Publications

A distributed framework leveraging Apache Spark for statistically rigorous LLM evaluation at scale. Treats evaluation as a data-parallel problem, providing bootstrap confidence intervals, statistical significance tests (paired t-tests, McNemar's test, Wilcoxon signed-rank), and content-addressable response caching backed by Delta Lake. Reports linear scaling performance.

A quality-diversity evolutionary framework operating at the semantic level for LLM adversarial testing. Uses MAP-Elites to maintain a diverse archive of interpretable attack strategies across behavioral dimensions, revealing distinct vulnerability profiles across GPT-4o-mini, Claude 3.5 Sonnet, and Gemini 2.0 Flash.

A memory architecture representing stored information as continuous fields governed by partial differential equations. Demonstrates 116% improvement on multi-session reasoning and 43.8% gains on temporal reasoning benchmarks, with multi-agent configurations achieving near-perfect collective performance through field coupling.

This work addresses a key challenge in multi-tiered anomaly detection systems: balancing the operational cost of accurate analytical models with the accuracy of less expensive rule engines.

This work addresses the tension between computational accuracy and operational speed in real-time risk systems. It proposes a multi-tier risk decisioning system managed by a predictive, cost-benefit routing engine.

Framework combining formal verification, program synthesis, and machine learning to automatically generate verified distributed system implementations. Achieves 274x speedup with 60% latency reduction.

Introduces ETLC (Extract, Transform, Load, Contextualize), adding semantic, relational, operational, environmental, and behavioral context to data pipelines for GenAI systems.

An innovative approach modeling context as interacting fields rather than discrete states, enabling natural context flow and dynamic evolution through partial differential equations.

An AI framework supporting complex debate scenarios and group decision-making through a tiered structure of language models that dynamically generate and evaluate arguments.

A comprehensive framework for enterprises to transform data assets into economic value, establishing methodologies for Data Monetization through a structured 12-month approach.

A privacy-aware open protocol to prove without repudiation an entity's point-in-time presence, participation and location in physical or virtual space.

A protocol and platform based on Blockchain Technology that enables transparent processing of personal data throughout its lifecycle from capture, lineage to redaction.

A novel Cascading Algorithm leveraging Bayesian inference to facilitate arbitrage-free pricing of financial options through continuously refined price estimates.

Coupled Temporal Deep Belief Networks with Conditional Restricted Boltzmann Machines to encode intra-market movements and temporary coupling with global indices.

On the fly creation and calculation of Max-flow min-cut gap and approximation of multicuts with deep emulations of a fault-free mesh on a mesh with random faults.

Algorithms for automatic on-the-fly wrapper creation for extractions from HTML and XML documents and compressing the adjacency list representation of graphs.

A discrete time-step optimization algorithm based on limited parameters of the sensor-target systems with OpenCV-based implementation.

Wireless power transfer via resonant magnetic coupling, demonstrating power transfer efficiencies of 67% at a distance of 30 cm with applications to consumer electronics and medical implants.