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

 

 

 

 

Aniruddha Deka | Computer Science | Best Researcher Award

Dr. Aniruddha Deka | Computer Science | Best Researcher Award

Associate Professor at Assam down town University, India.

Dr. Aniruddha Deka is a respected figure in the academic and research community of Computer Science and Engineering, currently holding the position of Associate Dean (Academics) and Associate Professor at Assam down town University, Guwahati, Assam. With an impressive educational background that includes a Ph.D. in Speech Processing from Bodoland University, an M.Tech in IT from Gauhati University, and a B.E in CSE from North Eastern Hill University, Dr. Deka has built a career marked by significant achievements in teaching, research, and administration.

Professional Profiles:

Education:

Dr. Aniruddha Deka has pursued a comprehensive academic journey, culminating in significant achievements across various levels of higher education. His educational endeavors include a Ph.D. in Speech Processing from Bodoland University, earned in 2019, which underscores his specialized expertise in this domain. Prior to this, he obtained a Master’s degree in Information Technology (IT) from Gauhati University in 2012, and a Bachelor’s degree in Computer Science and Engineering (CSE) from North Eastern Hill University in 2006. Dr. Deka’s academic foundation was laid with his Higher Secondary (H.S.) education in Science from the Assam Higher Secondary Education Council in 2002, followed by his High School Leaving Certificate (H.S.L.C) from the Secondary Education Board of Assam (SEBA) in 1999. This rich educational background reflects his commitment to advancing knowledge and expertise in the field of Computer Science and Engineering.

Research Experience:

Dr. Aniruddha Deka has amassed a wealth of research experience across various domains within Computer Science and Engineering. His contributions encompass cutting-edge research in speech processing, where he has delved into innovative methods for analyzing and interpreting speech signals, thereby advancing the fields of speech recognition, synthesis, and understanding. Additionally, Dr. Deka has actively engaged in software development projects during his tenure as an Assistant Project Engineer at IIT Guwahati, demonstrating his ability to design and implement solutions to real-world problems. As an academic leader and Associate Dean (Academics), he has played a pivotal role in fostering a culture of research within his institution, providing mentorship to students and faculty members and promoting interdisciplinary collaborations. Furthermore, his industry experience as an Assistant System Engineer at TCS has equipped him with valuable insights into industry practices, facilitating collaboration between academia and industry. Dr. Deka’s diverse research portfolio underscores his dedication to advancing knowledge and driving innovation in Computer Science and Engineering.

Research Interest:

Dr. Aniruddha Deka’s research interests lie at the intersection of technology and its practical applications, particularly within the realm of Computer Science and Engineering. With a keen focus on speech processing, he seeks to unravel the complexities of analyzing and interpreting speech signals, aiming to enhance speech recognition, synthesis, and understanding technologies. Dr. Deka is also intrigued by the possibilities offered by software development, where he explores innovative solutions to real-world challenges, leveraging his expertise to create impactful tools and systems. Furthermore, as an academic leader, he is deeply committed to fostering a vibrant research culture within his institution, encouraging interdisciplinary collaborations and guiding aspiring researchers towards meaningful contributions in their respective fields. Dr. Deka’s research interests reflect his dedication to pushing the boundaries of knowledge and technology, with a vision to address pressing societal needs and drive positive change through innovative research endeavors.

Award and Honors:

Dr. Aniruddha Deka’s exceptional contributions to Computer Science and Engineering have garnered him recognition and honors throughout his career. His dedication to excellence in teaching, research, and academic leadership has been acknowledged through a variety of awards. These include the Outstanding Researcher Award, which celebrates his significant advancements in speech processing and software development, highlighting his impact on pushing the boundaries of knowledge in the field. Additionally, his role as Associate Dean (Academics) has been honored with the Excellence in Academic Leadership Award, recognizing his efforts in fostering a culture of research and academic excellence within his institution. Dr. Deka’s scholarly work has also been recognized with Best Paper Awards, underscoring the quality and significance of his research contributions. Furthermore, his industry experience and service on academic committees have earned him industry recognition and service awards, reflecting his multifaceted expertise and commitment to both academia and industry. These accolades serve as a testament to Dr. Deka’s outstanding achievements and leadership in Computer Science and Engineering, solidifying his reputation as a respected figure in the field.

Research Skills:

Dr. Aniruddha Deka possesses a diverse set of research skills honed through years of academic and professional experience in Computer Science and Engineering. With a solid foundation in research methodologies acquired during his doctoral and postgraduate studies, Dr. Deka demonstrates proficiency in experimental design, data collection, and statistical analysis. His expertise extends to conducting comprehensive literature reviews, critically evaluating existing research, and identifying gaps in knowledge to inform his own research endeavors. Dr. Deka’s strong analytical skills enable him to derive meaningful insights from complex datasets, contributing to advancements in speech processing and software development. Moreover, his collaborative approach and effective communication skills facilitate interdisciplinary collaborations, fostering innovative research projects that address real-world challenges. As an academic leader, Dr. Deka is committed to mentoring students and guiding them in developing their research skills, ensuring the next generation of researchers is equipped to make significant contributions to the field. Overall, Dr. Aniruddha Deka’s research skills, coupled with his dedication to excellence, position him as a valuable asset to the research community in Computer Science and Engineering.

Publications:

Early diagnosis of rice plant disease using machine learning techniques – M Sharma, CJ Kumar, A Deka, Archives of Phytopathology and Plant Protection, 55 (3), 259-283, 2022. Citations: 61

Assamese spoken query system to access the price of agricultural commodities – S Shahnawazuddin, D Thotappa, BD Sarma, A Deka, SRM Prasanna, et al., 2013 National Conference on Communications (NCC), 1-5, 2013. Citations: 29

Low complexity on-line adaptation techniques in context of Assamese spoken query system – S Shahnawazuddin, KT Deepak, BD Sarma, A Deka, SRM Prasanna, et al., Journal of Signal Processing Systems, 81, 83-97, 2015. Citations: 11

Land cover classification: a comparative analysis of clustering techniques using Sentinel-2 data – M Sharma, CJ Kumar, A Deka, International Journal of Sustainable Agricultural Management and Informatics, 2021. Citations: 8

A Comparative Analysis of Vegetation Radiometric Indices for Classification of Bambusa Tulda using Satellite Imagery – M Sharma, A Deka, International Journal of Computer Sciences and Engineering Open Access, 7 (1), 2019. Citations: 4

Spoken dialog system in Bodo language for agro services – A Deka, MK Deka, Advances in Electronics, Communication and Computing: ETAEERE-2016, 623-631, 2018. Citations: 4

Speaker independent speech based telephony service for agro service using asterisk and sphinx 3 – A Deka, MK Deka, Int. J. Comput. Sci. Eng. Open Access, 4, 47-52, 2016. Citations: 3

A review of physiological signal processing via Machine Learning (ML) for personal stress detection – M Lourens, SM Beram, BB Borah, AP Dube, A Deka, V Tripathi, 2022 2nd International Conference on Advance Computing and Innovative …, 2022. Citations: 2

A hybrid Grasshopper optimization algorithm for skin lesion segmentation and melanoma classification using deep learning – P Thapar, M Rakhra, M Alsaadi, A Quraishi, A Deka, JVN Ramesh, Healthcare Analytics, 100326, 2024. Citations:

HandloomGCN: Real-time handloom design generation using Generated Cellular Network – A Das, A Deka, International Journal of Computing and Digital Systems, 16 (1), 1-10, 2024.