Dr.Asadi Srinivasulu
University of Newcastle Australia, Optficial Labs, B.Tech(CSE), M.Tech(IIIT), Ph.D., BlueCrest University College
About
Dr. Asadi Srinivasulu received his B.Tech in Computer Science Engineering (CSE) from Sri Venkateswara University, Tirupati, Andhra Pradesh, in 2000. He completed his M.Tech in Intelligent Systems (IS) from the Indian Institute of Information Technology (IIIT), Allahabad, Uttar Pradesh, India, in 2004. He is currently pursuing a double Ph.D. in Artificial Intelligence (IT) at the Indian Institute of Information Technology, Allahabad (IIIT-Allahabad), as a working professional under the supervision of Prof. Anupam Agrawal. He earned his Ph.D. in Data Science, from J.N.T.U.A, Anantapur, India, under the supervision of Prof. Ch. D. V. Subbarao. Currently, Dr. Asadi is a Visiting Researcher at crcCARE, the University of Newcastle, Australia. Previously, he worked as the Head of Research & OpenLabs in Information Technology at BlueCrest University, Monrovia, Liberia, and he has been working as a Subject Matter Expert (SME) at Deloitte, Delhi, from 2020 to 2023. He has 24 years of teaching and industrial experience and served as the Head of the Department of Information Technology at S.V College of Engineering, Tirupati from 2007-2009. Dr. Asadi expertly reviewed 96 research theses. He also holds several professional certifications, including 07 IBM Professional Certifications such as RAD, RFT, DB2, RTC, TDS, LOTUS Domino, and WID, 02 Microsoft Certifications, 03 edX Certifications, 02 TechGig Professional Certifications, 02 Cybrary Micro Certifications, 02 uDemy Certifications on Python, 02 Solo Learn Certifications on C++, 09 NPTEL Certifications, and 04 Spoken Tutorial Project Certifications from IIT-Bombay. His area of interest includes Data Science, Big Data Analytics, Data Mining, Artificial Intelligence, Robotic Process Automation, Cloud Computing, Pattern Recognition, Machine Learning, and Software Engineering. He is a professional member of several organizations, including IEEE (97608096), SCOPUS ID: 57191070975, Web of Science Researcher ID: B-9382-2018, CSI, ACM, ISTE, IAENG, IACSIT, ICST, SCIEI, VSRDIJ, NASSCOM, ASDF, Meetingfora, and ICA (Indian Congress Association). He serves on the editorial boards of several journals, including i-manager's Journal on Cloud Computing (JCC), SCIERA Journal of Computers, International Journal of Advanced Research in Computer Science and Electronics Engineering (IJARCSEE), Hindawi, Journal of Advances in Management Sciences & Information Systems, and International Journal of Research Innovations in Engineering Education. He is also a professional reviewer for several publishers, including Springer Nature, World Journal of Engineering, IEEE, Springer, Elsevier, Inderscience, Hindawi, CSI, Journal of Advances in Management Sciences & Information Systems (JAMSIS-USA), Data Mining & Knowledge Management, IAENG, Biosciences Biotechnology Research Asia (BBRA) and VSRD-CSIT. Throughout his career, he has performed various roles, such as HOD, R&D, NBA, BOS, NAAC, TEQIP-II, IIIC, NPTEL, EDC, TGMC, AICTE-SIP, STP, and IBM CoE Coordinator. He has guided 3 Ph.D. students and 5 students who are pursuing their Ph.D., as well as 14 M.Tech and 62 B.Tech students. Dr. Asadi’s key strength is Adjudicated 50 Ph.D. theses across 19 universities, reflecting strong evaluation skills and research expertise. He has published over 200+ papers, 44 of which are in SCI and 57 in Scopus & WOS, with the remaining UGC listed, in international journals and conferences. He has attended over 197 workshops, symposiums, and seminars and has conducted and acted as a resource person for more than 157 international or national conferences, workshops, symposiums, and seminars. He is an accomplished author with 9 published textbooks, including "Data Science Applications using Python Programming," "Data Science," "Machine Learning Techniques," “Navigating the Information Landscape: Exploring NLP and Information Retrieval Synergies,” “From Text to Insight: A Journey through NLP and Information Retrieval Fusion” and "Methodologies for Software Testing." He has a book under review titled "Machine Learning for Space Exploration" and he has also contributed to 36 book chapters. Additionally, he has obtained 4 patents. Dr. Asadi has received 2 DST-SERB seminar grants worth RS. 1 Lakh and 9 Lakhs, and his publications are listed in digital libraries such as Springer Nature, IEEE Xplorer, Elsevier Xplorer, Springer Xplorer, SCI Indexed, Scopus, Web of Science, World Journal of Engineering, IGI Global, IJCA, Bookman International Journal (Free), IJAIS, IJCSNS, JACRIJ, DOAJ, PDF DIGITAL LIBRARY, IJCSET, IJCSIT, IJARCET, IJARCSSE, Horizon Publication, Helix, IJEECS, CSI, and COGNIZANCE Journals. Dr. Asadi has received several awards throughout his career, including the "Bharat Vidya Ratan" national award from the International Business Council, Delhi, in 2018, and the "Best IT Teacher of the Year" award for the state ITAP-2020 from ITAP & Tutors Pride, Hyderabad. He also received the "Lifetime Achievement Excellence
Employment
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Optficial Labs Chief Advisor2026 - 2037
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University of Newcastle Australia Visiting Professor2023 - Present
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BlueCrest University College Professor, Head Research, Head of OpenLabs2020 - 2023
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Mohan Babu University Professor2000 - 2020
Education
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B.Tech(CSE), M.Tech(IIIT), Ph.D.
Projects & Funding
Projects & funding information is unavailable.
Publications (138)
- AI-Driven Generative Deep Learning Models for Viral Disease Detection: A Comprehensive Review of Challenges Ethical Implications and Future Directions Save
- A Federated and Explainable Vision-Transformer Framework Enhanced with Generative AI for Real-Time, Accurate, and Ethical Viral Disease Detection Across Diverse Clinical Modalities Save
- Classification of toxic element accumulation in rice grains using optimized machine learning models: A comparative study Save
- Enhancing Viral Disease Prediction and Detection Using ECNN and ERNN Techniques Save
- Constraints and prospects of adoption of climate smart agriculture interventions: Implication for farm sustainability Save
- Multivariate and predictive modelling of arsenic and cadmium in rice: Influence of origin, grain type, and processing Save
- Predictive Modeling of Mean Residence Time in Bubble Column Reactors: A Machine Learning Approach Using Linear Regression, Random Forest, and Neural Networks Save
- Personalized Music Recommendation System for Athletes Using EEG Signals Save
- A Comprehensive Study in the Kidney Transplantation Process with the Role of Blockchain Technology Save
- COVID-19 health data prediction: a critical evaluation of CNN-based approaches Save