Computational Techniques in Neuroscience (ePub)
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The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis.
Dr. Harsh Sadawarti is currently working as Vice Chancellor of CT University and Professor of Computer Science and Engineering in School of Engineering and Technology at CTU Ludhiana, Punjab India. He has published Scientific research Publications in reputed International Journals including SCI indexed and Scopus indexed Journals
Mr. Moolchand Sharma is currently an Assistant Professor in the Department of Computer Science and Engineering at the Maharaja Agrasen Institute of Technology, GGSIPU Delhi. He has published scientific research publications in reputed international journals and conferences, including SCI-indexed and Scopus-indexed journals such as Expert Systems (Wiley), Cognitive Systems Research (Elsevier), Physical Communication(Elsevier), Journal of Electronic Imaging (SPIE ), Intelligent Decision Technologies: An International Journal, Cyber-Physical Systems (Taylor & Francis Group), International Journal of Image & Graphics (World Scientific), International Journal of Innovative Computing and Applications (Inderscience) and Innovative Computing and Communication Journal (Scientific Peer-reviewed Journal). He has authored/co-authored chapters with International publishers like Elsevier, Wiley, and De Gruyter. He has authored/edited four books with a National/International level publisher (CRC Press, Bhavya publications). His research areas include Artificial Intelligence, Nature-Inspired Computing, Security in Cloud Computing, Machine Learning, and Search Engine Optimization. He is associated with various professional bodies like IEEE, ISTE, IAENG, ICSES, UACEE, Internet Society, and life membership of the Universal Inovators research lab, etc. He possesses teaching experience more than nine years. He is the co-convener of the ICICC, DOSCI, ICDAM & ICCCN springer Scopus Indexed conference series and ICCRDA-2020 Scopus Indexed IOP Material Science & Engineering conference series. He is also the organizer and co-convener of the International Conference on Innovations and Ideas towards Patents (ICIIP) series. He is also the advisory and TPC committee member of the ICCIDS-2022 Elsevier SSRN Conference. He is also the reviewer of many reputed journals like Springer, Elsevier, IEEE, Wiley, Taylor & Francis Group, IJEECS and World Scientific Journal, and many springer conferences. He is also served as a session chair in many international springer conferences. He is a doctoral researcher at DCR University of Science & Technology, Haryana. He completed his Post Graduation in 2012 from SRM UNIVERSITY, NCR CAMPUS, GHAZIABAD, and Graduated in 2010 from KNGD MODI ENGG. COLLEGE, GBTU.
Dr. Umesh Gupta is currently an Assistant Professor at the School of Computer Science Engineering and Technology at Bennett University, Times of India Group, Greater Noida, Uttar Pradesh, India. He received a Doctor of Philosophy (Ph.D.) (Machine Learning) from the National Institute of Technology, Arunachal Pradesh, India. He has awarded a gold medalist for his Master of Engineering (M.E.) from the National Institute of Technical Teachers Training and Research (NITTTR), Chandigarh, India, and Bachelor of Technology (B.Tech.) from Dr. APJ, Abdul Kalam Technical University, Lucknow, India. His research interests include SVM, ELM, RVFL, machine learning, and deep learning approaches. He has published over 35 referred journal and conference papers of international repute. His scientific research has been published in reputable international journals and conferences, including SCI-indexed and Scopus-indexed journals like Applied soft computing (Elsevier) and Applied Intelligence (Springer), each of which is a peer-reviewed journal. His publications have more than 158 citations with an h-index of 8 and an i10-index of 8 on Google Scholar as of March 1, 2023. He is a senior Member of IEEE (SMIEEE) and an active member of ACM, CSTA, and other scientific societies. He also reviewed papers for many scientific journals and conferences in the US and abroad. He led sessions at the 6th International conference (ICICC-2023), 3rd International Conference on Data Analytics and Management (ICDAM 2023), the 3rd International Conference on Computing and Communication Networks (ICCCN 2022), and other international conferences like Springer ETTIS 2022 and 2023. He is currently supervising two Ph.D. students. He is the co-principal investigator (co-PI) of TWO major research projects. He published three patents in the years 2021-2023. He also published four book chapters with Springer, CRC.
Dr. Prayag Tiwari received his Ph.D. degree from the University of Padova, Italy. He is currently working as a Postdoctoral Researcher at Aalto University. Previously, he worked as a Marie Curie Researcher at the University of Padova, Italy. He also worked as a research assistant at the NUST ``MISiS", Moscow, Russia. He has several publications in top journals and conferences, including Neural Networks, Information Fusion, IPM, IJCV, IEEE TNNLS, IEEE TFS, IEEE TII, IEEE JBHI, IEEE IOTJ, IEEE BIBM, ACM TOIT, CIKM, SIGIR, AAAI, etc. His research interests include Machine Learning, Deep Learning, Quantum Machine Learning, Information Retrieval, Healthcare, and IoT. He is also associated with one Funded-based project named "Data Literacy for Responsible Decision-Making" Short title (STN LITERACY/Marttinen). He is also the reviewer of many reputed journals like Springer, Elsevier, IEEE, Wiley, Taylor & Francis Group, IJEECS and World Scientific Journal, and many springer conferences.
- 2023, 1. Auflage, 242 Seiten, Englisch
- Herausgegeben: Kamal Malik, Harsh Sadawarti, Moolchand Sharma, Umesh Gupta, Prayag Tiwari
- Verlag: Taylor & Francis
- ISBN-10: 100099421X
- ISBN-13: 9781000994216
- Erscheinungsdatum: 14.11.2023
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- Dateiformat: ePub
- Größe: 4.04 MB
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