Demo Data from EDBT 2026 / reviewers in the wild / expert
Dominick Banasik
dblp:407/4542
· DBLP profile ↗
3ranked-venue papers
3as first author
3since 2021 · last 2026
0009-0002-1414-7268ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2 · 2 first-author · 2 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.
| Theoretical computer science
2 papers |
Distributed computing theory · 100% | |
| Computer networks
1 paper |
Wireless networking · 50% Internet of things and sensor networks · 50% |
Topics — the 7 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Distributed computing theory › distributed complexity
energy complexity |
1.9 | 2 | 2026 | Brief Announcement: On Energy Complexity and Multi-Instance Computation in the Congested Clique · PODC 2026 Brief Announcement: Energy-Efficient Maximal Independent Sets in Radio Networks · PODC 2025 |
Distributed computing theory
distributed algorithms |
1.0 | 1 | 2026 | Brief Announcement: On Energy Complexity and Multi-Instance Computation in the Congested Clique · PODC 2026 |
Distributed computing theory
distributed graph algorithms |
0.9 | 1 | 2025 | Brief Announcement: Energy-Efficient Maximal Independent Sets in Radio Networks · PODC 2025 |
Distributed computing theory › distributed graph algorithms
maximal independent set |
0.9 | 1 | 2025 | Brief Announcement: Energy-Efficient Maximal Independent Sets in Radio Networks · PODC 2025 |
Distributed computing theory › distributed graph algorithms
congested clique |
0.3 | 1 | 2026 | Brief Announcement: On Energy Complexity and Multi-Instance Computation in the Congested Clique · PODC 2026 |
Wireless networking
radio networks |
0.3 | 1 | 2025 | Brief Announcement: Energy-Efficient Maximal Independent Sets in Radio Networks · PODC 2025 |
Internet of things and sensor networks
wireless sensor network |
0.3 | 1 | 2025 | Brief Announcement: Energy-Efficient Maximal Independent Sets in Radio Networks · PODC 2025 |
Methods — techniques the papers use, named apart from their topics
distributed algorithm · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Brief Announcement: On Energy Complexity and Multi-Instance Computation in the Congested Clique
Dominick Banasik, Varsha Dani |
PODC | 1 |
| 2025 | Brief Announcement: Energy-Efficient Maximal Independent Sets in Radio NetworksabstractMaximal Independent Set (MIS) is one of the most fundamental problems in distributed computing, and it has been studied intensively for over four decades. This paper focuses on the MIS problem in the radio networks model, a standard model widely used to model wireless networks, particularly ad hoc wireless and sensor networks. Energy is a premium resource in these networks, which are typically battery-powered. Hence, designing distributed algorithms that use as little energy as possible is crucial. We use the well-established energy model where a node can be sleeping or awake in a round, and only the awake rounds (when it can send or listen) determine the energy complexity of the algorithm. Dominick Banasik, Varsha Dani, Fabien Dufoulon, Thomas P. Hayes, Gopal Pandurangan |
PODC | 1 |
| 2025 | Energy-Efficient Maximal Independent Sets in Radio NetworksabstractThe maximal independent set (MIS) is one of the most fundamental problems in distributed computing, and it has been studied intensively for over four decades. This paper focuses on the MIS problem in the Radio Network model, a standard model widely used to model wireless networks, particularly ad hoc wireless and sensor networks. Energy is a premium resource in these networks, which are typically battery-powered. Hence, designing distributed algorithms that use as little energy as possible is crucial. We use the well-established energy model where a node can be sleeping or awake in a round, and only the awake rounds (when it can send or listen) determine the energy complexity of the algorithm, which we want to minimize. We present new, more energy-efficient MIS algorithms in radio networks with arbitrary and unknown graph topology. We present algorithms for two popular variants of the radio model -- with collision detection (CD) and without collision detection (no-CD). Specifically, we obtain the following results: 1. CD model: We present a randomized distributed MIS algorithm with energy complexity $O(\log n)$, round complexity $O(\log^2 n)$, and failure probability $1 / poly(n)$, where $n$ is the network size. We show that our energy complexity is optimal by showing a matching $Ω(\log n)$ lower bound. 2. no-CD model: In the more challenging no-CD model, we present a randomized distributed MIS algorithm with energy complexity $O(\log^2n \log \log n)$, round complexity $O(\log^3 n \log Δ)$, and failure probability $1 / poly(n)$. The energy complexity of our algorithm is significantly lower than the round (and energy) complexity of $O(\log^3 n)$ of the best known distributed MIS algorithm of Davies [PODC 2023] for arbitrary graph topology. Dominick Banasik, Varsha Dani, Fabien Dufoulon, Thomas P. Hayes, Gopal Pandurangan |
DISC | 1 |