Abhishek Shukla is a well-established Principal Software Engineer with over 16 years of stints in the technology world. He did his Master's from Syracuse University, New York, USA. In fact, over these years, Abhishek has contributed immensely to the field of AI, ML, and Software Engineering by authoring 19 scholarly articles. Apart from research, Abhishek has contributed to more than 100 conferences as a technical program committee member, reviewer, keynote speaker, and advisory board member. The career path for Abhishek includes stints in India, South Korea, and the USA; his versatility fits all kinds of professional environments. He has demonstrated outstanding contributions toward AI and ML for e-commerce applications-features that put him in a league of leadership within global technologies. Currently, Abhishek continues to drive innovation and excellence in technology, integrating wide experiences and an academic foundation into furthering the fields of AI, ML, and Software Engineering.

Adaptive AI Architectures for Scalable Cybersecurity: Leveraging NVIDIA Technologies for Threat Detection Abstract: As cyber threats grow in complexity, integrating artificial intelligence (AI) with robust cybersecurity frameworks is critical for resilient digital ecosystems. This presentation introduces an adaptive AI architecture designed for scalable cybersecurity, leveraging NVIDIA’s A100 GPUs, Triton Inference Server, and CUDA-X libraries to enhance threat detection and response. The proposed framework employs dynamic orchestration and hybrid cloud-edge designs to achieve low-latency inference (~90 ms) and high throughput (15,000 requests/second), addressing enterprise-scale challenges in real-time threat mitigation. By integrating machine learning models with privacy-preserving techniques like federated learning and secure multi-party computation, the architecture ensures GDPR compliance and data integrity.