Demo Data from EDBT 2026 / reviewers in the wild / expert
Keshav Agarwal
dblp:346/8062
· DBLP profile ↗
3ranked-venue papers
0as first author
3since 2021 · last 2025
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
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.
| Artificial intelligence
1 paper |
Planning, search and constraint satisfaction · 100% | |
| Theoretical computer science
1 paper |
Distributed computing theory · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
scheduling |
0.8 | 1 | 2024 | Linear-Time Optimal Deadlock Detection for Efficient Scheduling in Multi-Track Railway Networks · IJCAI 2024 |
Distributed computing theory › predicate detection › stable property detection
deadlock detection |
0.8 | 1 | 2024 | Linear-Time Optimal Deadlock Detection for Efficient Scheduling in Multi-Track Railway Networks · IJCAI 2024 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Kinship in Speech: Leveraging Linguistic Relatedness for Zero-Shot TTS in Indian Languages
Utkarsh Pathak, Chandra Sai Krishna Gunda, Anusha Prakash 0001, Keshav Agarwal, Hema A. Murthy |
INTERSPEECH | 4 |
| 2024 | Linear-Time Optimal Deadlock Detection for Efficient Scheduling in Multi-Track Railway Networks
Hastyn Doshi, Ayush Tripathi, Keshav Agarwal, Harshad Khadilkar, Shivaram Kalyanakrishnan |
IJCAI | 3 |
| 2023 | t-PIR Schemes with Flexible Parameters via Star Products of Berman CodesabstractWe present a new class of private information retrieval (PIR) schemes that keep the identity of the file requested private in the presence of at most t colluding servers, based on the recent framework developed for such t-PIR schemes using star products of transitive codes. These t-PIR schemes employ the class of Berman codes as the storage-retrieval code pairs. Berman codes, which are binary linear codes of length nmfor any n ≥ 2 and m ≥ 1 being positive integers, were recently shown to achieve the capacity of the binary erasure channel. We provide a complete characterization of the star products of the Berman code pairs, enabling us to calculate the PIR rate of the star product-based schemes that employ these codes. The schemes we present have flexibility in the number of servers, the PIR rate, the storage rate, and the collusion parameter t, owing to numerous codes available in the class of Berman codes.Due to space restrictions, the full version of this paper containing proofs of claims, additional examples, and results, is made available in [1]. Srikar Kale, Keshav Agarwal, Prasad Krishnan |
ISIT | 2 |