activity
20152026
most citedA Sound and Complete Axiomatization of Majority-n Logic

37 citations · 96 across the 13 of their papers we have counts for

collaborators

14 papers

eess.SP2026

Robust and Efficient Feature Extraction for Spike Sorting via the Walsh-Hadamard Transform

Emily Yang, Liyuan Guo, Seyed Mohammad Ali Zeinolabedin +5

Implantable neural interfaces require low-power real-time signal processing to remain within strict thermal and bandwidth constraints, motivating lightweight feature extraction met…

cs.AI2026

Automated Generation of Microfluidic Netlists using Large Language Models

Jasper Davidson, Skylar Stockham, Allen Boston +3

Microfluidic devices have emerged as powerful tools in various laboratory applications, but the complexity of their design limits accessibility for many practitioners. While progre…

cs.AR2025

Lightweight Congruence Profiling for Early Design Exploration of Heterogeneous FPGAs

Allen Boston, Biruk Seyoum, Luca Carloni +1

Field-Programmable Gate Arrays (FPGAs) have evolved from uniform logic arrays into heterogeneous fabrics integrating digital signal processors (DSPs), memories, and specialized acc…

cs.AI2025★ 1 cited

Nexus: A Lightweight and Scalable Multi-Agent Framework for Complex Tasks Automation

Humza Sami, Mubashir ul Islam, Samy Charas +3

Recent advancements in Large Language Models (LLMs) have substantially evolved Multi-Agent Systems (MASs) capabilities, enabling systems that not only automate tasks but also lever…

cs.AR2024

EDA-Aware RTL Generation with Large Language Models

Mubashir ul Islam, Humza Sami, Pierre-Emmanuel Gaillardon +1

Large Language Models (LLMs) have become increasingly popular for generating RTL code. However, producing error-free RTL code in a zero-shot setting remains highly challenging for…

cs.AI2024★ 2 cited

AIvril: AI-Driven RTL Generation With Verification In-The-Loop

Mubashir ul Islam, Humza Sami, Pierre-Emmanuel Gaillardon +1

Large Language Models (LLMs) are computational models capable of performing complex natural language processing tasks. Leveraging these capabilities, LLMs hold the potential to tra…

cs.AR2023

NSF Integrated Circuit Research, Education and Workforce Development Workshop Final Report

M. Guthaus, C. Batten, E. Brunvand +6

As the pace of progress that has followed Moore's law continues to diminish, it is critical that the US support Integrated Circuit (IC or chip) education and research to maintain t…

cs.AR2022★ 19 cited

ALICE: An Automatic Design Flow for eFPGA Redaction

Chiara Muscari Tomajoli, Luca Collini, Jitendra Bhandari +6

Fabricating an integrated circuit is becoming unaffordable for many semiconductor design houses. Outsourcing the fabrication to a third-party foundry requires methods to protect th…

cs.AR2022★ 28 cited

FlowTune: End-to-end Automatic Logic Optimization Exploration via Domain-specific Multi-armed Bandit

Walter Lau Neto, Yingjie Li, Pierre-Emmanuel Gaillardon +1

Recent years have seen increasing employment of decision intelligence in electronic design automation (EDA), which aims to reduce the manual efforts and boost the design closure pr…

cs.OH2021★ 7 cited

A Two-Level Approximate Logic Synthesis Combining Cube Insertion and Removal

Gabriel Ammes, Walter Lau Neto, Paulo Butzen +2

Approximate computing is an attractive paradigm for reducing the design complexity of error-resilient systems, therefore improving performance and saving power consumption. In this…

cs.CR2021★ 2 cited

Not All Fabrics Are Created Equal: Exploring eFPGA Parameters For IP Redaction

Jitendra Bhandari, Abdul Khader Thalakkattu Moosa, Benjamin Tan +6

Semiconductor design houses rely on third-party foundries to manufacture their integrated circuits (IC). While this trend allows them to tackle fabrication costs, it introduces sec…

cs.CR2021

Exploring eFPGA-based Redaction for IP Protection

Jitendra Bhandari, Abdul Khader Thalakkattu Moosa, Benjamin Tan +6

Recently, eFPGA-based redaction has been proposed as a promising solution for hiding parts of a digital design from untrusted entities, where legitimate end-users can restore funct…

cs.LG2020

Logic Synthesis Meets Machine Learning: Trading Exactness for Generalization

Shubham Rai, Walter Lau Neto, Yukio Miyasaka +37

Logic synthesis is a fundamental step in hardware design whose goal is to find structural representations of Boolean functions while minimizing delay and area. If the function is c…

cs.LO2015★ 37 cited

A Sound and Complete Axiomatization of Majority-n Logic

Luca Amaru, Pierre-Emmanuel Gaillardon, Anupam Chattopadhyay +1

Manipulating logic functions via majority operators recently drew the attention of researchers in computer science. For example, circuit optimization based on majority operators en…