Ashish Zombade
Vizra Industries Founder
Oxford, United Kingdom
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Vizra Industries is an Uk based company and Ashish Zombade being founder , The company focuses on customer and automation and helps corporated gain 10x results in their Business, also Ashish being Ai Researcher from Oxford has delivered and researched on the papers on automation and cyber security and concept not known by society,
The following Papers include
Published book Ecointelligence: When Artificial Intelligence Converges with Sustainability
● UK-Smart-Office-Helper Developed an AI assistant using OpenAI API to structure user data, generate insights, and manage
interaction logs within a cloud-based workflow.
● Encrypted Neural Network Training via Functional Encryption Primitives
Developed privacy-preserving predictive models using advanced encryption techniques, balancing data security with model
accuracy and analytical performance.
● Temporal Key-State Stream Processing for Real-Time Anomaly Detection
Designed real-time data stream processing framework to detect anomalies, applying machine learning and time-series analytics
for performance monitoring.
● Communication-Frugal Federated Training for Deep Neural Networks
Optimized distributed model training by reducing communication overhead, improving scalability and efficiency across large
datasets.
● Byzantine-Resilient Gradient Aggregation for Distributed Non-Convex Optimization
Engineered robust gradient aggregation methods to ensure reliable model optimization in distributed analytics environments.
● Kernel-Native Packet Steering and Network Function Virtualization for Pod-Level Traffic Engineering in Distributed
Container Clusters
Implemented performance optimization techniques for distributed systems, enhancing traffic efficiency and data flow
management at scale.
● Automated Scalable Visualization Framework for Reproducible Environmental Data Science
Built automated data visualization framework to transform complex datasets into scalable, reproducible dashboards supporting
data-driven decision-making.
-Perception of Fairness in Recommender Systems – Generated actionable insights to optimize personalization
strategies and engagement.
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