AWAIS KHAN | Engineering | Best Researcher Award

Posted on by sciencefather

Assist. Prof. Dr. AWAIS KHAN | Engineering | Best Researcher Award

πŸ‘€ Assist. Prof. Dr. AWAIS KHAN, Beijing Institute of Technology Zhuhai Campus, China

Dr. Awais Khan is an Assistant Professor at the Beijing Institute of Technology, Zhuhai Campus, specializing in advanced control systems, renewable energy technologies, and interval observers. With a PhD in Control Theory and Control Engineering from South China University of Technology, Dr. Khan has made significant contributions to mechatronics and control engineering during his tenure as a Postdoctoral Research Fellow at Shenzhen University. His research is recognized for its innovative approach, particularly in the application of control systems in energy-efficient technologies. A prolific researcher and published author, Dr. Khan has been actively involved in securing research funding and publishing in top-tier journals. His passion for both teaching and research allows him to foster a dynamic learning environment for students while contributing to the advancement of technology in engineering and energy sectors.

Professional Profile

Google Scholar

🌟 Summary of Suitability for the Research for Best Researcher Award

Awais Khan’s impressive academic background and research trajectory make him highly suitable for the Research for Best Researcher Award. He currently serves as an Assistant Professor at the Beijing Institute of Technology, where he leads cutting-edge research in advanced control systems, renewable energy technologies, and interval observers. His teaching excellence, combined with his groundbreaking research contributions, aligns well with the award’s criteria, which honors those making significant academic and technological advancements.

Awais Khan’s postdoctoral experience at Shenzhen University further solidifies his research prowess, particularly in mechatronics and control engineering. His work has been recognized in reputable journals, with a consistent record of impactful publications in high-impact platforms such as IEEE Transactions and the Journal of the Franklin Institute. He has demonstrated leadership in securing research funding and fostering interdisciplinary collaboration.

πŸŽ“   Education 

Dr. Awais Khan holds a PhD in Control Theory and Control Engineering from the South China University of Technology (2016–2020), where his research focused on interval observers and their applications to control theory. Prior to that, he earned a Master’s degree in Electrical Engineering from the University of Engineering and Technology (UET) Lahore (2014–2016). Dr. Khan’s academic journey began with a Bachelor of Science in Electronics Engineering from UET Peshawar (2009–2013), which laid the foundation for his expertise in engineering and control systems. Throughout his academic career, he has received several scholarships, including the prestigious Chinese Government Scholarship for his PhD studies. His educational background is complemented by his active participation in various research projects, workshops, and technical conferences, enabling him to stay at the forefront of advancements in control systems, renewable energy technologies, and energy-efficient engineering solutions.

πŸ’Ό   Professional Experience 

Since 2022, Dr. Awais Khan has been an Assistant Professor at the Beijing Institute of Technology, Zhuhai Campus, where he teaches a range of courses, including C/C++, Probability & Statistical Analysis, Circuits & Electronics, and Physics. His role involves both delivering high-quality lectures and conducting groundbreaking research in advanced control systems, renewable energy, and interval observers. Prior to this, Dr. Khan was a Postdoctoral Research Fellow at Shenzhen University (2020–2022), where he worked on mechatronics and control engineering, developing innovative technologies in interdisciplinary research collaborations. His work on interval observers for nonlinear systems garnered attention, leading to publications in reputable journals. Dr. Khan has also contributed to National Natural Science Foundation of China projects, enhancing the understanding of control systems in uncertain environments. His teaching and research experience are central to his contributions to the field, shaping future engineers and advancing the integration of energy-efficient technologies.

πŸ… Awards and Recognition 

Dr. Awais Khan has been recognized for his outstanding contributions to control systems and engineering through several prestigious awards and honors. Notably, he received the Best Presentation Award at the EECR in 2018, reflecting his excellence in research communication. His doctoral research, supported by the Chinese Government Scholarship, marked a milestone in the development of interval observers for linear and nonlinear systems. In addition, Dr. Khan serves as an editor for Technological Innovations & Energy and has been an active member of professional organizations, such as the IEEE and the International Association of Engineers, since 2024. His scholarly work has been widely recognized, with numerous publications in leading journals and conferences. He continues to secure research grants, supporting the advancement of innovative technologies in control systems and energy efficiency. Dr. Khan’s contributions to both academia and the engineering community have made him a respected figure in the field.

🌍  Research Skills On Engineering

Dr. Awais Khan possesses a deep proficiency in advanced control systems, renewable energy technologies, and interval observers. His research expertise spans control theory, nonlinear systems, and energy-efficient technologies, focusing on their applications in both academia and industry. With a strong background in mechatronics and control engineering, he has developed innovative solutions for system stability and energy optimization. Dr. Khan is skilled in designing interval observers for dynamic systems, particularly in uncertain environments, and has published extensively on the subject. His work also explores adaptive control strategies for robotics and power systems, leveraging cutting-edge technologies such as SiC and GaN. Dr. Khan is proficient in several programming languages, including Matlab, Simulink, Python, and C/C++, enabling him to implement complex models and simulations for his research. His skills in interdisciplinary collaboration and securing funding for research projects further highlight his versatility and commitment to advancing technological solutions in engineering.

 πŸ“– Publication Top Notes

  • A survey of interval observers design methods and implementation for uncertain systems
    A Khan, W Xie, Z Bo, LW Liu
    Journal of the Franklin Institute, 358(6), 3077-3126, 2021
    Citation: 52
  • Design and Applications of Interval Observers for Uncertain Dynamical Systems
    A Khan, W Xie, Z Langwen, LW Liu
    IET Circuits, Devices & Systems, 14(6), 721-740, 2020
    Citation: 48
  • Path Planning for Wheeled Mobile Robot in Partially Known Uneven Terrain
    B Zhang, G Li, Q Zheng, X Bai, Y Ding, A Khan
    Sensors, 22(14), 5217, 2022
    Citation: 41
  • Finite‐time nonsingular terminal sliding mode control of converter‐driven DC motor system subject to unmatched disturbances
    A Rauf, M Zafran, A Khan, AR Tariq
    International Transactions on Electrical Energy Systems, 31(11), e13070, 2021
    Citation: 26
  • Interval state estimation for linear time-varying (LTV) discrete-time systems subject to component faults and uncertainties
    A Khan, W Xie, L Zhang, Ihsanullah
    Archives of Control Sciences, 29(2), 289-305, 2019
    Citation: 22
  • Set-Membership Interval State Estimator Design Using Observability Matrix for Discrete-Time Switched Linear Systems
    A Khan, LW Liu, W Xie
    IEEE Sensors Journal, 20(11), 6121-6129, 2020
    Citation: 20
  • Interval State Estimator Design for Linear Parameter Varying (LPV) Systems
    A Khan, X Bai, Z Bo, P Yan
    IEEE Transactions on Circuits and Systems II: Express Briefs, 68(8), 2865-2869, 2021
    Citation: 19
  • Finite‐time functional interval observer for linear systems with uncertainties
    L Liu, W Xie, A Khan, L Zhang
    IET Control Theory & Applications, 14(18), 2868-2878, 2020
    Citation: 14
  • Fault detection and diagnosis for a class of linear time-varying (LTV) discrete-time uncertain systems using interval observers
    Z Yi, W Xie, A Khan, B Xu
    2020 39th Chinese Control Conference (CCC), 4124-4128, 2020
    Citation: 14
  • Interval State Estimator Design Using the Observability Matrix for Multiple Input Multiple Output Linear Time-Varying Discrete-Time Systems
    A Khan, W Xie
    IEEE Access, 7, 167566-167576, 2019
    Citation: 13

Dr. Inam Illahi | Software Engineering | Best Researcher Award

Posted on by sciencefather

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

Google scholar

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.

πŸŽ“  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.

πŸ’Ό   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.

πŸ…  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 β€œDr. 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.

πŸ“– 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. Daniel Morariu | Resilience | Best Researcher Award

Posted on by sciencefather

Mr. Daniel Morariu | Resilience | Best Researcher Award

Mr. Daniel Morariu, Lucian Blaga University of Sibiu, Romania

Morariu Ionel Daniel is an esteemed associate professor at β€œLucian Blaga” University of Sibiu, Romania, with expertise in computer science, automatic systems, data mining, and machine learning. Born on September 17, 1974, in Sighisoara, he has dedicated over two decades to education and research. He holds a Bachelor’s and Master’s degree in Computer Science from β€œLucian Blaga” University and completed his PhD in Computer Science with a focus on β€œAutomatic Knowledge Extraction from Unstructured Data” in 2007. Daniel has been a consistent contributor to advanced research, particularly in data mining, neural networks, and natural language processing. With a robust portfolio of software engineering and academic experience, his career includes impactful projects in automation systems, energy control solutions, and numerous published research papers. His dedication to knowledge dissemination and technological advancements has earned him respect in both academic and industrial circles.

Professional Profile

google scholar

Summary of Suitability for the Award

Dr. Morariu Ionel Daniel stands out as a highly qualified candidate for the Research for Best Researcher Award, particularly due to his extensive academic background, research experience, and contributions in the field of Computer Science. His educational path, including a PhD focused on automatic knowledge extraction from unstructured data, demonstrates his depth in data mining and machine learning, areas that are essential in today’s technological landscape. Furthermore, his PhD was supported by SIEMENS Corporate Technology, highlighting the practical relevance of his work.

 πŸŽ“  Education 

Daniel Morariu completed his secondary education at β€œMircea Eliade” Theoretic High School, Sighisoara, between 1989-1993. He pursued higher education at β€œLucian Blaga” University of Sibiu’s Engineering Faculty, earning a Bachelor’s degree in Computer Science and Automatic Systems in 1998. His academic journey continued with a Master’s degree in Computer Science in 1999, specializing in β€œParallel and Distribute Processing Systems” from the same university. His thirst for knowledge culminated in a PhD in Computer Science, awarded in April 2007. His PhD research focused on β€œContributions to Automatic Knowledge Extraction from Unstructured Data,” under the supervision of Professor Lucian N. VinΘ›an. Supported by SIEMENS Corporate Technology from Munich, his doctoral research provided significant insights into data mining and natural language processing. This strong educational foundation has positioned him as a distinguished academic in the field of computer science.

πŸ’Ό     Experience 

Daniel Morariu has held a variety of academic positions throughout his career. He began as a teaching assistant at β€œLucian Blaga” University in 1998, contributing to courses such as Microprocessors and Object-Oriented Programming. From 2003 to 2007, he served as a lecturer, teaching advanced courses in Neural Networks and Data Mining. In 2007, he became an associate professor, focusing on courses like Data Mining, Machine Learning, and Interfaces and Communication Protocols. Outside academia, Morariu gained valuable industry experience. He worked with SC Consultens Informationstechnik SRL, a German software company, as a software engineer from 2001 to 2002. He also worked as an engineer at SC IRMES SA Sibiu from 1998 to 2000, developing software for monitoring generators and controlling gas supply in thermoelectric power stations. His career reflects a strong blend of academic expertise and practical industry experience, especially in computer science and automation systems.

πŸ…  Awards and Honors

Throughout his career, Daniel Morariu has been recognized for his contributions to computer science and engineering. His PhD research, supported by SIEMENS Corporate Technology from Munich, was a notable achievement, reflecting both scientific and financial backing from a prestigious institution. Over the years, his dedication to teaching and research has earned him accolades within the academic community at β€œLucian Blaga” University, including recognition for his innovative approach to data mining and machine learning education. His work in automation systems, particularly in the energy sector, has also been praised for its practical applications, further solidifying his status as a leading figure in the intersection of academia and industry. Though specific awards are not listed, his consistent professional growth and contributions speak to a career filled with academic accomplishments and recognition.

 πŸŒ  Research Focus

Daniel Morariu’s research primarily revolves around data mining, machine learning, and natural language processing. His academic focus is on extracting meaningful knowledge from unstructured data using advanced techniques such as Support Vector Machines (SVM) and neural networks. His PhD dissertation on β€œContributions to Automatic Knowledge Extraction from Unstructured Data” set the foundation for his continuing research into text document processing and computational linguistics. Additionally, he explores the applications of these technologies in real-world problems, particularly in automation systems and energy sector monitoring. His work on computational linguistics helps bridge the gap between machine learning models and language understanding, while his research in data mining enhances predictive models across industries. Morariu’s blend of theoretical research and practical applications has made him a valuable contributor to advancements in these fields, influencing both academic research and industrial applications.

πŸ“– Publication Top Notes

  • Feature selection methods for an improved SVM classifier
    • Cited by: 31
  • Meta-Classification using SVM Classifiers for Text Documents
    • Cited by: 27
  • The WEKA Multilayer Perceptron Classifier
    • Cited by: 22
  • Text Mining Methods Based on Support Vector Machine
    • Cited by: 22
  • Evolutionary Feature Selection for Text Documents Using the SVM
    • Cited by: 22

Ms. Meaad Alqahtany | Education | Research Excellence Award

Posted on by sciencefather

Ms. Meaad Alqahtany | Education | Research Excellence Award

Ms. Meaad Alqahtany, King Saud Bin Abdulaziz University for Health Sciences, Saudi Arabia

Meaad Alqahtany is a dedicated biologist specializing in cellular and molecular biology, with a focus on understanding the structural intricacies of prokaryotic cells. Currently a Research Assistant at King Saud bin Abdulaziz University for Health Sciences in Saudi Arabia, Meaad plays a key role in supporting research projects, monitoring ongoing studies, and contributing to data analysis. With prior experience as a part-time lecturer and science teacher, she brings a blend of academic rigor and practical teaching experience. Her research revolves around using high-resolution microscopies to investigate surface cell molecules, particularly in bacterial cells.

Professional Profile

Scopus

Summary of Suitability for the Research for Research Excellence Award

Meaad Alqahtany is a strong candidate for the Research for Research Excellence Award. Her extensive research experience, publication record, leadership initiatives, and passion for education make her well-suited for recognition. Her work in cellular and molecular biology, coupled with her ability to teach and mentor, positions her as a scientist contributing significantly to both her field and the broader scientific community.

πŸŽ“ Education

Meaad Alqahtany holds a Master of Science in Cell and Molecular Biology from the University of Arkansas (2019), where she researched bacterial cell proteins using advanced molecular techniques. She completed her Bachelor’s in Biology (Microbiology) at King Abdulaziz University, Saudi Arabia, in 2014. In addition to her formal education, Meaad has also completed several advanced courses and workshops, including research data management, scientific writing, and statistical analysis. Her diverse educational background equips her with a deep understanding of biological sciences and the technical skills needed for cutting-edge research.

πŸ’Ό Experience

Meaad has amassed significant experience across academic and research settings. As a Research Assistant since 2021, she has supported projects at King Saud bin Abdulaziz University for Health Sciences. Previously, she was a Lecturer at Bisha University, teaching Micro Techniques. From 2019-2021, she taught science to middle school students at Majestic International School, where she also organized science fairs. During her time at the University of Arkansas (2017-2019), she conducted advanced research on bacterial cell proteins as part of her graduate studies. Meaad has also been a Lab Instructor, training undergraduate students in biology lab techniques.

πŸ…Awards and Honors

  • Founder and active member of the Biology Club at the College of Science
  • Organized New Students Orientation, Bio Day, and other student events
  • Led the 3-Minute Research Proposal competition at KSAU-HS
  • Presented research at international conferences on cellular biology
  • Received recognition for her contribution to scientific publications on antimicrobial mechanisms and nanoparticle effects

🌍  Research Focus

Meaad’s research focuses on cellular and molecular biology, particularly prokaryotic cells. She uses high-resolution microscopy techniques to investigate surface cell molecules, including histone-like proteins and nucleoid structuring in bacteria. Her studies aim to uncover the molecular mechanisms of how silver nanoparticles affect bacterial cells and their proteins, shedding light on antimicrobial actions. Meaad also delves into nanoparticle stability and its impact on biological systems, providing insight into how nanotechnology can influence microbiology.

 πŸ“– Publication Top Notes

  • Faculty and students perspectives towards game-based learning in health sciences higher education
  • Nanoscale reorganizations of histone-like nucleoid structuring proteins in Escherichia coli are caused by silver nanoparticles
    • Citations: 18

Dr. Phuong Nguyen-Thanh | Engineering | Best Researcher Award

Posted on by sciencefather

Dr. Phuong Nguyen-Thanh | Engineering | Best Researcher Award

Dr. Phuong Nguyen-Thanh, National Kaohsiung University of Science and Technology, Taiwan

Phuong Nguyen Thanh is a dedicated Postdoctoral Researcher at the Energy Technology Research Center (ETRIC) in the Department of Electrical Engineering at the National Kaohsiung University of Science and Technology. Born on April 14, 1988, in Vietnam, he has developed a strong academic and professional background in electrical engineering and energy systems. His core skills encompass independent research, teaching various subjects in English, and programming in multiple languages, including JavaScript and MATLAB. With a passion for renewable energy integration, Phuong aims to contribute significantly to advancements in power systems. He is fluent in Vietnamese and English and has basic proficiency in Chinese. His professional journey reflects a commitment to fostering knowledge and innovation in the field of electrical engineering.

Professional Profile

Orcid

Summary of Suitability for the Research for Best Researcher Award

Phuong Nguyen Thanh’s expertise in Electrical Engineering and Energy Technology positions him as a highly suitable candidate for the Research for Best Researcher Award. His background as a Postdoc Researcher at the Energy Technology Research Center (ETRIC), combined with his significant teaching experience at Nha Trang University, demonstrates a strong blend of academic knowledge and practical research ability. His PhD from National Kaohsiung University of Science and Technology further emphasizes his dedication to advancing energy systems, a critical area in modern research.

 πŸŽ“ Education 

Phuong Nguyen Thanh earned his Doctor of Philosophy in Electrical Engineering from the National Kaohsiung University of Science and Technology in 2022, where he focused on integrating artificial intelligence and deep learning algorithms in power systems. Before that, he completed his Master’s degree in Electronic and Computer Engineering at RMIT Vietnam in November 2014, a branch of the renowned Royal Melbourne Institute of Technology in Australia. His academic foundation includes a Bachelor’s degree in Electrical Engineering from the University of Vietnam Technology, where he specialized in Energy Systems, graduating in December 2010. Phuong’s strong educational background equips him with the theoretical knowledge and practical skills essential for addressing complex challenges in energy technology, paving the way for his impactful research in renewable energy and smart systems.

 πŸ’Ό Experience

Phuong Nguyen Thanh has a rich professional experience in academia and research. He is currently a Postdoctoral Researcher at the Energy Technology Research Center (ETRIC), National Kaohsiung University of Science and Technology, where he applies AI and deep learning algorithms to enhance power systems since September 2022. Prior to this role, he served as a full-time lecturer at Nha Trang University, Vietnam, from 2010 to January 2019, where he taught courses on Power Systems, Power Dispatching Strategies, and Programming on Microcontrollers. His teaching methods emphasized practical applications and hands-on learning, fostering a deep understanding of electrical engineering among his students. Phuong has demonstrated his commitment to education and research by developing various applications for smartphones on Android and iOS platforms, as well as engaging in independent research projects that focus on renewable energy solutions and smart grid technologies.

πŸ… Awards and Honors 

Phuong Nguyen Thanh has received several accolades for his contributions to the field of electrical engineering and renewable energy. His academic excellence was recognized with a scholarship for his Ph.D. studies at the National Kaohsiung University of Science and Technology, underscoring his commitment to advancing knowledge in energy technology. During his Master’s program at RMIT Vietnam, he was awarded a merit scholarship for outstanding performance in his coursework. Phuong has also been acknowledged for his innovative research projects, which have been presented at various national and international conferences. His dedication to teaching has earned him positive evaluations from students and faculty alike, reflecting his effective communication skills and passion for educating the next generation of engineers. Phuong’s continued pursuit of research excellence is expected to yield further recognition as he contributes to significant advancements in renewable energy integration and smart systems.

 πŸŒ Research Focus 

Phuong Nguyen Thanh’s research focus lies in the integration of renewable energy technologies and the application of artificial intelligence (AI) in power systems. His recent work involves exploring deep learning algorithms to enhance the efficiency and reliability of energy distribution networks. Phuong is particularly interested in developing smart grid solutions that can adapt to dynamic energy demands while optimizing the use of renewable sources such as solar and wind power. He aims to create innovative algorithms for energy management systems that can facilitate the seamless integration of distributed energy resources. Additionally, Phuong’s research investigates the implementation of microcontroller programming in energy systems to improve automation and control. Through his work at the Energy Technology Research Center (ETRIC), he seeks to address the challenges of renewable energy integration and contribute to the development of sustainable energy solutions for the future.

 πŸ“– Publication Top Notes

  • Hourly load prediction based feature selection scheme and hybrid CNN-LSTM method for building’s smart solar microgrid
  • A cloud 15kV-HDPE insulator leakage current classification based improved particle swarm optimization and LSTM-CNN deep learning approach
  • Advanced AIoT for failure classification of industrial diesel generators based hybrid deep learning CNN-BiLSTM algorithm
  • Real-time AIoT anomaly detection for industrial diesel generator based an efficient deep learning CNN-LSTM in industry 4.0
  • Novel cloud-AIoT fault diagnosis for industrial diesel generators based hybrid deep learning CNN-BGRU algorithm

Assoc Prof. Dr. Merga Agga | Pbulic Health | Best Researcher Award

Posted on by sciencefather

Assoc Prof. Dr. Merga Agga | Pbulic Health | Best Researcher Award

Assoc Prof. Dr. Merga Agga, Haramaya University, Ethiopia

Merga Dheresa Agga is an accomplished public health expert based at the Ethiopian Public Health Institute in Addis Ababa. He holds a PhD in Public Health with a focus on Maternal and Child Health from Haramaya University. With extensive teaching and research experience, Dr. Merga has contributed significantly to public health initiatives, particularly in reproductive health and disease prevention. He has authored over 100 publications, including articles and books, establishing himself as a leading figure in public health research in Ethiopia. In addition to his academic roles, Dr. Merga actively participates in national health policy-making, serving as a senior researcher and advisor on various health programs.

Professional Profile

orcid

Evaluation of Merga Dheresa Agga for the Research for Best Researcher Award

Summary of Suitability for the Award

Merga Dheresa Agga is an accomplished scholar and practitioner in the field of public health, particularly in maternal and child health. With a Ph.D. in Public Health from Haramaya University, he has dedicated his career to addressing critical health challenges in Ethiopia and beyond. His extensive educational background, which includes an MPH in Reproductive Health and a BSc in Nursing, provides a solid foundation for his research and professional activities.

πŸŽ“ Education 

Dr. Merga Dheresa Agga earned his PhD in Public Health (Maternal and Child Health) from Haramaya University on February 3, 2019. He also holds a Master of Public Health (MPH) in Reproductive Health, completed on July 10, 2010, from the same institution. Prior to that, he obtained a Bachelor of Science in Nursing on July 8, 2006, from the School of Nursing and Midwifery at Haramaya University. In addition, Dr. Merga pursued an MBA from Lead Star College in collaboration with Ashland University, graduating on September 1, 2018. His diverse educational background equips him with the knowledge and skills to tackle complex health challenges in Ethiopia and beyond.

πŸ’Ό Experience

Dr. Merga Dheresa Agga has a rich professional history in public health. Currently, he is a Senior Researcher at the Burden of Disease Unit and a member of the National Health System Innovation Think Tank at the Federal Ministry of Health in Ethiopia. He has served as an Associate Professor of Public Health at Haramaya University since March 2022, where he previously held positions as Assistant Professor and Department Head. His expertise extends to leading health programs, including the National Immunization Program Evaluation Research. Dr. Merga has also collaborated with various institutions, including the Addis Continental Institute of Public Health, contributing to the advancement of public health initiatives at regional and national levels.

πŸ…Awards and Honors 

Dr. Merga Dheresa Agga has received numerous accolades for his outstanding contributions to public health. His impactful research and commitment to improving health outcomes have earned him recognition in the academic community and among health practitioners. He has been actively involved in various health initiatives, receiving commendations for his leadership and innovative approaches to public health challenges in Ethiopia. While specific awards may not be detailed, his significant publication record and roles in national health policy-making reflect his influence and dedication to advancing public health in the region.

🌍 Research Focus 

Dr. Merga Dheresa Agga’s research primarily focuses on maternal and child health, reproductive health, and the evaluation of public health programs. His work often examines barriers to health service utilization and factors influencing health outcomes, particularly in underserved populations. He is committed to addressing issues such as HIV/AIDS, maternal mental health, and the impact of social determinants on health. His extensive publication record highlights his contributions to the understanding of health challenges in Ethiopia, providing valuable insights for policymakers and health practitioners aiming to enhance health care delivery and outcomes.

πŸ“– Publication Top Notes

Association between antenatal common mental disorders symptoms, and adverse obstetric and perinatal outcomes: A community-based prospective cohort study in Eastern Ethiopia
Determinants of Cervical Cancer Screening among Female Health Professionals in Harar Town, Eastern Ethiopia: A Cross-Sectional Study
Disclosure of diagnosis by parents and caregivers to children infected with HIV in Hawassa, southern Ethiopia: a multicentre, cross-sectional study
Early Postnatal Care Utilization and Associated Factors Among Women Who Give Birth in the Last Six Weeks in Hosanna Town, Southern Ethiopia, 2022
Predictor of anemia among pregnant women attending antenatal clinics at Hiwot Fana Comprehensive Specialized Hospital, Eastern Ethiopia: a case-control study