Demo Data from EDBT 2026 / reviewers in the wild / expert
Parthasarathi Panda
dblp:180/5661
· DBLP profile ↗
3ranked-venue papers
1as first author
1since 2021 · last 2026
0000-0003-0071-708XORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Security and privacy · 1Databases, data management, data science and information retrieval · 1 · 1 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Privacy and data protection · 100% | |
| Computer networks
1 paper |
Content delivery and video streaming · 100% | |
| Theoretical computer science
1 paper |
Information theory · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Content delivery and video streaming › caching
coded caching |
0.3 | 1 | 2018 | Private Coded Caching · IEEE Trans. Inf. Forensics Secur. 2018 |
Privacy and data protection › web privacy
cache privacy |
0.3 | 1 | 2018 | Private Coded Caching · IEEE Trans. Inf. Forensics Secur. 2018 |
Privacy and data protection › privacy metrics › privacy quantification
information-theoretic privacy |
0.3 | 1 | 2018 | Private Coded Caching · IEEE Trans. Inf. Forensics Secur. 2018 |
Information theory › information-theoretic limits
information-theoretic lower bounds |
0.1 | 1 | 2018 | Private Coded Caching · IEEE Trans. Inf. Forensics Secur. 2018 |
Methods — techniques the papers use, named apart from their topics
information-theoretic bounds · 1.0coded caching · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | CRAFT: Clustered Regression for Adaptive Filtering of Training Data
Parthasarathi Panda, Asheswari Swain, Subhrakanta Panda |
DATA (1) | 1 |
| 2018 | Private Coded CachingabstractRecent work by Maddah-Ali and Niesen (2014) introduced coded caching which demonstrated the benefits of joint design of storage and transmission policies in content delivery networks. They studied a setup where a server communicates with a set of users, each equipped with a local cache, over a shared error-free link and proposed an order-optimal caching and delivery scheme. In this paper, we introduce the problem of private coded caching where we impose the additional constraint that no user learns any information about the contents of the files it did not request from what is stored in its cache and the server transmissions. We propose a feasible scheme for this setting and demonstrate its order-optimality by deriving information-theoretic lower bounds. Vaishakh Ravindrakumar, Parthasarathi Panda, Nikhil Karamchandani, Vinod M. Prabhakaran |
IEEE Trans. Inf. Forensics Secur. | 2 |
| 2016 | Fundamental limits of secretive coded cachingabstractRecent work by Maddah-Ali and Niesen introduced coded caching which demonstrated the benefits of joint design of storage and transmission policies in content delivery networks. They studied a setup where a server communicates with a set of users, each equipped with a local cache, over a shared error-free link and proposed an order-optimal caching and delivery scheme. In this paper, we introduce the problem of secretive coded caching where we impose the additional constraint that a user should not be able to learn anything, from either the content stored in its cache or the server transmissions, about a file it did not request. We propose a feasible scheme for this setting and demonstrate its order-optimality with respect to information-theoretic lower bounds. Vaishakh Ravindrakumar, Parthasarathi Panda, Nikhil Karamchandani, Vinod M. Prabhakaran |
ISIT | 2 |