ICACSDF 2026 features focused Special Sessions on emerging and interdisciplinary topics in cybersecurity, AI, and digital forensics. Each session is organized by domain experts and brings together high-quality research contributions for in-depth discussion and collaboration.
Browse the confirmed special sessions for ICACSDF 2026. More sessions will be added as proposals are accepted.
This special session has been accepted. Full details including topics, organizers, and submission information will be published shortly. Please check back soon.
This special session focuses on developing robust, explainable, and secure AI-driven systems for data-intensive and real-time applications. It brings together researchers at the intersection of AI, IoT, and secure intelligent systems, with emphasis on trustworthy and privacy-aware solutions for wearable biomedical and digital health environments.
This special session focuses on the application of deep learning techniques in image processing for digital forensics. The session aims to bring together researchers and practitioners working on advanced AI-driven methods to analyze, enhance, and authenticate digital images in forensic investigations — spanning detection, explainability, and low-quality image recovery.
This special session explores the application of artificial intelligence and machine learning to modern malware analysis and cyber threat intelligence. It brings together researchers and industry practitioners working on static/dynamic malware analysis, botnet detection, polymorphic threat modelling, and SOC-integrated AI defences — bridging academic research with real-world endpoint protection challenges.
Additional special sessions are currently under review. This page will be updated as sessions are confirmed.
Propose a Special SessionSession 02 is organized by distinguished researchers from UPES Dehradun and MANIT Bhopal.
Assistant Professor (Senior Scale) at UPES Dehradun. She completed her Ph.D. from MANIT Bhopal with research focused on robust, interpretable, and resource-efficient frameworks for Human Activity Recognition (HAR) using wearable sensor data. Her work spans multimodal data (IMU and sEMG), explainable AI (XAI), and edge-deployable AI for personalized healthcare. Published in IEEE Sensors Journal, IEEE Transactions on Consumer Electronics, Applied Soft Computing, and Neural Computing and Applications.
Assistant Professor (Senior Scale) in the School of Computer Science (AI Cluster) at UPES Dehradun. Ph.D. from MANIT, Bhopal. His research spans machine learning, optimization techniques, and support vector machines (SVM), with contributions to noise-robust SVM variants, image classification, and deep learning in healthcare analytics. Published in Information Sciences, Expert Systems with Applications, and Biomedical Signal Processing and Control.
Assistant Professor at MANIT Bhopal since 2019. Ph.D. in Robotics and Artificial Intelligence from IIIT Allahabad (2017). Has previously served at NIT Rourkela, IIIT Dharwad, and NIT Jamshedpur. Research interests include Human–Robot Interaction, wearable sensor-based healthcare, HAR, gait analysis, IoT, and AI. Author of 50+ SCI/SCOPUS-indexed publications, recipient of the DST-SERB Early Career Research Award (ECRA), and Senior Member of IEEE.
Session 03 is organized by researchers from IIT Patna, IIT Bombay, and IIIT Ranchi, working at the intersection of Biomedical Image Processing, AI, and Generative AI.
Assistant Professor at the School of Computer Science, UPES Dehradun. Prior to joining UPES, he served as Ad-hoc Faculty in the Department of Computer Science at NIT Patna. He completed his Ph.D. from the Department of Electrical Engineering, IIT Patna. His research focuses on the intersection of Biomedical Image Processing and Artificial Intelligence.
Assistant Professor at the School of Computer Science, UPES, working at the intersection of machine learning, deep learning, and healthcare. He holds a Ph.D. (2024) in Electrical Engineering from IIT Patna and completed a postdoctoral fellowship at IIT Bombay before joining UPES.
Assistant Professor in the Department of Electronics and Communication at IIIT Ranchi. He completed his Ph.D. from the Department of Electrical Engineering, IIT Patna. His research focuses on the intersection of Generative AI and Machine Learning.
Session 04 is organized by industry-academia experts bridging malware research, threat intelligence, and AI-driven security operations.
A cybersecurity researcher with 14+ years of expertise in malware analysis and threat intelligence. He holds a Ph.D. from BITS Pilani and a law degree in cyber crime, bridging academia and industry. As Cybersecurity Advisor at WatchGuard Technologies and an IIT Kanpur postdoctoral fellow, he has published extensively on Android malware, botnet analysis, and polymorphic threats. His work integrates static/dynamic analysis with machine learning for real-world SOC security challenges.
Senior Security and Compliance Specialist at Atari Inc. with 8+ years of experience in information security, compliance, threat analysis, and cyber risk management. His expertise spans security governance, ISO 27001 & SOC 2 compliance, security awareness, and operational cyber defence. He has prior experience in malware analysis and ML-based security research, and is currently pursuing a Ph.D. focused on multi-source threat detection and classification using machine learning.
