CALL FOR PAPERS
Next Generation Computing Applications 2026
30-31 July 2026, Mauritius
NextComp 2026 Workshops
NextComp2026 Conference will feature the following free workshops:
Workshop 1: Artificial Intelligence and Ayurveda: Shaping the Future of Personalized Healthcare
Dr. Pooja Sabharwal, BAMS, MD (Ayurveda), PhD
Ayurveda Chair, University of Mauritius
Under the aegis of the Ministry of AYUSH, Government of India
Dr. Pooja Sabharwal is an Ayurveda academician, researcher, international speaker, and administrator with expertise in Integrative Oncology, Epigenetics, Evidence-Based Ayurveda, and Global Health Diplomacy. She currently serves as the Ayurveda Chair at the University of Mauritius, deputed by the Ministry of AYUSH, Government of India, where she is actively promoting academic excellence, research, innovation, and international collaborations in Ayurveda and integrative healthcare.
A Gold Medalist in BAMS, Dr. Sabharwal obtained her MD (Ayurveda) and PhD (Ayurveda) from the National Institute of Ayurveda, Jaipur. She has held several key academic and administrative positions, including Associate Professor, OSD to the Director, In-charge Academics, and Postgraduate Coordinator at Chaudhary Brahm Prakash Ayurved Charak Sansthan (CBPACS), Government of NCT of Delhi. She has also served as Assistant Medical Superintendent at Dabur Dhanwantry Hospital and as a Consultant Ayurveda Physician with Kerala Ayurveda in Germany.
Dr. Sabharwal has represented India internationally through academic lectures, workshops, conferences, and policy dialogues across Germany, Latvia, the United Kingdom, Austria, Brazil, Thailand, Malaysia, the United Arab Emirates, Trinidad and Tobago, and Curaçao.
She serves as a QCI Assessor under NCISM, Master Trainer in Research Methodology, Scientific Writing, and Research Ethics, Associate of the Indian Knowledge System (IKS), Ministry of Education, and Expert Member of the Board of Studies at Mangalayatan University.
Her research interests include Integrative Oncology, Epigenetics and Ayurveda, Evidence-Based Ayurveda, Ayurveda Bioenergetics, Mind-Body Medicine, Sustainable Development Goals (SDGs), Artificial Intelligence in Ayurveda, and Transdisciplinary Health Research. She has authored the books Epigenetics and Ayurveda, Yoga Chakras and its Relation to Ayurveda and Cancer, and Traditional Indian Medicine and World Economic Growth @ G20 – A Review.
Dr. Sabharwal has published and presented more than 50 research papers and has received several recognitions, including the National Human Rights Award, the Ayurveda Excellence Award conferred by the Union Minister of Communication, Government of India, appreciation from the Ministry of AYUSH, and the Best Paper Presentation Award at the Ayurveda Summit (2014).
Her areas of expertise include Ayurveda education and curriculum development, integrative medicine, research methodology and ethics, quality assurance, health diplomacy, public health, innovation and entrepreneurship, sustainable development, and international academic collaboration.
Dr. Sabharwal's talk will be on Artificial Intelligence and Ayurveda: Shaping the Future of Personalized Healthcare
Artificial Intelligence (AI) has the potential to transform Ayurveda by integrating traditional wisdom with modern data-driven technologies. AI can support personalized healthcare through Prakriti-based assessment, predictive analytics, clinical decision support, disease risk stratification, and digital health applications. By combining the holistic principles of Ayurveda with AI-enabled innovation, new opportunities can be created for research, education, preventive healthcare, and precision wellness, paving the way for a more personalized and evidence-informed healthcare system.
This workshop will provide participants with a practical overview of deep learning models and their applications in computer vision and signal processing. It is designed for students, researchers, professionals, and individuals interested in understanding how modern deep learning techniques are developed and applied to real-world problems.
The workshop will begin with an introduction to Convolutional Neural Networks (CNNs), covering their fundamental concepts, architectures, and applications in both computer vision and signal processing. Participants will also be introduced to pre-trained models and transfer learning, with emphasis on how existing deep learning models can be adapted to new datasets and tasks.
Hands-on practice and demonstrations will be conducted through selected case studies in computer vision and signal processing. These sessions will guide participants through the main stages of a deep learning workflow, including data preparation, model selection, training, evaluation, and interpretation of results.
By the end of the workshop, participants will have gained a clearer understanding of key deep learning architectures, their practical applications, and the tools required to begin developing their own deep learning solutions.
Participant requirement: Participants are encouraged to bring their own laptop for the hands-on practical sessions.
Workshop 2: Deep Learning Models and Applications
By Mohammad Shoaib Casseem and Muhammad Muzzammil Auzine
Workshop 3: Responsible AI
