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Mr. Shahzeb Khan | Time series | Best Researcher Award

Assistant Professor at Sharda University, India.

Shahzeb Khan is a dedicated data scientist with a passion for teaching and research. Holding an M.Tech from Mahatma Gandhi Central University Bihar and a B.Tech from AKTU Uttar Pradesh, he has consistently demonstrated academic excellence. With professional experience as an Assistant Professor in Computer Science & Applications at Sharda University and Jagannath University College JIMS, Shahzeb has honed his skills in big data analytics, data science, and data analytics. He has also contributed to the field of data science as a freelance trainer and through his research endeavors, including a paper accepted in the prestigious journal Biomedical Signal Processing and Control. Shahzeb’s expertise spans statistical analysis, machine learning, deep learning, and programming languages like Python, R, and C. With a commitment to continuous learning and a diverse skill set, he seeks to make impactful contributions to the field of data science and academia.

Professional Profiles:

Education

Mr. Shahzeb Khan pursued his M.tech from Mahatma Gandhi Central University Bihar, graduating in 2023 with an impressive CGPA of 8.5. Prior to that, he completed his B.tech from AKTU Uttar Pradesh in 2020, achieving a CGPA of 6.8. His academic journey began with his Intermediate and Matriculation from CBSE in 2015 and 2013 respectively, where he demonstrated strong academic performance. Throughout his education, Shahzeb has shown a commitment to excellence and a passion for learning, evident in his consistent academic achievements and his pursuit of knowledge in diverse fields.

Professional Experience

Mr. Shahzeb Khan has garnered diverse professional experience across the fields of education, data science, and software development. Currently serving as an Assistant Professor of Computer Science & Applications at Sharda University, Greater Noida, he imparts knowledge in various subjects, demonstrating his expertise in big data analytics, data science, and data analytics. Previously, he held the position of Assistant Professor of Data Science at Jagannath University College JIMS, where he taught courses on data analytics and big data analytics. Additionally, Shahzeb has worked as a freelancer data science trainer, conducting training sessions for industries. He also gained valuable experience as a website developer intern at IIY Software Pvt Ltd and contributed as a key coordinator in the Time Series Machine Learning (TSML) 2023 summer training program at MGCUB. Through these roles, Shahzeb has showcased his versatility, leadership, and dedication to both academia and practical application in the field of data science and technology.

Research Interest

Mr. Shahzeb Khan’s research interests lie at the intersection of data science and healthcare, with a particular focus on clinical data analysis and predictive modeling. His research endeavors encompass the development and implementation of machine learning and deep learning techniques for analyzing medical data, especially electrocardiogram (ECG) time series data. He is passionate about leveraging advanced algorithms to enhance the accuracy of disease diagnosis and prognosis, particularly in the context of cardiovascular diseases. Additionally, Shahzeb is interested in exploring statistical, machine learning, and deep learning models for various healthcare applications, aiming to contribute to advancements in predictive analytics and personalized medicine.

Award and Honors

Mr. Shahzeb Khan has been recognized with several prestigious awards and honors for his outstanding contributions to the field of data science and academia. Noteworthy among these accolades is his certification as a Microsoft Technical Associate Front End Web Developer, showcasing his proficiency in web development technologies. Additionally, he has been acknowledged as a Certified Clinical Analyst, demonstrating his expertise in utilizing Software as a Service (SaaS) for clinical data analysis. Furthermore, Mr. Khan played a pivotal role as a key coordinator in the TSML (Time Series Machine Learning) 2023 Summer Training Program at MGCUB, highlighting his leadership and organizational skills. Moreover, his research paper titled “A Novel Hybrid GRU-CNN and Residual Bias (RB) based RB-GRU-CNN Models for Prediction of PTB Diagnostic ECG Time Series Data” was accepted in the prestigious Q1 journal Biomedical Signal Processing and Control, further solidifying his reputation as a distinguished researcher in the field. These honors underscore Mr. Shahzeb Khan’s dedication to excellence and his significant impact in advancing the realms of data science and healthcare analytics.

Research Skills

Mr. Shahzeb Khan possesses a diverse range of research skills that enable him to excel in the field of data science and academia. His proficiency in statistical analysis allows him to conduct rigorous evaluations of various models and techniques, aiding in the selection of optimal methodologies for data analysis and prediction. Furthermore, he demonstrates expertise in machine learning, deep learning, and artificial neural network (ANN) training, utilizing these techniques to develop advanced predictive models and algorithms. Additionally, Mr. Khan is adept at programming languages such as Python, R, and C, enabling him to implement complex algorithms and conduct extensive data manipulation tasks. His problem-solving abilities, coupled with a strong foundation in data structures and algorithms, empower him to tackle challenging research problems effectively. Moreover, Mr. Shahzeb Khan’s theoretical understanding of computer science concepts further enriches his research capabilities, allowing him to contribute meaningfully to the advancement of knowledge in his field.

 

 

 

Shahzeb Khan | Time series | Best Researcher Award

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