Dr. Vinod Kumar
Working as Associate Professor and Research Coordinator in the Department of Computer Science and Engineering, Chandigarh University.
Dr. Vinod Kumar: Pioneering Researcher and Educator in Computer Science with a Remarkable Journey.
Dr. Vinod Kumar is a distinguished academic and researcher who has achieved remarkable accomplishments in the field of Computer Science and Engineering. Graduating with a Ph.D. in Computer Science and Engineering from I.K. Gujral Punjab Technical University in May 2023, Dr. Kumar's journey is one of resilience and dedication.
Surviving lung cancer, he has channeled his passion into developing cutting-edge diagnostic approaches for lung cancer. His commitment to this cause is underscored by his involvement with prestigious organizations like the International Association for the Study of Lung Cancer (IASLC) and the Indian Society for the Study of Lung Cancer (ISSLC). These associations exemplify his mission to advance lung cancer detection through innovative technologies.
Dr. Kumar's academic achievements are extensive. He qualified the UGC-NET exam in 2012 and holds an M.Tech. (2012) and a B.Tech. (2009) in Computer Science and Engineering. His educational prowess extends further with a Diploma in Computer Engineering (1995). With over a decade of teaching experience, he currently serves as an Assistant Professor at the Panipat Institute of Engineering and Technology, affiliated with Kurukshetra University and approved by AICTE, New Delhi.
His research contributions are impressive, with 29 research papers published in international journals and conferences, two authored and edited books, and two contributed book chapters published by Taylor & Francis. Dr. Kumar's intellectual property includes an Indian patent, reflecting his innovative thinking and technological insights.
Dr. Kumar's expertise spans diverse domains, including Artificial Intelligence, Machine Learning, Computer Networks, Unix & Linux programming, and Computer Organization and Architecture. His fascination with medical image processing and deep learning highlights his multidisciplinary approach.
Furthermore, Dr. Kumar's global engagement is noteworthy. He has presented research at international conferences and attended lung cancer-focused meetings in Canada, Spain, Singapore, and the USA. His international exposure has enriched his perspective and contributed to his impactful work.
Beyond academia, Dr. Kumar's personal journey adds depth to his profile. A cancer survivor for 27 years, he attributes his recovery to holistic practices such as living foods, nature care, meditation, and yoga science. His story serves as a powerful motivation for others.
Notably, Dr. Kumar's talents extend beyond the realm of academia. He is a gifted singer and songwriter, showcasing his creativity and artistic expression.
In summary, Dr. Vinod Kumar's biography is a testament to his unwavering dedication to education, research, and innovation in Computer Science. His triumph over adversity, extensive contributions to academia, and commitment to advancing lung cancer detection exemplify his impactful journey.
Address: India
Dr. Vinod Kumar: Pioneering Researcher and Educator in Computer Science with a Remarkable Journey.
Dr. Vinod Kumar is a distinguished academic and researcher who has achieved remarkable accomplishments in the field of Computer Science and Engineering. Graduating with a Ph.D. in Computer Science and Engineering from I.K. Gujral Punjab Technical University in May 2023, Dr. Kumar's journey is one of resilience and dedication.
Surviving lung cancer, he has channeled his passion into developing cutting-edge diagnostic approaches for lung cancer. His commitment to this cause is underscored by his involvement with prestigious organizations like the International Association for the Study of Lung Cancer (IASLC) and the Indian Society for the Study of Lung Cancer (ISSLC). These associations exemplify his mission to advance lung cancer detection through innovative technologies.
Dr. Kumar's academic achievements are extensive. He qualified the UGC-NET exam in 2012 and holds an M.Tech. (2012) and a B.Tech. (2009) in Computer Science and Engineering. His educational prowess extends further with a Diploma in Computer Engineering (1995). With over a decade of teaching experience, he currently serves as an Assistant Professor at the Panipat Institute of Engineering and Technology, affiliated with Kurukshetra University and approved by AICTE, New Delhi.
His research contributions are impressive, with 29 research papers published in international journals and conferences, two authored and edited books, and two contributed book chapters published by Taylor & Francis. Dr. Kumar's intellectual property includes an Indian patent, reflecting his innovative thinking and technological insights.
Dr. Kumar's expertise spans diverse domains, including Artificial Intelligence, Machine Learning, Computer Networks, Unix & Linux programming, and Computer Organization and Architecture. His fascination with medical image processing and deep learning highlights his multidisciplinary approach.
Furthermore, Dr. Kumar's global engagement is noteworthy. He has presented research at international conferences and attended lung cancer-focused meetings in Canada, Spain, Singapore, and the USA. His international exposure has enriched his perspective and contributed to his impactful work.
Beyond academia, Dr. Kumar's personal journey adds depth to his profile. A cancer survivor for 27 years, he attributes his recovery to holistic practices such as living foods, nature care, meditation, and yoga science. His story serves as a powerful motivation for others.
Notably, Dr. Kumar's talents extend beyond the realm of academia. He is a gifted singer and songwriter, showcasing his creativity and artistic expression.
In summary, Dr. Vinod Kumar's biography is a testament to his unwavering dedication to education, research, and innovation in Computer Science. His triumph over adversity, extensive contributions to academia, and commitment to advancing lung cancer detection exemplify his impactful journey.
Address: India
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Papers by Dr. Vinod Kumar
cancer. Medical professionals look time as one of the important parameter to discover the cancer in the patient at the earlier stage; which is very important for successful treatment. The present paper presents a methodology for accurate diagnosing of lung nodule based on x-ray imaging. This research work focuses on finding nodules, early symptoms of cancer diseases, appearing in patient’s lungs. The author uses a modified Watershed Segmentation approach to isolate a lung of an x-ray image. It further evaluates for identifying the pixels of an affected nodule. Most of the nodules can be observed after carefully selection of parameters. The primary objective is to atomize these selections. The training dataset of x-ray images of lung cancer are processed in three stages to attain more quality and accuracy in the observational results: pre-processing stage, feature extraction stage and identification of lung cancer nodule.
paper presents a neural network based approach to detect lung cancer from raw chest X-ray images. The author use an image processing technique to remove noise using various filters and segment the lung to detect abnormal regions in the X-ray image and extracted regions that demonstrate area, perimeter and shape characteristics of lung nodules. These shape features are considered as the inputs to train a neural network and to verify whether a region is a malignant nodule or not. This research work concentrate on detecting nodules, early stages of cancer diseases, appearing in patient’s lungs. Most of the nodules can be observed after carefully selection of parameters. The training dataset of X-ray images of lung cancer are processed in three stages to attain more quality and accuracy in the observational results.
Conference Presentations by Dr. Vinod Kumar
cancer. Medical professionals look time as one of the important parameter to discover the cancer in the patient at the earlier stage; which is very important for successful treatment. The present paper presents a methodology for accurate diagnosing of lung nodule based on x-ray imaging. This research work focuses on finding nodules, early symptoms of cancer diseases, appearing in patient’s lungs. The author uses a modified Watershed Segmentation approach to isolate a lung of an x-ray image. It further evaluates for identifying the pixels of an affected nodule. Most of the nodules can be observed after carefully selection of parameters. The primary objective is to atomize these selections. The training dataset of x-ray images of lung cancer are processed in three stages to attain more quality and accuracy in the observational results: pre-processing stage, feature extraction stage and identification of lung cancer nodule.
paper presents a neural network based approach to detect lung cancer from raw chest X-ray images. The author use an image processing technique to remove noise using various filters and segment the lung to detect abnormal regions in the X-ray image and extracted regions that demonstrate area, perimeter and shape characteristics of lung nodules. These shape features are considered as the inputs to train a neural network and to verify whether a region is a malignant nodule or not. This research work concentrate on detecting nodules, early stages of cancer diseases, appearing in patient’s lungs. Most of the nodules can be observed after carefully selection of parameters. The training dataset of X-ray images of lung cancer are processed in three stages to attain more quality and accuracy in the observational results.