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

 

 

 

 

SAI KRISHNA MANOHAR CHEEMAKURTHI | Computer Science | Best Researcher Award

Mr. Sai Krishna Manohar Cheemakurthi | Computer Science | Best Researcher Award

Sai Krishna Manohar Cheemakurthi, U.S. BANK, United States.

Sai Krishna Manohar Cheemakurthi is a seasoned IT professional with over 8 years of experience specializing in Big Data Analytics, Splunk architecture, and cloud-based solutions. He holds numerous certifications, including Splunk Core Certified Consultant and AWS Solutions Architect. Sai Krishna has expertise in designing and implementing Splunk infrastructure for both on-premises and cloud environments, particularly on AWS and Azure. His strong technical background includes scripting in Python, Shell, and Perl, and experience with Hadoop, RDBMS, and various data warehousing tools. Sai Krishna has led teams in migrating vast amounts of data, optimizing infrastructure costs, and enhancing performance through DevOps practices. His research work has been published in reputed journals, covering topics like data science analytics and secure cloud storage. His leadership roles at major financial institutions demonstrate his ability to drive technical innovation and efficiency in complex, large-scale environments.

Profile:

Education

Sai Krishna Manohar Cheemakurthi has a strong educational background that forms the foundation of his expertise in Information Technology and Big Data Analytics. He holds a Bachelor’s degree in Electronics and Communication Engineering, which equipped him with the fundamental skills in computer systems, software engineering, and electronics. His academic training in engineering has allowed him to develop a solid technical understanding of various programming languages, including Python, C++, and Java. Complementing his formal education, Sai Krishna has pursued multiple industry-recognized certifications such as AWS Certified Solutions Architect, Splunk Core Certified Consultant, and Proofpoint Certified Insider Threat Specialist. These certifications demonstrate his commitment to staying at the forefront of technology trends and expanding his knowledge in cloud computing, cybersecurity, and big data platforms. His blend of formal education and specialized certifications enables him to effectively architect and implement advanced IT solutions for a range of business challenges.

Professional Experiences 

Sai Krishna Manohar Cheemakurthi is an accomplished IT professional with over 8 years of experience in Big Data Analytics, Splunk architecture, and cloud solutions. Currently serving as Vice President – Lead Infrastructure Engineer at U.S. Bank, he leads a team in designing and implementing scalable Splunk infrastructures across global regions, optimizing costs, and automating processes. Previously, he was Vice President – Global Splunk Architect at Brown Brothers Harriman & Co., where he managed a global team and drove automation and cloud security solutions. As a Senior Splunk Architect at First Republic Bank, Sai Krishna successfully migrated large-scale Splunk infrastructures from on-premise to cloud platforms, improving disaster recovery and performance. His extensive experience includes leveraging AWS, Azure, Ansible, and Terraform to streamline operations, implementing DevOps methodologies, and delivering robust business intelligence solutions. Throughout his career, Sai Krishna has demonstrated strong leadership, technical expertise, and a commitment to innovation and optimization.

Awards and Honors

Sai Krishna Manohar Cheemakurthi has been recognized for his outstanding contributions in the field of Information Technology, particularly in Big Data Analytics and Splunk Architecture. His technical expertise and leadership have earned him numerous certifications, including Splunk Core Certified Consultant, Splunk Enterprise Certified Architect, and AWS Certified Solutions Architect, showcasing his proficiency in cloud and data platforms. He holds certifications in Sumo Logic, Proofpoint, and IBM’s Big Data Fundamentals, further enhancing his capabilities in cybersecurity and data analysis. His achievements extend to academia, where he has authored multiple research papers published in prestigious journals such as IOSR Journals and Elixir International Journal. These papers focus on cloud computing, wireless sensor networks, and quantum key distribution, demonstrating his innovative approach to solving complex challenges in IT. Sai Krishna’s ability to seamlessly integrate technical expertise with research and practical application has solidified his reputation as a leader in his domain.

Research Interest

Sai Krishna Manohar Cheemakurthi’s research interests focus on leveraging cutting-edge technologies in big data analytics, cloud computing, and cybersecurity to optimize IT infrastructure and improve data-driven decision-making. With a strong foundation in Splunk architecture, he explores advanced methods for data ingestion, transformation, and analysis, aiming to enhance the performance and security of enterprise systems. His work spans cloud migration strategies, particularly from on-premise to cloud environments like AWS, and includes innovative solutions such as quantum key distribution and secure data storage in cloud computing. Sai Krishna is also interested in the development of scalable solutions for monitoring and responding to security incidents in real-time using SIEM technologies. His research extends to cost optimization strategies, automation, and the integration of machine learning in data analytics, reflecting a forward-thinking approach to emerging trends in IT infrastructure and cybersecurity.

Research Skills

Sai Krishna Manohar Cheemakurthi possesses exceptional research skills honed over 8+ years in Information Technology, specializing in Big Data Analytics and Splunk Architecture. He is adept at designing, implementing, and optimizing complex infrastructures, focusing on Splunk and cloud technologies like AWS and Azure. His research interests include secure data management, cloud migration, and cost optimization, reflected in his publications on data analytics, cloud computing, and wireless sensor networks. Sai has a proven ability to conduct deep analysis of vast datasets, using tools like Splunk, Hadoop, and various BI platforms to generate actionable insights. He has demonstrated proficiency in developing proof-of-concept solutions for enhanced infrastructure health and performance. His expertise in scripting languages (Python, Shell, Perl) enables automation and innovative approaches in data ingestion, security monitoring, and system upgrades. Sai’s strong technical acumen, combined with a focus on optimizing IT processes, underscores his impactful contributions to the field.

Publication Top Notes
  • Cloud Observability In Finance: Monitoring Strategies For Enhanced Security
    • Authors: NB Kilaru, SKM Cheemakurthi
    • Year: 2023
    • Journal: NVEO-Natural Volatiles & Essential Oils
    • Volume/Issue/Page: 10(1), 220-226
  • Mitigating Threats in Modern Banking: Threat Modeling and Attack Prevention with AI and Machine Learning
    • Authors: SK Manohar, V Gunnam, NB Kilaru
    • Year: 2022
    • Journal: Turkish Journal of Computer and Mathematics Education (TURCOMAT)
  • Next-gen AI and Deep Learning for Proactive Observability and Incident Management
    • Authors: NBK Sai Krishna Manohar Cheemakurthi, Vinodh Gunnam
    • Year: 2022
    • Journal: Turkish Journal of Computer and Mathematics Education
    • Volume/Issue/Page: 13(3), 1550-1564
  • Scaling DevOps with Infrastructure as Code in Multi-Cloud Environments
    • Authors: NBK Sai Krishna Manohar Cheemakurthi, Vinodh Gunnam
    • Year: 2022
    • Journal: Turkish Journal of Computer and Mathematics Education
    • Volume/Issue/Page: 13(3), 1189-1200
  • Advanced Anomaly Detection In Banking: Detecting Emerging Threats Using SIEM
    • Authors: NBK Sai Krishna Manohar Cheemakurthi, Vinodh Gunnam
    • Year: 2021
    • Journal: International Journal of Computer Science and Mechatronics (IJCSM)
    • Volume/Issue/Page: 7(04), 28-33
  • Analytics of Data Science using Big Data
    • Authors: CSK Manohar
    • Year: 2013
    • Journal: IOSR Journal of Computer Engineering
    • Volume/Issue/Page: 10(2), 19-21
  • AI-Powered Fraud Detection: Harnessing Advanced Machine Learning Algorithms for Robust Financial Security
    • Authors: SKM Cheemakurthi, NB Kilaru, V Gunnam
    • Year: (Not provided)
  • Deep Learning Models For Fraud Detection In Modernized Banking Systems: Cloud Computing Paradigm
    • Authors: Y Vasa, SKM Cheemakurthi, NB Kilaru
    • Year: (Not provided)
  • SOAR Solutions in PCI Compliance: Orchestrating Incident Response for Regulatory Security
    • Authors: NB Kilaru, SKM Cheemakurthi, V Gunnam
    • Year: (Not provided)
  • AI-Driven SOAR in Finance: Revolutionizing Incident Response and PCI Data Security with Cloud Innovations
    • Authors: V Gunnam, SKM Cheemakurthi, NB Kilaru
    • Year: (Not provided)