Patents
Inventions filed at IBM, and one earlier one from HP Labs, grouped by invention rather than by filing — one entry may have issued in several jurisdictions. Filed under my full legal name, Jayaram Kallapalayam Radhakrishnan.
12 granted inventions (20 issued patents across jurisdictions), 8 pending applications. Years shown are the disclosure year. Where a PDF link is shown, it points to the full document on USPTO. Grants without one had no public PDF that could be verified.
Named an IBM Master Inventor in 2026.
Granted
- Federated Learning with Partitioned and Dynamically-Shuffled Model Updates CN ZL202210537839.3·JP 7740842
- Trusted and Decentralized Aggregation for Federated Learning US 12541708 PDF·CN ZL202280032564.6·JP 7841826
- Data Subset Selection for Federated Learning US 12632795
- Secure Federation of Distributed Stochastic Gradient Descent CN ZL202080079660.7·GB 2606867·JP 7513359
- Hyperparameter Determination for a Differentially Private Federated Learning Process US 11941520 PDF
- Application Aware Resource Allocation for Deep Learning Job Scheduling US 11586475 PDF
- Determining Optimal Compute Resources for Distributed Batch Based Optimization Applications US 11263052 PDF·CN ZL202010724291.4
- Scalable Multi-Framework Multi-Tenant Lifecycle Management of Deep Learning Applications US 11269728 PDF·US 11196547 PDF
- Graphics Processing Unit Resource Sharing US 9830677 PDF·US 9830678 PDF
- Application Deployment and Monitoring in a Cloud Environment to Satisfy Integrity and Geo-Fencing Constraints US 10228924 PDF
- Selecting from Computing Nodes for Correlating Events US 10419457 PDF
- Virtual Machine Image Access De-Duplication US 8897573 PDF
Pending applications
- Extracting and Generalizing Subtask-Level Knowledge for Autonomous Agents
- Trajectory-Based Memory Generation and Contextual Retrieval
- Storage and Memory Management for Multimodal AI Systems
- Deployment-Aware Memory Packaging for Artificial Intelligence Agents
- Conversational Workflow Building using Large Language Models
- In-Context Example Ordering for Large Language Models
- Using Secure and Reliable Benefit-Analysis Matchmaking to Select Federated Learning Candidates
- Grouped Aggregation in Federated Learning
Other disclosures
- Purpose-Directed Gisting for Agentic Memoryfiled
- Federated Learning Participant Selection through Label Distribution Clusteringfiled
- Method and System for In-Field Malfunctioning Detection of AI Systemsfiled
- Serverless Federated Learning: Unifying Cross-Device and Cross-Silo Learningdefensive publication