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Matin Amini

dblp:390/7379 · DBLP profile ↗
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3ranked-venue papers
0as first author
3since 2021 · last 2025
0009-0006-8776-3925ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2 · 2 since 2021Security and privacy · 1 · 1 since 2021Theory of computation · 1 · 1 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.

Theoretical computer science
1 paper
Automata and formal languages · 50% Computational complexity · 50%
Artificial intelligence
1 paper
Image recognition and object detection · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational complexity › decision problems
membership problem
0.912025
Membership Testing for Semantic Regular Expressions · Proc. ACM Program. Lang. 2025
Automata and formal languages › regular languages
regular expressions
0.912025
Membership Testing for Semantic Regular Expressions · Proc. ACM Program. Lang. 2025
Computer vision › Image recognition and object detection › visual concept learning
semantic concept detection
0.312025
Membership Testing for Semantic Regular Expressions · Proc. ACM Program. Lang. 2025

Methods — techniques the papers use, named apart from their topics

large language model · 1.7external oracles · 1.7
YearPublicationVenuePosition
2025 Efficient Parallel Execution of Blockchain Transactions Leveraging Conflict Specifications
Parwat Singh Anjana, Matin Amini, Rohit Kapoor, Rahul Parmar, Raghavendra Ramesh, Srivatsan Ravi, Joshua Tobkin
AFT2
2025 "How Does my Circuit Work?": Local Explanations for the Behavior of Sequential Circuits
Amirmohammad Nazari, Matin Amini, Mukund Raghothaman
FMCAD2
2025 Membership Testing for Semantic Regular Expressions
abstract
This paper is about semantic regular expressions (SemREs). This is a concept that was recently proposed by Chen et al. [ 9 ] in which classical regular expressions are extended with a primitive to query external oracles such as databases and large language models (LLMs). SemREs can be used to identify lines of text containing references to semantic concepts such as cities, celebrities, political entities, etc. The focus in their paper was on automatically synthesizing semantic regular expressions from positive and negative examples. In this paper, we study the membership testing problem :
Yifei Huang 0007, Matin Amini, Alexis Le Glaunec, Konstantinos Mamouras, Mukund Raghothaman
Proc. ACM Program. Lang.2