The latest issue of our chapter's signature publication, "The Cognitive Nexus," offers perspectives on advanced applications and security challenges in computational intelligence, primarily focusing on three areas: robust AI systems, retail technology integration, and AI security architecture.

One of the articles introduces a cognitive neuro-symbolic reinforcement learning (CNS-RL) framework designed to improve the robustness and explainability of agents in dynamic environments like Procgen (for procedurally generated games) by unifying causal reasoning and temporal logic constraints.

Another article presents a case study on a Real-Time AI-Driven Omnichannel Synchronization Framework for retail, detailing how machine learning models like XGBoost and BERT, combined with edge computing, can optimize demand forecasting, customer engagement, and operational efficiency across e-commerce and point-of-sale (POS) systems.

A pair of articles address the critical issue of AI security, with one proposing a comprehensive evaluation suite (Secure-RAG) to assess the reliability and safety of Retrieval-Augmented Generation (RAG) pipelines, while the other analyzes the complex threat landscape of agentic AI systems using the Model Context Protocol (MCP), mapping over twenty attack vectors across five architectural layers and suggesting layered defense strategies.

Read the issue here: https://lnkd.in/gCg7dwtk.

Watch an overview here: https://lnkd.in/g-FUVrQS

Congratulations to the editorial team, Vishnu Pendyala, Rahul Raja, and Arpita V., for bringing out the issue on time.

The podcast presents some distinct research papers from the "Feedforward" magazine. The first paper proposes a deep learning approach for interpreting ECG signals and detecting pathologies, utilizing models like ResNet-18 and U-Net for classification and segmentation of heart conditions. The second paper introduces optimized techniques for scalable parallel processing of dynamic graphs, focusing on a hybrid model that integrates message-passing and shared-memory concepts for efficiency in applications like social media analytics. The third paper details an LLM-powered API Navigator, an intelligent assistant designed to simplify understanding complex API specifications using AI for semantic search and query processing. Together, these documents highlight advancements in AI applications across medical diagnostics, complex data analysis, and software development tools, emphasizing the role of machine learning in addressing real-world challenges.

A discussion on the articles from the inaugural issue of The Cognitive Nexus, a quarterly magazine published by the IEEE Computational Intelligence Society, Santa Clara Valley Chapter. These articles explore various applications of artificial intelligence and machine learning. Topics include "Advancing Collaborative Intelligence Through Model Context Protocol", which details a new framework for AI system collaboration; "AI-Powered Chess Insights", showcasing real-time chess analysis using computer vision and large language models; "Machine Learning for Predicting Displacement Patterns in Conflict Zones", focusing on humanitarian aid in South Sudan; and "Leveraging AI Models for Proactive Problem Detection... in Enterprise IT Infrastructure", which discusses AI's role in IT operations. Additionally, "Enhancing Financial Network Threat Detection" examines how unsupervised learning and generative AI can improve financial security.

Editor: Vishnu S. Pendyala, Ph.D.

Editorial Board Members:

Rahul Raja

Arpita Vats

A conversation on the articles published in Feedforward April - June 2025

After a brief intro highlighting issues and solutions for data privacy in machine learning settings, Prof. Gautam Kamath answers questions related to data privacy, machine unlearning, research, academia, career advice, and anything in between.

The panel discussion explores the potential of generative AI in enhancing medical care. Generative AI holds immense promise for transforming healthcare, but ethical considerations, thorough validation, and responsible implementation are essential. Careful attention to these challenges will unlock the full potential of AI to improve diagnosis, treatment, and overall patient care. The panelists delved into a range of questions on leveraging the predictive power of GenAI for personalized medicine, enhanced diagnostics, ethical dilemmas, and more.

Topics covered include neuromorphic hardware, spiking neural networks, big data processing frameworks, Hadoop, Spark, Mining Streaming data

Speaker, Raghavendra K. Chunduri is working as a Postdoctoral Research Fellow in the Department of Electrical and Computer Engineering, at the University of Colorado, Colorado Springs

Moderator, Vishnu S. Pendyala, PhD is a faculty in Applied Data Science at San Jose State University.

Panelists:

Dr. Katharina Koerner, Tech Diplomacy Network, USA

Recently, the news media has been filled with reports and debates on the powers and dangers of Artificial Intelligence. Adding to the confusion, even experts have been differing in their opinions. This panel discussion is intended to help clarify and provide interesting perspectives on the topic. It was featured in ICADS ’23: Second International Conference on Applied Data Science organized by the chapter.

Panelists: Prof. Charalampos Patrikakis, Manish Mradul, Dr. Vishnu Pendyala, Prasanna Vijayanathan, Krupa Kothadia