutionizing Power Electronics Design Through Large Language Models: Applications and Future Directions (2024)
🌊 Floating Solar Wireless Power Transfer System for Electric Ships: Design and Laboratory Tests (2025)
🔋 Harnessing Energy for Wearables: A Review of Radio Frequency Energy Harvesting Technologies (2023)
☀️ The Effect of Solar Irradiation on Solar Cells (2019)
🌡️ Cooling of Concentrated Photovoltaic Cells—A Review and the Perspective of Pulsating Flow Cooling (2023)
🌱 High-Performance Green Hydrogen Generation System (2021)
⚗️ Advancing Hydrogen: A Closer Look at Implementation Factors, Current Status, and Future Potential (2023)
📡 Survey and Assessment of Radiation Levels Associated with Mobile and Wireless Telecommunication Mast in Residential and Office Areas within Kaduna Metropolis (2019)
🚀 Decision Support System for Sustainable Hydrogen Production: Case Study of Saudi Arabia (2025)
🛢️ Measurements of Pour Points, Flash Points, Water Contents, and Viscosity of Some Selected Automobile Oils Used as Lubricants in Nigeria (2022)

Jiantao Shi | Robotics and Automation | Best Researcher Award

Posted on 07/03/202507/03/2025 by Research Hypothesis

Jiantao Shi | Robotics and Automation | Best Researcher Award

Mrs Jiayun Nie, chongqing Jiaotong University, China

Jiayun Nie is a distinguished professor at Nanjing Tech University, China, specializing in cooperative control of multi-robot systems, fault diagnosis, and fault-tolerant control of distributed systems. 📡 With a Ph.D. in Control Science and Engineering from Tsinghua University, she has made pioneering contributions to multi-agent systems, UAV adaptive control, and reinforcement learning-based fault diagnosis. ✈️🔍 Her research has led to high-impact publications on fault estimation, bipartite consensus, and deep learning models for system diagnostics. 🤖 She has served as a research fellow at the Nanjing Research Institute of Electronic Technology and has received recognition as an Outstanding Reviewer for the Journal of the Franklin Institute (2017). 📚 Her latest work explores AI-driven fault-tolerant frameworks for autonomous systems and aerospace applications. 🚀 With a stellar academic record and transformative research, she is a deserving recipient of the Best Researcher Award. 🏅

Publication Profile

Orcid

Education

Jiayun Nie’s academic journey is marked by excellence in control science and automation engineering. She earned her Ph.D. in Control Science and Engineering from Tsinghua University (2011-2016), focusing on fault-tolerant systems and adaptive control strategies for multi-robot cooperation. 🤖🔍 Her doctoral research introduced novel iterative learning algorithms for fault estimation and compensation, improving system reliability. Before this, she completed her B.E. in Electrical Engineering and Automation at Beijing Institute of Technology (2007-2011), where she laid the groundwork in robotic control, embedded systems, and automation engineering. 🎛️⚡ During her studies, she was actively involved in research projects on UAV dynamics and cooperative control theory, leading to early publications and innovative designs for fault-resilient robotics. 🚀 Her strong educational foundation, combined with rigorous research, has positioned her as a global leader in fault diagnosis and control engineering. 📚

Experience

Jiayun Nie has an extensive academic and research career, currently serving as a Professor at Nanjing Tech University (2021-present), where she leads groundbreaking work on distributed control and autonomous systems. 🤖🔍 Prior to this, she was a Research Fellow (2019-2021) and Associate Research Fellow (2016-2018) at the Nanjing Research Institute of Electronic Technology, contributing to fault detection models for phased array radar transceivers and advanced control strategies for UAVs. ✈️📡 Her expertise in adaptive control and AI-driven fault detection has been instrumental in developing next-generation intelligent robotic networks. 🚀 Throughout her career, she has collaborated with leading research institutions, advancing the state-of-the-art in reinforcement learning-based fault diagnosis, consensus control, and multi-agent fault-tolerant frameworks. 🏅 Her work continues to influence aerospace, robotics, and autonomous vehicular technologies, making her an authority in the field. 📚

Awards and Honors

Jiayun Nie’s outstanding contributions to robotics and fault-tolerant control have earned her several prestigious accolades. 🎖️ She was recognized as an Outstanding Reviewer for the Journal of the Franklin Institute (2017) 📚, reflecting her expertise in control systems and automation engineering. 🚀 Her innovative research on fault diagnosis in distributed robotic systems has been cited extensively, leading to multiple best paper awards at international IEEE and IFAC conferences. 🏅 She has received multiple grants and funding awards for her pioneering work in multi-agent cooperative control and AI-driven adaptive learning control. 🤖 As a highly regarded professor and researcher, her contributions continue to impact autonomous systems, aviation safety, and smart robotics. ✈️ With her extensive publications and transformative research, she is a deserving recipient of the Best Researcher Award, recognized for her excellence in innovation and scientific advancement. 🏆📡

Research Focus

Jiayun Nie’s research revolves around cooperative control, fault diagnosis, and learning-based fault-tolerant strategies in autonomous systems. 🤖 She has made significant breakthroughs in multi-robot cooperation, bipartite consensus, and AI-driven adaptive fault detection. 📊 Her work in fault-tolerant control enhances resilience in UAVs and aerospace systems, ensuring robustness against unknown disturbances and failures. ✈️ She has developed deep learning and reinforcement learning models for self-healing robotic networks, transforming distributed control frameworks. 🏅 Her studies in event-based control, collision avoidance, and system stability have contributed to advancements in autonomous vehicle technology. 🚀 By integrating data-driven methods with real-time fault estimation, her research provides solutions for smart transportation, defense, and aerospace industries. 📡 With numerous high-impact publications, Jiayun Nie’s pioneering work defines the future of adaptive robotics and autonomous systems. 🎓

Publications Top Notes

“A parallel weighted ADTC-Transformer framework with FUnet fusion and KAN for improved lithium-ion battery SOH prediction” 🔋 (2025)
“Bipartite Fault-Tolerant Consensus Control for Multi-Agent Systems with a Leader of Unknown Input Under a Signed Digraph” 🤖 (2025)
“Iterative learning based fault estimation for stochastic systems with variable pass lengths and data dropouts” 📊 (2025)
“A Two-Stage Fault Diagnosis Method With Rough and Fine Classifiers for Phased Array Radar Transceivers” 📡 (2024)
“An intuitively-derived decoupling and calibration model to the multi-axis force sensor using polynomials basis” 📊 (2024)
“Event-Based Adaptive Fault Tolerant Control and Collision Avoidance of Wheel Mobile Robots With Communication Limits” 🤖 (2024)
“Reinforcement Learning-Based Fault Tolerant Control Design for Aero-Engines With Multiple Types of Faults” ✈️ (2024)

Ebrahim Farrokh | Engineering and Technology | Best Researcher Award

Posted on 06/03/202506/03/2025 by Research Hypothesis

Ebrahim Farrokh | Engineering and Technology | Best Researcher Award

Assoc. Prof. Dr Ebrahim Farrokh, Amirkabir University of Technology, Iran

Assoc. Prof. Dr. Ebrahim Farrokh is a distinguished expert in rock mechanics and mining engineering, serving as the Head of Rock Mechanics and Mining Engineering at Amirkabir University of Technology. With a career spanning academia and industry, he specializes in tunnel boring machines (TBMs), underground excavation, and rock stability analysis. He has played a key role in major tunneling projects, providing expertise on TBM operations, rock fragmentation, and ground control. His research has led to numerous influential publications, advancing TBM performance prediction and tunnel design methodologies. Alongside his academic role, he consults for Tunnel Saz Machin Co. and has held managerial positions at Hyundai Engineering and Construction. Recognized with prestigious awards, including the Hardy Memorial Award and SME’s NAT Conference Scholarship, his contributions continue to shape the field of mining engineering. His work combines theoretical advancements with practical applications, ensuring safer and more efficient underground construction projects. 🚆💡

Publication Profile

Google Scholoar

Education

Ph.D. in Mining Engineering, Penn State University (2009-2012) 🏗️
Dr. Farrokh earned his Ph.D. at Penn State University, focusing on TBM performance evaluation, advance rate prediction, and rock behavior analysis. His research contributed to innovative methodologies for assessing TBM cutter wear and ground stability.
M.Sc. in Mining Engineering, Tehran University (2001-2004) ⛏️
During his master’s studies, he specialized in underground excavation, tunnel stability, and mine planning. His thesis examined rock fragmentation techniques and their applications in mechanized tunneling.
B.Sc. in Mining Engineering, Yazd University (1997-2001) 🌍
He completed his undergraduate degree at Yazd University, gaining foundational knowledge in rock mechanics, mineral extraction, and geotechnical engineering. His early research explored TBM operational parameters and ground convergence in tunneling projects.

Experience

Associate Professor & Head, Rock Mechanics & Mining Engineering, Amirkabir University of Technology (2018-present) 🎓
Leads research and academic initiatives in TBMs, tunnel stability, and underground mining.
Consultant, Tunnel Saz Machin Co. (2018-present) 🏗️
Provides technical expertise in TBM operations, ground support, and excavation efficiency.
TBM Specialist & Manager, Hyundai Engineering & Construction (2013-2017) 🚜
Managed TBM operations in major tunneling projects, optimizing performance and reducing downtime.
Research Assistant, Penn State University (2009-2012) 📊
Conducted cutting-edge research on TBM cutter wear, penetration rate estimation, and tunnel convergence.

Awards and Honors 🏆

Outstanding Business Performance Award, Hyundai Engineering & Construction (2015) 🌟
Recognized for leadership in TBM project execution and efficiency improvements.
Outstanding Research Award, Hyundai Engineering & Construction (2014, 2015) 🏅
Awarded for contributions to TBM performance evaluation and geotechnical risk mitigation.
NAT Student Conference Scholarship Award, SME (2012) 🎓
Acknowledged for excellence in mining engineering research and academic achievements.
Hardy Memorial Award, Penn State University (2010) 🏆
Prestigious recognition for outstanding research contributions in mining and rock mechanics.

Research Focus

Dr. Farrokh’s research focuses on Tunnel Boring Machines (TBMs) 🚜, specializing in performance evaluation, advance rate prediction, and cutterhead design optimization. In Rock Mechanics 🏗️, he investigates rock properties, ground convergence, and stability assessment for underground projects. His work in Mining Engineering ⛏️ explores underground mining methods, rock fragmentation, and geotechnical risk analysis. By integrating theoretical advancements with real-world applications, Dr. Farrokh enhances the efficiency and safety of tunneling and mining operations. His research contributes to optimizing excavation processes, reducing operational risks, and advancing sustainable underground construction. 📊🔬

Publications Top Notes

Tunnel Face Pressure Design and Control 📊 (2020)
Concrete Segmental Lining: Procedure of Design, Production, and Erection of Segmental Lining in Mechanized Tunneling 📚 (2006)
Study of Various Models for Estimation of Penetration Rate of Hard Rock TBMs 📊 (2012)
Effect of Adverse Geological Conditions on TBM Operation in Ghomroud Tunnel Conveyance Project 🌎 (2009)
Correlation of Tunnel Convergence with TBM Operational Parameters and Chip Size in the Ghomroud Tunnel, Iran 📊 (2008)
A Discussion on Hard Rock TBM Cutter Wear and Cutterhead Intervention Interval Length Evaluation 💡 (2018)
Evaluation of Ground Convergence and Squeezing Potential in the TBM-Driven Ghomroud Tunnel Project 🌎 (2006)
Study of Utilization Factor and Advance Rate of Hard Rock TBMs 📊 (2013)
A Study of Various Models Used in the Estimation of Advance Rates for Hard Rock TBMs 📊 (2020)
Analysis of Unit Supporting Time and Support Installation Time for Open TBMs 🕒 (2020)

Eduardo Garcia Magraner | Engineering and Technology | Best Researcher Award

Posted on 20/02/202520/02/2025 by Research Hypothesis

Eduardo Garcia Magraner | Engineering and Technology | Best Researcher Award

Dr Eduardo Garcia, Magraner Ford Motor Company, Spain

🔧 Dr. Eduardo García Magraner is a distinguished expert in industrial automation, manufacturing, and occupational safety. With a Ph.D. in Computer Engineering & Industrial Production (Cum Laude, CEU Cardenal Herrera, 2016) 🎓, he has led key roles at Ford Spain 🚗, from Electromechanical Maintenance to Manufacturing Manager. A Lean Six Sigma Black Belt ⚙️, he has earned multiple innovation and safety awards 🏆, including the Henry Ford Technical Award. A sought-after speaker 🎤 and researcher 📖, his contributions span Industry 4.0, predictive maintenance, and AI-driven efficiency. Passionate about smart factories 🏭, he bridges academia and industry for sustainable progress. 🌍

Publication Profile

Orcid

Academic and Professional Background

Dr. Eduardo Garcia Magraner 🎓⚙️ is an expert in industrial engineering, automation, and occupational safety. His academic journey began with vocational training in electrical and telecommunications, followed by a Ph.D. in Computer Engineering and Industrial Production (2016) 🏅. Certified in Lean Six Sigma (Black Belt) and occupational risk prevention, he has mastered integrated management systems 🏭✅. With expertise in robotics 🤖, energy efficiency 🌱, and human resources 🤝, he has undertaken extensive additional training in automation and safety. His research explores machine deterioration and throughput optimization 📊. A leader in engineering and innovation, he continuously enhances industry standards 🚀.

Experience

Dr. Eduardo Garcia Magraner has built an impressive career at Ford S.L, starting as a First-Class Electromechanical Maintenance Operator (1990-2001) ⚙️. He advanced to Equipment Engineer (2001-2006) and later became a Maintenance Supervisor (2006) 🔩. His expertise led him to roles such as Senior Equipment Engineer in Maintenance & Automation (2007-2012) and Production Supervisor (2012) 🏭. He progressed to Manufacturing Manager for Body & Stamping (2014) and Champion of M.O.S. (2016) 🔧. As SPOC for Cyber Security (2019) and now Manufacturing Manager for Assembly & Battery Plants (2023), he continues shaping Ford’s production excellence ⚡🚗.

Awards and Recognitions

Dr. Eduardo Garcia Magraner has been recognized for his outstanding contributions to safety, productivity, and innovation at Ford Spain 🚗🏆. His accolades include multiple Maximum Awards for enhancing press line efficiency (1997, 1999, 2002) and the prestigious Henry Ford Technical Award (2019) for IIoT-based predictive maintenance 🔧📊. He received honors for workplace safety (1995, 2010, 2012) and academic mentorship at the Polytechnic University of Valencia (2014) 🎓👏. His work in AI and cybersecurity earned global recognition (2019, 2020) 🤖🔐. A leader in industrial innovation, he continues to push the boundaries of engineering excellence 🚀⚙️.

Academic Impact

Dr. Eduardo Garcia is a distinguished researcher in automation and smart manufacturing 🤖🏭. Beyond his groundbreaking research, he has delivered keynote presentations at global conferences, sharing insights on smart factories and AI-driven manufacturing 🔍🎤. His expertise has influenced industry advancements, making him a sought-after speaker in the field. In recognition of his contributions, he was honored with the prestigious CEU Ángel Herrera Prize in 2023 🏆🎓, further solidifying his reputation as a leading researcher. Through his work, Dr. Garcia continues to shape the future of industrial automation, bridging innovation and practical applications for smarter, more efficient production systems ⚙️🌍.

Presentation

Dr. Eduardo García is a distinguished expert in industrial robotics and Industry 4.0 🤖🏭, actively contributing to global conferences and forums. He has delivered impactful presentations at events like EVERii2020, PENTEO2020, and INNOVATION TALKS 2020, addressing smart manufacturing and supply chains 🚀📦. A sought-after speaker, he has shared insights at Advanced Factories, the Global Robot Expo, and the International Conference on Big Data, AI, and IoT 🌍📊. As a Master Professor at PEAKS BUSINESS SCHOOL, he fosters innovation in Industry 4.0. In 2023, he received the prestigious CEU Ángel Herrera Prize for outstanding research excellence 🏆📖.

Research Focus

Dr. Eduardo García Magraner’s research focuses on Industrial Internet of Things (IIoT) 🏭📡, smart manufacturing 🤖, and predictive maintenance 🔧⚙️ within Industry 4.0. His work includes real-time condition monitoring 🕒, virtual sensors 📊, and AI-driven automation 🤖🔍 to enhance efficiency in industrial environments. Key contributions involve sub-bottleneck detection 🚀, autonomous mobile warehouses 🚗🏭, and manufacturing process optimization 📈 using big data and simulation tools 📡💡. His research advances smart factory management 🏭💻, ensuring reliability, reducing downtime, and boosting productivity. His innovations drive next-gen industrial automation 🚀🏗️ for intelligent and self-optimizing manufacturing ecosystems.

Publication Top Notes

I3oT (Industrializable Industrial Internet of Things) Tool for Continuous Improvement in Production Line Efficiency by Means of Sub-Bottleneck Detection Method

Survival 1.0: A Novel Autonomous Industrial Mobile Warehouse (AIMW) for Industrial Environments

Virtual Sensor of Gravity Centres for Real-Time Condition Monitoring of an Industrial Stamping Press in the Automotive Industry

Influence of Mechanical Failures of the Welding Gun on the Magnetic Field Generated in the Measurement of Misalignment

Mini-Sym 4.0. a Novel Simulation Tool to Calculate Real-time Production Line Productivity

Miniterm, a Novel Virtual Sensor for Predictive Maintenance for the Industry 4.0 Era

Manufacturing Maps, a Novel Tool for Smart Factory Management Based on Petri Nets and Big Data Mini-Terms

Ali Othman Albaji | Computer Science and Artificial Intelligence | Best Researcher Award

Posted on 26/10/202426/10/2024 by Research Hypothesis

Ali Othman Albaji | Computer Science and Artificial Intelligence | Best Researcher Award

Dr Ali Othman Albaji, Libyan Authority for Scientific Research, Libya

With a Bachelor’s in Electrical Engineering and a Master’s in Electronics & Telecommunications from Universiti Teknologi Malaysia, this accomplished professional has extensive experience in academia and industry. Currently an Assistant Professor at the Higher College of Science and Technology in Libya, they also lead CR Technology System in the MENA region. Their research interests include optical wireless technologies and machine learning applications in environmental monitoring. Fluent in Arabic and English, with a diploma in Italian, they are also the President of the Postgraduate Student Society at UTM. 📡🎓🌍✍️

Publication profile

google scholar

Academic Background

With a diverse academic journey, the individual holds a Master’s in Public Management and Leadership from the London School of Economics (LSE), UK, completed in 2010. They further pursued a Master in Electronics and Telecommunications at the University Technology Malaysia from 2019 to 2023. Their foundational education includes a Bachelor’s degree in Electrical Engineering, specializing in General Communications, from the Civil Aviation Higher College in Tripoli, Libya, earned in 2007. Additionally, they completed a Diploma in the Italian language during the 2011/2012 academic year. 🎓📡

Experience

Dr. Ali Othman Albaji boasts a diverse work history across reputable organizations. He started as a Sales Advisor at Akida Company (LG) and ZTE/Telecom China, honing his expertise in the telecommunications field. His academic journey includes significant roles as an Assistant Professor and lecturer in Electronics and Telecommunications. In addition to his teaching, he has demonstrated leadership as the Chairman of CR Technology System (CRTS Group) and the President of the Postgraduate Student Society at Universiti Teknologi Malaysia. Dr. Albaji’s commitment to both academia and industry underscores his dedication to advancing technology and education. 📡🎓💼🌟

Main Hard Skills

Dr. Albaji possesses a robust set of technical skills, including proficiency in CAD Design, MATLAB Simulation Analysis, Python, and data visualization tools like Tableau. His capabilities extend to qualitative and quantitative analysis, SCADA systems, and programming languages like Verilog and HTML. These skills enable him to tackle complex research problems and contribute innovatively to his field.

Languages

Fluent in Arabic and English, with an IELTS Band Score of 8.5, Dr. Albaji also has a very good command of Italian. This linguistic proficiency allows him to collaborate with international researchers and disseminate his work to a broader audience.

Research focus

Ali Othman Albaji’s research focus centers on machine learning applications in environmental noise classification, emphasizing smart cities and mobile communications. His work includes developing algorithms for monitoring and classifying noise pollution using MATLAB, contributing to urban planning and public health. He has also explored traffic noise impacts on residential areas and mobile telecommunications in Libya. His diverse research interests extend to the design and implementation of communication systems, highlighting the integration of technology in environmental studies. Through these contributions, Albaji aims to enhance noise management and promote sustainable urban environments. 🌍📊🔊📡