Publications & Research | Reshma Thakkallapelly

Publications, Research & Industry Contributions

Technology leadership extends beyond building systems—it also involves sharing knowledge, contributing to industry conversations, and advancing research that helps shape the future.

Over the years, I have contributed to research, industry discussions, conference presentations, and thought leadership initiatives focused on healthcare technology, artificial intelligence, cloud architecture, enterprise systems, and digital transformation.

My work explores how modern technology platforms can improve healthcare accessibility, support intelligent decision-making, and create more connected digital ecosystems.

Reshma’s scholarly and technical work spans explainable AI, neuro-symbolic reasoning, autonomous agents, graph neural networks, reinforcement learning, IoT routing, and real-time decision systems. Her publications connect advanced AI methods with practical architecture themes that recur in her enterprise work: decision transparency, reliability, scalability, observability, and responsible automation.

Research Publications

Neuro-Symbolic AI for Context-Aware Decision Making in Real-Time Systems

This research explores the integration of symbolic reasoning and machine learning techniques to improve decision-making in dynamic, real-time environments. The work focuses on combining the interpretability of symbolic systems with the adaptability of modern AI models, enabling more context-aware and transparent intelligent systems. The research has applications across healthcare, enterprise automation, and complex decision-support environments.

IEEE Conference Publication

Research contributions published through IEEE explore emerging technologies, enterprise-scale systems, intelligent automation, and modern computing architectures. These publications reflect ongoing efforts to bridge academic research with real-world technology challenges and industry implementation.

Conference Speaking

SCIS 2025 – 24/7 Pharmacy at Your Fingertips

As a speaker at SCIS 2025, I shared insights into digital pharmacy transformation and the architecture behind modern healthcare delivery platforms.

The session explored how cloud-native systems, healthcare interoperability, API ecosystems, and digital pharmacy technologies are helping healthcare organizations deliver more accessible, reliable, and patient-centric services at scale.

Featured Industry Article

Architecting the Next Wave of Digital Healthcare

This feature explores my perspective on healthcare technology modernization, digital pharmacy infrastructure, cloud-native architecture, interoperability, and the role of intelligent systems in improving healthcare experiences.

The article highlights the importance of resilient platforms, observability, interoperability standards, and architectural thinking as healthcare organizations continue their digital transformation journeys.

Graph Neural Network-Based Routing Optimization in Large-Scale IoT Deployments

ICAICCIT 2025 / IEEE; DOI:10.1109/ICAICCIT68829. 2025.11434239

Applies graph neural networks to large-scale IoT routing optimization, emphasizing adaptive routing, latency reduction, energy efficiency, and embedded deployment.

Explainability- Driven Autonomous AI Agents for Multi- Domain Applications

ACOIT 2025 / IEEE; DOI: 10.1109/ACOIT66109.2025.11436949

Focuses on explainability- driven autonomous agents across multiple domains, relevant to governed AI, human-in-the-loop workflows, and auditable decision systems.

Neuro Symbolic AI for Context-Aware Decision Making in Real-Time Systems

I3CTCON 2026 / IEEE; DOI: 10.1109/I3CTCON68242.2026.11507136

Explores neuro-symbolic AI for real-time, context- aware decision-making, aligning with transparent and explainable intelligent systems.

Deep Reinforcement Policy for Coordinating Cooperative Autonomous Vehicles at Highway Intersection Merges

ICEEI 2025 / IEEE

Shows work in reinforcement learning, multi-agent coordination, real-time decisioning, and safety-aware policy execution. Public web mentions list Reshma among the authors.

German Utility Model / Published Utility Model: Explainable Automated Pre- Approval Decisions in a Payer-Owned Digital Pharmacy Benefits Platform

DE202026100957U1 / 2026

Public listing describes a computerized system for explainable automated pre- approval decisions in a payer-owned digital pharmacy benefits platform. Use careful wording: “published German utility model / utility-model filing,” not “examined patent grant.”

Research, Publications & Industry Contributions

Explore Reshma’s published research, academic citations, and contributions to healthcare technology, cloud architecture, enterprise systems, and emerging technologies.

Testimonials

“Reshma’s work represents a meaningful advancement in modern PBM architecture, combining digital pharmacy, explainable prior authorization, audit-ready workflows, and governed automation at national scale.”

“Reshma is an elite technology architect who turns complex healthcare requirements into resilient, cloud-native platforms where reliability, interoperability, compliance, and security are built in.”

“Reshma was trusted with infrastructure supporting thousands of distributed locations under live commercial conditions, contributing directly to enterprise modernization at national scale.”