I am an Assistant Professor at Rochester Institute of Technology.
The overarching theme of my research is engineering mobile and social applications. I develop computational abstractions and techniques to enable mobile social applications to deliver a personalized, context-aware, and privacy-preserving experience. My research offers benefits to both application devlopers and end-users.
I defended my PhD in Computer Science at North Carolina State University under the guidance of Professor Munindar P. Singh. I was a Research Scientist at RIT, funded by the Dean's Postdoctoral Fellowship, working with Professor Naveen Sharma.
I envision mobile social applications as personal agents that can act and interact on their users behalf. Engineering a personal agent is a two-fold challenge. On the one hand, we must understand how humans act and interact—a challenge centered on understanding cognition. On the other hand, we must develop automated techniques to facilitate personal agents to operate on their users' behalf—a challenge centered on understanding data.
Abstractions: I develop (1) high-level abstractions to represent user- and context-specific requirements, (2) techniques to learn those abstractions from data, and (3) methods to incorporate those abstractions in the development of personal agents.
Data-driven methods: I collect data for my research from a variety of sources including social media, software repositories, crowdsourcing, and crowdsensing. I have conducted multiple user studies, demonstrating benefits of my methods to both application developers and end-users.
Privacy: My works emphasize preserving users' privacy. I develop techniques to (1) reason about a user's personal data and (2) facilitate users to share personal data (e.g., on social media) in a privacy-preserving manner.
Read more about my research thrusts below.
|Sharing policies in multiuser privacy scenarios: Incorporating context, preferences, and arguments in decision making.
R Fogues, PK Murukannaiah, J Such, and MP Singh. ACM Transactions on Computer-Human Interaction, To appear, 1–26, 2017.
|Platys: An active learning framework for place-aware application development and its evaluation.
PK Murukannaiah and MP Singh. ACM Transactions on Software Engineering and Methodology, 24(3):1–33, 2015.
|Platys: From position to place-oriented mobile computing.
L Zavala, PK Murukannaiah, N Poosamani, T Finin, A Joshi, I Rhee, and MP Singh. AI Magazine, 36(2):50–62, 2015.
|AI Magazine 2015||1.05|
|Platys Social: Relating shared places and private social circles.
PK Murukannaiah and MP Singh. IEEE Internet Computing, 16(3):53–59, 2012.
|Engineering privacy in social applications.
PK Murukannaiah, N Ajmeri, and MP Singh. IEEE Internet Computing, 20(2):72–76, 2016.
|Understanding location-based user experience. PK Murukannaiah and MP Singh. IEEE Internet Computing, 18(6):53–59, 2014.||IC 2014||2.47|
|Canary: Extracting Requirements-Related Information from Online Discussions.
G Kanchev, PK Murukannaiah, AK Chopra, and P Sawyer.
In Proceedings of the IEEE 25th International Requirements Engineering Conference, 1–10, Lisbon, 2017.
|RE 2017||35.5% [27/76]|
|Arnor: Modeling social intelligence via norms to engineer privacy-aware personal agents.
N Ajmeri, PK Murukannaiah, H Gao, and MP Singh.
In Proceedings of the 16th International Conference on Autonomous Agents and MultiAgent Systems, 1–9, São Paulo, Brazil, 2017.
|AAMAS 2017||26.1% [155/595]|
|Acquiring creative requirements from the crowd: Understanding the influences of personality and creative potential in crowd RE.
PK Murukannaiah, N Ajmeri, and MP Singh.
In Proceedings of the IEEE 24th International Requirements Engineering Conference, 176–185, Beijing, 2016.
|RE 2016||27.8% [22/79]|
|Percimo: A personalized community model for location estimation in social media. G Yuan, PK Murukannaiah, and MP Singh.
In Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 271–278, San Francisco, 2016.
|ASONAM 2016||13.6% [43/316]|
|Resolving goal conflicts via argumentation-based analysis of competing hypotheses. PK Murukannaiah, AK Kalia, PR Telang, and MP Singh. In Proceedings of the IEEE 23rd International Requirements Engineering Conference, 156–165, Ottawa, 2015.||RE 2015||19.8% [19/96]|
|TRACE: A dynamic model of trust for people-driven service engagements. AK Kalia, PK Murukannaiah, and MP Singh.
In Proceedings of the 13th International Conference on Service-Oriented Computing, 353–361, Goa, 2015.
|ICSOC 2015||24.2% [27/112]|
|Xipho: Extending Tropos to engineer context-aware personal agents. PK Murukannaiah and MP Singh.
In Proceedings of the International Conference on Autonomous Agents and MultiAgent Systems, 309–316, Paris, 2015.
|AAMAS 2014||23.8% [169/709]|
|Exploiting sentiment homophily for link prediction. G Yuan, PK Murukannaiah, Z Zhang, and MP Singh.
In Proceedings of the ACM Conference on Recommender Systems, 17–24, Foster City CA, 2014.
|RecSys 2014||14.9% [35/234]|
|Structure discovery queries in disk-based Semantic Web databases. K Anyanwu, PK Murukannaiah, and A Maduko.
In Proceedings of the IEEE International Conference on Semantics, Knowledge, and Grid, 336–342, Beijing, 2008.
|PrIncipedia: A privacy incidents encyclopedia.PK Murukannaiah, J Staddon, H Lipford, and B knijnenburg.
The 9th Annual Privacy Law Scholars Conference, 2016.
|Dimensionality reduction. MR Marri, L Ramachandran, PK Murukannaiah, P Ravindra, A Paul, D Young, DF Lee, S Murugappan, W Hendrix.
In NF Samatova, W Hendrix, J Jenkins, K Padmanabhan, A Chakraborty (Eds.), Practical Graph Mining with R, CRC Press, 2013.
|Graph Mining 2013|
|Toward Automating Crowd RE. PK Murukannaiah, N Ajmeri, and MP Singh.
In Proceedings of the IEEE 25th International Requirements Engineering Conference (Data Track), 1–4, Lisobon. 2017.
|A Domain-Independent Model for Identifying Security Requirements. N Munaiah, A Meneely, and PK Murukannaiah.
In Proceedings of the IEEE 25th International Requirements Engineering Conference (Data Track), 1–6, Lisobon. 2017.
|Canary: An Interactive and Query-Based Approach to Extract Requirements from Online Forums. G Kanchev, PK Murukannaiah, AK Chopra, and P Sawyer.
In Proceedings of the IEEE 25th International Requirements Engineering Conference (Demonstration), 1–4, Lisobon. 2017.
|Learning a privacy incidents database. PK Murukannaiah, C Dabral, K Sheshadri, E Sharma, and J Staddon.
In Proceedings of the Symposium and Bootcamp on Hot Topics in Science of Security, 1–10, Hanover, MD. 2017.
|(Work in Progress) Is this a privacy incident? Using news exemplars to study end user perceptions of privacy incidents.
PK Murukannaiah, J Staddon, H Lipford, and B knijnenburg. In Proceedings of the Workshop on Usable Security, 1–7, San Diego, 2017.
|Argumentation for multi-party privacy management (Position paper). R Fogues, PK Murukannaiah, JM Such, A Espinosa, A Garcia-Fornes, and MP Singh. International Workshop on Agents and CyberSecurity, 2015.||ACySe 2015|
|Reasoning about context and engineering context-aware agents (Doctoral Consortium). PK Murukannaiah.
In Proceedings of the International Conference on Autonomous Agents and MultiAgent Systems, 1733–1734, 2014
|Platys: A framework for supporting context-aware personal agents (Demonstration). PK Murukannaiah, R Fogues, and MP Singh.
In Proceedings of the International Conference on Autonomous Agents and MultiAgent Systems, 1689–1690, 2014.
|Platys: User-Centric Place Recognition. C-W Hang, PK Murukannaiah, and MP Singh.
AAAI Workshop on Activity Context-Aware System Architectures, 2013
|AAAI WS 2013|
|Engineering personal agents: Toward personalized, context-aware, and privacy-preserving applications.
PK Murukannaiah. North Carolina State University, 2016.
Keywords: Crowd-based RE, creativity, human factors, team work, goal modeling, argumentation, RE at runtime
Keywords: Agents, modeling, context-awareness, middleware, machine learning, sensors, Internet of things
Keywords: Multiagent systems, social media analysis, geo-social, social norms, argumentation
Keywords: Multiuser privacy, usable privacy, privacy incidents, social norms, personal data