Dr. Inam Illahi | Software Engineering | Best Researcher Award

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Dr. Inam Illahi | Software Engineering | Best Researcher Award

Dr. Inam Illahi, Emerson University Mutlan, Pakistan

Inam Illahi is an accomplished Assistant Professor at Emerson University Multan, Pakistan. With a rich academic background and over a decade of teaching experience, he has made significant contributions to the field of computer science. Inam holds a PhD in Computer Science and Technology from the Beijing Institute of Technology, where he focused on Assistant Technologies for Crowdsourcing Software Development. His research encompasses machine learning, deep learning, and software development, yielding several publications in prestigious journals. In addition to his academic pursuits, Inam has worked in various educational institutions, enhancing the quality of education and fostering student engagement. His dedication to research and teaching reflects a passion for advancing knowledge and technology, making him a respected figure in his field. Inam’s commitment to improving educational practices and research outcomes highlights his role as a leader in academia.

Professioanl Profile

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Summary of Suitability for the Research for Best Researcher Award

Inam Illahi is a highly qualified candidate for the Research for Best Researcher Award, showcasing a solid academic and professional background in computer science, particularly in the field of software development and machine learning. His extensive teaching experience at various reputable universities, including his current role as an Assistant Professor at Emerson University Multan, highlights his commitment to academia and his ability to contribute significantly to the educational sector.

🎓  Education

Inam Illahi’s educational journey is marked by notable achievements and a commitment to excellence. He earned his PhD in Computer Science and Technology from the Beijing Institute of Technology, China, between 2016 and 2022. His research during this time focused on Assistant Technologies for Crowdsourcing Software Development, resulting in impactful publications. Prior to his PhD, Inam completed his Master’s in Software Engineering and Management from Chalmers University of Technology, Sweden, in 2010, where he gained insights into software development practices. He also holds a Master of Computer Science from the University of Sargodha, Pakistan, which he completed in 2007. His educational foundation is complemented by a Bachelor of Arts in Computer Science and Economics from the same institution. Inam’s diverse academic experiences, along with his international exposure in Sweden and Denmark, have equipped him with a global perspective and a strong skill set in technology and education.

💼   Experience 

Inam Illahi possesses extensive experience in academia, contributing to various educational institutions over the past decade. Since March 2024, he has been serving as an Assistant Professor at Emerson University Multan, where he is involved in teaching and research activities. Before that, he held a Tenure Track Assistant Professor position at the University of Education, Lahore, Multan Campus, from August 2023 to March 2024. His earlier roles include Assistant Professor at the Institute of Southern Punjab and Lecturer positions at National Textile University, Faisalabad, and Riphah International University. Inam has also served as an Academic Coordinator at COMSATS Institute of Technology, where he played a crucial role in teaching and administration. His experience as a Deputy Director at the Quality Enhancement Cell at The University of Faisalabad further underscores his leadership abilities. Inam’s diverse roles highlight his commitment to enhancing the educational landscape through effective teaching and administrative practices.

🏅  Awards and Honors 

Inam Illahi’s commitment to excellence in research and education has earned him several accolades throughout his career. Notably, his innovative work in crowdsourcing software development and machine learning has resulted in multiple publications in reputable journals, receiving recognition from his peers. His research on the “Dr. Wheat” web-based expert system for diagnosing diseases in Pakistani wheat was presented at the International Conference of Information Security and Internet Engineering in London in 2008, showcasing his contributions to agricultural technology. In addition to research-related recognition, Inam has been actively involved in various academic committees and organizations, where his leadership skills have been acknowledged. His role as Deputy Director at The Quality Enhancement Cell highlighted his commitment to improving educational quality, further solidifying his reputation in academia. Inam’s dedication to research and education continues to inspire students and colleagues alike, contributing to his growing list of honors and achievements.

🌍  Research Focus

Inam Illahi’s research focuses primarily on the intersection of software development and artificial intelligence, with a particular emphasis on crowdsourcing and machine learning. His PhD thesis explored Assistant Technologies for Crowdsourcing Software Development, where he analyzed motivating and inhibiting factors for developers and success prediction in competitive crowdsourcing projects. His innovative contributions include the application of machine learning techniques for resolution prediction, enhancing the success rates of software development initiatives. Inam has published several influential papers in leading journals, examining various aspects of software project management and quality assurance. Notable works include studies on bug report prioritization using convolutional neural networks and severity prediction models. Through his research, Inam aims to bridge the gap between theory and practice in software development, providing valuable insights and tools for industry practitioners. His commitment to advancing knowledge in this rapidly evolving field makes him a key player in the research community.

📖 Publications Top Notes

  • Title: Deep neural network-based severity prediction of bug reports
    Cited by: 94
  • Title: CNN-based automatic prioritization of bug reports
    Cited by: 85
  • Title: Dr. Wheat: a Web-based expert system for diagnosis of diseases and pests in Pakistani wheat
    Cited by: 79
  • Title: Serum tumor necrosis factor-alpha as a competent biomarker for evaluation of disease activity in early rheumatoid arthritis
    Cited by: 19
  • Title: An empirical study on competitive crowdsource software development: motivating and inhibiting factors
    Cited by: 13

Mr. Rafael Siqueira | Nutrition | Best Researcher Award

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Mr. Rafael Siqueira | Nutrition | Best Researcher Award

Mr. Rafael Siqueira, Federal university of Bahia, Brazil

Rafael Pena Siqueira is a distinguished nutritionist and academic with a comprehensive background in nutrition, biosciences, and public health. He completed his PhD in Nutrition at the Federal University of Bahia (UFBA), focusing on the impacts of the COVID-19 pandemic on the lifestyle of higher education professionals and students. His Master’s degree explored analytical methods for detecting uranium in breast milk, further demonstrating his expertise in biosciences. Throughout his career, he has been actively involved in teaching, research, and extension activities at UFBA, where he supervises nutrition internships, oversees university food services, and participates in various academic committees. Rafael has also contributed to community health education, delivering lectures and courses on nutrition and public health. His ongoing research focuses on mental health and chronic diseases during the pandemic, highlighting his commitment to addressing real-world health challenges through innovative research.

Professional Profile

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Summary of Suitability for the Award

Rafael Pena Siqueira is a well-rounded candidate for the “Research for Best Researcher Award,” showcasing a solid academic and research background in the field of Nutrition. With a Ph.D. focused on the impact of the COVID-19 pandemic on lifestyle habits within higher education, Siqueira has tackled timely and relevant issues, demonstrating his ability to conduct impactful research. His prior work includes a Master’s thesis on the development of analytical methods for uranium detection in breast milk, highlighting his technical expertise in biosciences and health research.

🎓 Education 

Rafael Pena Siqueira holds a PhD in Nutrition from the Federal University of Bahia (UFBA), where he conducted a cohort study on the lifestyle impacts of the COVID-19 pandemic on students and faculty members in Brazilian higher education. His academic journey began with a Bachelor’s degree in Nutrition from UFBA’s Anísio Teixeira Campus, followed by a Master’s degree in Biosciences, where he developed an analytical method for detecting uranium in breast milk. His studies reflect a strong foundation in health and biosciences, with a focus on clinical and public health nutrition. Additionally, Rafael has pursued specialized courses, including Clinical Nutrition and Public Health from UNIGRAD, and short-term certifications in maternal and infant nutrition, sexually transmitted infections, and nutrition biochemistry. His education showcases a commitment to both academic excellence and practical applications in the field of nutrition, equipping him with the skills to address critical health issues.

💼   Experience 

Rafael Pena Siqueira has amassed extensive experience in both academic and public health sectors. Since 2016, he has been serving as a Technical Officer in Nutrition and Dietetics at the Federal University of Bahia (UFBA), where he supervises collective feeding internships, supports research and extension activities, and oversees food services contracts for the university’s dining facilities. Rafael has also served as an invited professor, teaching courses on topics like database research and artificial intelligence tools for scientific research. His role extends beyond the classroom, as he participates in various academic committees, including biosafety and internship coordination. He also facilitated community health education, acting as a mediator in courses designed to enhance the care for chronic non-communicable diseases in Bahia. His diverse roles highlight his ability to integrate academic knowledge with practical applications in nutrition and public health.

🏅  Awards and Honors 

Rafael Pena Siqueira has earned several accolades throughout his career, recognizing his contributions to nutrition and public health. In 2021, he received an award for his research on incorporating sociobiodiversity foods into the school diets of children with special dietary needs. This project, developed as part of the Postgraduate Program in Food and Nutrition at UFPR, exemplifies his commitment to improving public health through sustainable and inclusive dietary practices. Additionally, Rafael has been a scholarship recipient of prestigious Brazilian research agencies such as FAPESB and CNPq, which supported his studies and research projects during his Master’s and PhD programs. These honors underscore his expertise in the field of nutrition and his ongoing dedication to advancing nutritional science for the benefit of both academic communities and broader society.

🌍  Research Focus 

Rafael Pena Siqueira’s research primarily revolves around public health, nutrition, and the effects of chronic diseases. His current focus is on the mental health and lifestyle changes of students and educators in Brazilian higher education during the COVID-19 pandemic. This research is part of his PhD thesis at UFBA, where he examines how the pandemic has impacted physical activity, dietary habits, and mental health within academic settings. Previously, his Master’s research involved developing analytical methods for detecting uranium in breast milk, showcasing his expertise in biosciences. Rafael also explores community health interventions, particularly the integration of sociobiodiversity foods in school meals, and has contributed to courses and public health projects addressing chronic non-communicable diseases in Bahia. His work aims to bridge the gap between scientific research and practical health solutions, contributing to the improvement of public health through evidence-based nutritional practices.

 📖 Publication Top Notes

  1. Mediating effect of emotional distress on the relationship between noncommunicable diseases and lifestyle among Brazilian academics during the COVID-19 pandemic
  2. A dispersive liquid–liquid microextraction based on solidification of floating organic drop and spectrophotometric determination of uranium in breast milk after optimization using Box-Behnken design

Dr. Roohollah Shirani Faradonbeh | Mining Engineering | Best Researcher Award

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Dr. Roohollah Shirani Faradonbeh | Mining Engineering | Best Researcher Award

Dr. Roohollah Shirani Faradonbeh, Curtin University, Australia

Dr. Roohollah Shirani Faradonbeh is an accomplished mining engineer with expertise in intelligent mining, mine electrification, and sustainable resource management. Currently, he serves as an Assistant Professor at Curtin University’s WA School of Mines, where he contributes to innovative research in digital mining technologies and advanced rock mechanics. With a PhD in Mining Engineering from the University of Adelaide, his research focuses on AI-driven predictive models for rockburst risk assessment in underground mines. Dr. Shirani has published extensively on topics like mine tailings recovery, blasting optimization, and sustainable mining practices.

Professional profile

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Summary of Suitability for the “Research for Best Researcher Award” – Roohollah Shirani Faradonbeh

Dr. Roohollah Shirani Faradonbeh has an outstanding academic background and extensive experience in the field of mining engineering, making him a highly suitable candidate for the Research for Best Researcher Award. His research focuses on critical areas such as rockburst phenomena in deep underground mining, which has significant implications for safety and operations in the mining industry. His development of AI-based models and novel testing methodologies, as demonstrated in his doctoral work, has opened new frontiers in intelligent mining, especially in predicting and mitigating rockburst risks.

 🎓Education

Dr. Shirani holds a PhD in Mining Engineering from the University of Adelaide, where his thesis explored AI-based models for predicting and controlling rockburst phenomena in deep underground mines. His MSc in Mining Engineering from Tarbiat Modares University focused on minimizing blast-induced ground vibrations using gene expression programming. During his BSc at the University of Kashan, he investigated methods for reducing the back-break phenomenon in Iran’s Sungun Copper Mine. His educational journey highlights his expertise in predictive modeling, experimental mechanics, and sustainable mining practices.

 💼 Experience

Dr. Shirani has held multiple academic and industry roles, including his current position as Assistant Professor at Curtin University’s WA School of Mines. He has served as an industry advisor for Fortescue Metals Group and was a research and teaching assistant at the University of Adelaide. His teaching portfolio covers advanced topics like rock excavation technology, mine automation, and slope engineering. In addition to academic contributions, Dr. Shirani has supervised numerous PhD and M.Phil. students in fields such as autonomous mining systems, rockburst early warning tools, and environmental impact assessments for deep-sea mining.

 🏅Awards and Honors

Throughout his career, Dr. Shirani has received recognition for his contributions to mining engineering and research excellence. He has been honored with multiple academic awards for his innovative work in intelligent mining systems and AI-driven rockburst models. His research on blasting operations and ground vibration prediction has garnered attention from industry and academia alike. Additionally, Dr. Shirani has played a key role in international mining conferences, where his contributions to sustainable mining and resource recovery have been highly regarded by peers and industry professionals.

🌍 Research Focus

Dr. Shirani’s research centers on cutting-edge mining technologies, focusing on areas like mine digitalization, autonomous systems, and AI-based predictive models. He is particularly interested in the electrification and decarbonization of mining operations, as well as sustainable mine rehabilitation and waste management. His work in the experimental analysis of rockburst behavior and mine tailings recovery has paved the way for advancements in mining safety and efficiency. He also explores alternative mining methods, such as deep-sea mining and asteroid mining, reflecting his forward-thinking approach to resource extraction.

 📖 Publications Top Notes

Forecasting blast-induced ground vibration developing a CART model
Cited by: 172
Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction
Cited by: 171
Prediction of the uniaxial compressive strength of sandstone using various modeling techniques
Cited by: 164
Combination of neural network and ant colony optimization algorithms for prediction and optimization of flyrock and back-break induced by blasting
Cited by: 153
Long-term prediction of rockburst hazard in deep underground openings using three robust data mining techniques
Cited by: 147