Identifying andTesting for Insecure Paths in Cryptographic Protocol Implementations. - K. R. Jayaram (COMPSAC (2), 2006)

On the Adequacy of Statecharts as a Source of Tests for Cryptographic Protocols. - K. R. Jayaram; Aditya P. Mathur (COMPSAC, 2008)

Lazy argument passing in Java RMI. - Christopher Line; K. R. Jayaram; Patrick Eugster (PPPJ, 2008)

EventJava: An Extension of Java for Event Correlation. - Patrick Th. Eugster; K. R. Jayaram (ECOOP, 2009)

Context-oriented programming with EventJava. - K. R. Jayaram; Patrick Eugster (COP@ECOOP, 2009)

Scalable Efficient Composite Event Detection. - K. R. Jayaram; Patrick Th. Eugster (COORDINATION, 2010)

Parametric Subscriptions for Content-Based Publish/Subscribe Networks. - K. R. Jayaram; Chamikara Jayalath; Patrick Eugster (Middleware, 2010)

Putting events in context: aspects for event-based distributed programming. - Adrian Holzer; Lukasz Ziarek; K. R. Jayaram; Patrick Eugster (AOSD, 2011)

Program analysis for event-based distributed systems. - K. R. Jayaram; Patrick Eugster (DEBS, 2011)

Split and Subsume: Subscription Normalization for Effective Content-Based Messaging. - K. R. Jayaram; Patrick Eugster (ICDCS, 2011)

FAIDECS: Fair Decentralized Event Correlation. - Gregory Aaron Wilkin; K. R. Jayaram; Patrick Eugster; Ankur Khetrapal (Middleware, 2011)

Brief Announcement: Weighted Partial Message Matching for Implicit Multicast Systems. - William Culhane; K. R. Jayaram; Patrick Eugster (DISC, 2012)

Abstracting Context in Event-Based Software. - Adrian Holzer; Lukasz Ziarek; K. R. Jayaram; Patrick Eugster (LNCS Trans. Aspect Oriented Softw. Dev., 2012)

Elastic Remote Methods. - K. R. Jayaram (Middleware, 2013)

Views and Transactional Storage for Large Graphs. - Michael Mihn-Jong Lee; Indrajit Roy 001; Alvin AuYoung; Vanish Talwar; K. R. Jayaram; Yuanyuan Zhou 001 (Middleware, 2013)

Parametric Content-Based Publish/Subscribe. - K. R. Jayaram; Patrick Eugster; Chamikara Jayalath (ACM Trans. Comput. Syst., 2013)

Fast, expressive top-k matching. - William Culhane; K. R. Jayaram; Patrick Eugster (Middleware, 2014)

Trustworthy geographically fenced hybrid clouds. - K. R. Jayaram; David Safford; Upendra Sharma; Vijay K. Naik; Dimitrios E. Pendarakis; Shu Tao (Middleware, 2014)

Decentralized Fault-Tolerant Event Correlation. - Gregory Aaron Wilkin; Patrick Eugster; K. R. Jayaram (ACM Trans. Internet Techn., 2014)

Towards Explicitly Elastic Programming Frameworks. - K. R. Jayaram (ICSE (2), 2015)

Subscription Normalization for Effective Content-Based Messaging. - K. R. Jayaram; Weihang Wang 001; Patrick Eugster (IEEE Trans. Parallel Distributed Syst., 2015)

Exploiting Causality to Engineer Elastic Distributed Software. - K. R. Jayaram (ICDCS, 2016)

Quantifying the Attack Detection Accuracy of Intrusion Detection Systems in Virtualized Environments. - Aleksandar Milenkoski; K. R. Jayaram; Nuno Antunes; Marco Vieira; Samuel Kounev (ISSRE, 2016)

Software Architectures for Self-protection in IaaS Clouds. - K. R. Jayaram; Aleksandar Milenkoski; Samuel Kounev (Self-Aware Computing Systems, 2017)

Benchmarking Intrusion Detection Systems with Adaptive Provisioning of Virtualized Resources. - Aleksandar Milenkoski; K. R. Jayaram; Samuel Kounev (Self-Aware Computing Systems, 2017)

Scalable, Efficient Anonymization with INCOGNITO - Framework & Algorithm. - Antorweep Chakravorty; Chunming Rong; K. R. Jayaram; Shu Tao (BigData Congress, 2017)

Agile Composition of Compliant Data Analytics Platforms. - Michael Le; K. R. Jayaram; Yaron Weinsberg; Daniel J. Dean; Shu Tao (IC2E, 2017)

IBM Deep Learning Service. - Bishwaranjan Bhattacharjee; Scott Boag; Chandani Doshi; Parijat Dube; Ben Herta; Vatche Ishakian; K. R. Jayaram; Rania Khalaf; Avesh Krishna; Yu Bo Li; Vinod Muthusamy; Ruchir Puri; et al. (CoRR, 2017)

IBM Deep Learning Service. - Bishwaranjan Bhattacharjee; Scott Boag; Chandani Doshi; Parijat Dube; Ben Herta; Vatche Ishakian; K. R. Jayaram; Rania Khalaf; Avesh Krishna; Yu Bo Li; Vinod Muthusamy; Ruchir Puri; et al. (IBM J. Res. Dev., 2017)

Dependability in a Multi-tenant Multi-framework Deep Learning as-a-Service Platform. - Scott Boag; Parijat Dube; Kaoutar El Maghraoui; Benjamin Herta; Waldemar Hummer; K. R. Jayaram; Rania Khalaf; Vinod Muthusamy; Michael H. Kalantar; Archit Verma (DSN Workshops, 2018)

Adaptively Accelerating Map-Reduce/Spark with GPUs: A Case Study. - K. R. Jayaram; Anshul Gandhi; Hongyi Xin; Shu Tao (ICAC, 2019)

FfDL: A Flexible Multi-tenant Deep Learning Platform. - K. R. Jayaram; Vinod Muthusamy; Parijat Dube; Vatche Ishakian; Chen Wang 039; Benjamin Herta; Scott Boag; Diana Arroyo; Asser N. Tantawi; Archit Verma; Falk Pollok; Rania Khalaf (Middleware, 2019)

MYSTIKO: Cloud-Mediated, Private, Federated Gradient Descent. - K. R. Jayaram; Archit Verma; Ashish Verma 001; Gegi Thomas; Colin Sutcher-Shepard (CLOUD, 2020)

Workshop 19: ScaDL Scalable Deep Learning over Parallel and Distributed Infrastructures. - Ashish Verma 001; Christopher D. Carothers; K. R. Jayaram; Parijat Dube (IPDPS Workshops, 2020)

Effective Elastic Scaling of Deep Learning Workloads. - Vaibhav Saxena; K. R. Jayaram; Saurav Basu; Yogish Sabharwal; Ashish Verma 001 (MASCOTS, 2020)

Separation of Powers in Federated Learning (Poster Paper). - Pau-Chen Cheng; Kevin Eykholt; Zhongshu Gu; Hani Jamjoom; K. R. Jayaram; Enriquillo Valdez; Ashish Verma 001 (ResilientFL, 2021)

Separation of Powers in Federated Learning. - Pau-Chen Cheng; Kevin Eykholt; Zhongshu Gu; Hani Jamjoom; K. R. Jayaram; Enriquillo Valdez; Ashish Verma 001 (CoRR, 2021)

Private Parameter Aggregation for Federated Learning. - K. R. Jayaram; Ashish Verma 001 (Federated Learning, 2022)

Adaptive Aggregation For Federated Learning. - K. R. Jayaram; Vinod Muthusamy; Gegi Thomas; Ashish Verma 001; Mark Purcell (IEEE Big Data, 2022)

Just-in-Time Aggregation for Federated Learning. - K. R. Jayaram; Ashish Verma 001; Gegi Thomas; Vinod Muthusamy (MASCOTS, 2022)

FLIPS: Federated Learning using Intelligent Participant Selection. - Rahul Atul Bhope; K. R. Jayaram; Nalini Venkatasubramanian; Ashish Verma 001; Gegi Thomas (Middleware, 2023)

On Serving Image Classification Models. - Aurora González-Vidal; Alexander Isenko; K. R. Jayaram (WOSC@Middleware, 2023)

DeTA: Minimizing Data Leaks in Federated Learning via Decentralized and Trustworthy Aggregation. - Pau-Chen Cheng; Kevin Eykholt; Zhongshu Gu; Hani Jamjoom; K. R. Jayaram; Enriquillo Valdez; Ashish Verma 001 (EuroSys, 2024)

A Conversational Assistant Framework for Automation. - Evelyn Duesterwald; Vatche Isahagian; K. R. Jayaram; Ritesh Kumar; Vinod Muthusamy; Punleuk Oum; Gegi Thomas; Praveen Venkateswaran (Middleware Industry, 2024)

On Automating Security Policies with Contemporary LLMs (Short Paper). - Pablo Fernández Saura; K. R. Jayaram; Vatche Isahagian; Jorge Bernal Bernabé; Antonio F. Skarmeta (SSE, 2025)

OptiSeq: Optimizing Example Ordering for In-Context Learning. - Rahul Atul Bhope; Praveen Venkateswaran; K. R. Jayaram; Vatche Isahagian; Vinod Muthusamy; Nalini Venkatasubramanian (CoRR, 2025)

FLOW-BENCH: Towards Conversational Generation of Enterprise Workflows. - Evelyn Duesterwald; Siyu Huo; Vatche Isahagian; K. R. Jayaram; Ritesh Kumar; Vinod Muthusamy; Punleuk Oum; Debashish Saha; Gegi Thomas; Praveen Venkateswaran (CoRR, 2025)

Performance of Confidential Computing GPUs. - Antonio Martínez Ibarra; Julian James Stephen; Aurora González-Vidal; K. R. Jayaram; Antonio Fernandez Gómez-Skarmeta (CoRR, 2025)

On Automating Security Policies with Contemporary LLMs. - Pablo Fernández Saura; K. R. Jayaram; Vatche Isahagian; Jorge Bernal Bernabé; Antonio F. Skarmeta (CoRR, 2025)

Shift Happens: Mixture of Experts based Continual Adaptation in Federated Learning. - Rahul Atul Bhope; K. R. Jayaram; Praveen Venkateswaran; Nalini Venkatasubramanian (CoRR, 2025)