Wisal Zafar | Computer Science | Best Researcher Award

Mr. Wisal Zafar | Computer Science | Best Researcher Award

Lecturer at Cecos university of information technology and emerging sciences, Pakistan.

Mr. Wisal Zafar is a dedicated researcher and lecturer with a strong background in software engineering, focusing on artificial intelligence, machine learning, and deep learning applications in healthcare. Born on March 25, 1999, in Peshawar, Pakistan, he has consistently demonstrated a passion for advancing technology’s role in solving real-world problems. He has developed and published research that leverages machine learning for medical diagnoses, including brain tumor analysis and diabetes prediction. As a lecturer and Electronic Data Processing (EDP) Officer at Iqra National University, he is committed to mentoring students and contributing to the field through both teaching and research. His work is distinguished by his continuous learning, keeping pace with emerging trends in AI and big data. Mr. Zafar’s career is marked by his enthusiasm for interdisciplinary research, integrating software engineering with advancements in health and data science. He is eager to expand his research contributions further through collaborations and innovative projects that address global challenges using advanced technologies.

Professional Profile

Education

Wisal Zafar holds an MS in Software Engineering from Iqra National University, Hayatabad Peshawar, completed in July 2024 with a commendable CGPA of 3.62/4.00. His postgraduate studies provided him with in-depth knowledge of advanced topics like artificial intelligence, data analysis, and big data. Prior to this, he earned a BS in Software Engineering from the same institution in October 2020, with a CGPA of 3.47/4.00, building a strong foundation in software development and computer science principles. His academic journey started with an intermediate qualification from Capital Degree College, Peshawar, where he scored 700 out of 1100 marks, and continued with his matriculation from The Jamrud Model High School, achieving 824 out of 1100 marks. His educational background is characterized by consistent academic performance and a focus on both theoretical and practical aspects of software engineering, which has prepared him for his subsequent roles in academia and research.

Professional Experience

Wisal Zafar currently serves as a Lecturer at Iqra National University, Hayatabad, Peshawar, where he has been teaching various software engineering subjects since January 2023. His areas of instruction include Data Science, Artificial Intelligence, Machine Learning, Data Structures, and Algorithms, allowing him to impart advanced knowledge to students and prepare them for careers in technology. Alongside his role as a lecturer, he also holds the position of Electronic Data Processing (EDP) Officer at the same university, a role he has been fulfilling since October 2021. In this capacity, he manages data processing tasks, ensuring the effective handling of academic data and resources. Previously, he gained practical experience as a Junior Web Developer at Pakistan Online Services Software House, where he worked from November 2020 to April 2021, specializing in web development using PHP, Laravel, JavaScript, and other technologies. This diverse experience in academia and industry has equipped Mr. Zafar with the skills to blend theoretical concepts with real-world applications, making him an effective educator and a valuable contributor to research.

Research Interests

Wisal Zafar’s research interests are centered around artificial intelligence (AI), machine learning (ML), deep learning, and their applications in healthcare and data analysis. He is particularly fascinated by the potential of AI and ML in developing advanced diagnostic tools, aiming to improve medical outcomes through data-driven insights. His recent research projects have explored the use of deep learning techniques like YOLOv8s and U-Net for multi-class brain tumor analysis, integrating detection, localization, and segmentation of tumors using MRI data. Additionally, he has delved into predictive models for diabetes diagnosis using various ML algorithms, such as Decision Trees, K-Nearest Neighbors, Random Forest, Logistic Regression, and Support Vector Machines. His interests extend to big data analytics and the role of data science in enhancing information retrieval and management in medical libraries. Through his work, Wisal Zafar seeks to advance the intersection of technology and healthcare, utilizing cutting-edge algorithms and data processing techniques to solve critical challenges and improve human well-being.

Research Skills

Wisal Zafar possesses a diverse skill set in artificial intelligence, machine learning, data analysis, and big data management, making him adept at tackling complex research challenges. He has extensive experience in using programming languages like Python and C++, which he applies to develop machine learning models and algorithms. His technical expertise includes working with deep learning frameworks, as seen in his research on brain tumor analysis using advanced models such as YOLOv8s and U-Net. Additionally, Wisal has proficiency in cloud computing and handling large datasets, which supports his work in big data analytics and the implementation of data-driven decision-making tools. His hands-on experience as a Research Assistant has further refined his skills in conducting surveys, data preprocessing, and statistical analysis. Mr. Zafar is also skilled in web development using frameworks like Laravel and JavaScript, allowing him to create interactive platforms for research applications. His ability to integrate these skills into interdisciplinary projects makes him a capable researcher with a focus on innovation and problem-solving.

Award Recognition

Wisal Zafar’s dedication to research and academic excellence has earned him recognition in the academic community, though he is still working towards broader award recognitions. His recent research publications, including studies on brain tumor analysis and diabetes prediction using machine learning, have been well-received and published in respected journals. These works have contributed significantly to the fields of AI in healthcare and big data analytics, positioning him as a promising researcher. His role as a Lecturer at Iqra National University also reflects the acknowledgment of his expertise, as he is entrusted with educating the next generation of software engineers. Additionally, Wisal has completed several certified courses from platforms like Coursera, receiving certificates in advanced learning algorithms, deep learning, and image processing with Python, which underscore his commitment to continuous learning. While he may not yet have specific awards, his publications, teaching contributions, and commitment to research excellence serve as strong indicators of his potential for future recognition in the field.

Awards and Honors

Wisal Zafar has demonstrated a commitment to continuous professional development through various certifications and achievements, contributing to his expertise in software engineering and AI. He has completed notable courses such as AI for Everyone and Advanced Learning Algorithms through Coursera, which are associated with respected institutions like DeepLearning.AI and Stanford University. These certifications have enhanced his knowledge of machine learning, deep learning, and image processing, enabling him to apply advanced concepts in his research. While he has not yet received specific formal awards, his role as a Lecturer at Iqra National University and his position as an Electronic Data Processing (EDP) Officer are testaments to his skills and recognition within the academic community. His contributions to research, especially in the areas of AI applications in healthcare, have been acknowledged through the publication of his work in peer-reviewed journals. Wisal Zafar’s ongoing pursuit of excellence, both in research and teaching, positions him as a candidate worthy of future awards and honors in the field of software engineering and AI.

Conclusion:

Wisal Zafar has demonstrated considerable research skills and expertise in the field of software engineering, particularly in applying machine learning and AI to medical problems. His academic background, technical skills, and research publications make him a strong contender for the Best Researcher Award. While he could benefit from diversifying his research and increasing his international presence, his current achievements in AI-driven healthcare solutions and data analytics set a solid foundation for this recognition.

Publications Top Notes

  1. Enhanced TumorNet: Leveraging YOLOv8s and U-net for superior brain tumor detection and segmentation utilizing MRI scans
    • Authors: Zafar, W., Husnain, G., Iqbal, A., AL-Zahrani, M.S., Naidu, R.S.
    • Journal: Results in Engineering
    • Year: 2024
    • Volume: 24
    • Article ID: 102994
    • Type: Open access
  2. Revolutionizing Diabetes Diagnosis: Machine Learning Techniques Unleashed
    • Authors: Shaukat, Z., Zafar, W., Ahmad, W., Ghadi, Y.Y., Algarni, A.
    • Journal: Healthcare (Switzerland)
    • Year: 2023
    • Volume: 11
    • Issue: 21
    • Article ID: 2864
    • Citations: 1
    • Type: Open access

 

 

 

 

Dian Kusumaningrum | Statistics | Best Researcher Award

Mrs. Dian Kusumaningrum | Statistics | Best Researcher Award

Distinguished Professor of Biomaterials of Tecnologico de Monterrey, Mexico.

Dian Kusumaningrum is a distinguished researcher and lecturer specializing in statistics and data science. She holds a Bachelor’s and Master’s degree in Statistics from IPB University and is currently pursuing a PhD in Statistics and Data Science at the same institution. Her impressive achievements include multiple research grants and scholarships, such as the SEARCA PhD Full Scholarship and SEARCA Conference Grants. Dian’s research focuses on crop insurance, Bayesian methods, and agricultural statistics, contributing significantly to the development of innovative models for agricultural sustainability. Her extensive experience includes roles as a researcher, consultant, and lecturer at prominent institutions. She has also presented at numerous international conferences and published extensively in respected journals. Dian’s dedication to advancing statistical methods and their applications in agriculture underscores her suitability for the Best Researcher Award.

Profile
Education

Dian Kusumaningrum’s educational background is marked by a strong foundation in statistics and data science. She earned her Bachelor’s degree in Statistics from IPB University, Faculty of Mathematics and Natural Sciences, in 2004. Continuing her academic journey, she completed her Master’s degree in Statistics from the same institution in 2010, supported by a scholarship from the Ministry of Education, Indonesia. Currently, she is pursuing her PhD in the Department of Statistics and Data Science at IPB University, a program which she started in 2020. Throughout her academic career, she has been recognized for her dedication and excellence, receiving various scholarships and research grants, including the SEARCA PhD Full Scholarship and SEARCA Research Grant. Her studies have consistently focused on advancing statistical methodologies and their applications, contributing to her expertise in actuarial science and data analysis.

Professional Experience

Dian Kusumaningrum has extensive professional experience in both academia and research. She began her career as a Co-Broadcaster at RRI PRO 1 Bogor and later served as a private English teacher and back data cleaner at AC Nielsen. Her expertise in statistics and data science was honed through various roles, including as a Research Assistant at UNESCAP-CAPSA and a lecturer at multiple institutions, such as Bogor Agriculture University and Prasetiya Mulya University. Kusumaningrum also held significant positions as a Statistician Lead at DAFEP Research and for various research collaborations with organizations like the World Bank and USAID. She has managed numerous research projects, including crop insurance policy development and statistical modeling for energy and financial sectors. Her contributions extend to leading statistical and actuarial product development, reflecting her significant impact on statistical research and applied data science.

Research Interest

Dian Kusumaningrum’s research interests are centered around the application of statistical methodologies to address complex problems in agriculture, economics, and risk management. Her work extensively explores the development and optimization of crop insurance policies, particularly focusing on Bayesian approaches and generalized linear mixed models to enhance agricultural productivity and farmer income sustainability. Kusumaningrum’s research also delves into the integration of climate change and smart agriculture into educational curricula, aiming to improve understanding and adaptation strategies. She has a keen interest in applying statistical and actuarial models to analyze and mitigate risks associated with agricultural practices and economic sustainability. Her commitment to advancing knowledge in these areas is demonstrated through her involvement in various national and international research projects and conferences, contributing to the development of innovative solutions for pressing challenges in agriculture and risk management.

Research Skills

Dian Kusumaningrum demonstrates exceptional research skills across a variety of statistical and data science domains. Her expertise spans Bayesian methods, small area estimation, and actuarial modeling, particularly in the context of crop insurance and food security. With extensive experience in data analysis and statistical consulting, Dian has successfully led numerous research projects, including those with international collaborations such as the World Bank and UNESCAP-CAPSA. Her proficiency in developing and applying complex models, such as the Bayesian Beta mixed regression model and generalized linear mixed models, highlights her advanced analytical capabilities. Additionally, Dian’s ability to present and publish her findings in reputable journals and conferences showcases her strong communication skills and her commitment to advancing knowledge in her field. Her diverse experience in teaching, research mentorship, and consultancy further underscores her comprehensive skill set and dedication to impactful research.

Awards and Recognition

Dian Kusumaningrum has garnered notable recognition throughout her academic and professional career. Her achievements include being awarded the Master Degree Program Scholarship and Research Grant Awardee from the Ministry of Education Indonesia, showcasing her commitment to advancing research in statistics. She has also received the SEARCA PhD Full Scholarship and multiple SEARCA Conference Grants, reflecting her excellence in academia and research. Her contributions to crop insurance development and statistical methodologies have been recognized through grants and awards from READI and STEM Prasetiya Mulya. Additionally, her international engagements, including the JASSO SUIJI Exchange Program and participation in various prestigious conferences, underline her global impact. Kusumaningrum’s extensive involvement in research and education is further highlighted by her numerous presentations and publications, cementing her reputation as a leading figure in her field.

Conclusion

Dian Kusumaningrum is a highly qualified candidate for the Research for Best Researcher Award. Her extensive educational background, notable achievements, and substantial contributions to research and teaching make her a standout candidate. By broadening her research scope and increasing international collaborations, she could further strengthen her position as a leading researcher in her field. Her commitment to both academic excellence and practical applications in statistics and data science reflects a well-rounded and impactful career.

Publications Top Notes

  1. Beta four parameter GLMM approach to evaluate paddy productivity
    • Authors: Kusumaningrum, D., Wijayanto, H., Notodiputro, K.A., Ardiansyah, M., Kurnia, A.
    • Year: 2024
  2. Comparison of Multi-satellite Rainfall Data in Runoff Model
    • Authors: Harsanto, P., Kusumaningrum, D., Legono, D., Rahardjo, A.P., Jayadi, R.
    • Year: 2024
  3. Area Yield Index and Multi-peril Crop Insurance Model Profitability Analysis
    • Authors: Suprajetno, R.I., Kusumaningrum, D., Sutomo, V.A., Anisa, R.
    • Year: 2023
  4. Pure Premium Calculation of Dry Weather-Based Insurance for Wonogiri Farmers
    • Authors: Paramita, A., Sari, F., Kusumaningrum, D., Sutomo, V.A.
    • Year: 2023
  5. Net Premium Determination of Reversionary Annuity Using Markovian Approach
    • Authors: Suardijaya, I.K.A., Kusumaningrum, D., Tobing, P.L., Tauryawati, M.L.
    • Year: 2023
  6. Premium Calculation for Paddy Plant Business Insurance (PPBI) and Microcredit Integration Program
    • Authors: Aldyan, K., Kusumaningrum, D., Hidayat, A.S.E., Sutomo, V.A.
    • Year: 2023
  7. Paddy Farmers Profiling and Estimation of Willingness to Pay Towards the AUTP and KUR Integration Program
    • Authors: Novita, L., Kusumaningrum, D., Saraswati, D.
    • Year: 2023
  8. Bayesian Premium Calculations of Multiperil Crop Insurance (MPCI) Based on Bayesian Beta Mixed Regression Model
    • Authors: Kusumaningrum, D., Sundari, M., Kurnia, A.
    • Year: 2022
  9. Alternative area yield index based crop insurance policies in Indonesia
    • Authors: Kusumaningrum, D., Anisa, R., Sutomo, V.A., Tan, K.S.
    • Year: 2021
    • Citations: 3