GIANLUCA PALERMO

Associate Professor

Politecnico di Milano

Italy

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About

Gianluca Palermo is an Associate Professor at Politecnico di Milano, Italy. His research areas include quantum molecular docking, virtual screening in drug discovery, and performance optimization for high-performance computing systems. His recent articles highlight advancements such as GPU-optimized molecular docking and the integration of machine learning for cloud system configurations.

Articles (13)

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2025

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2025

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2025

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2025

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2024

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2024

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2024

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2023

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2022

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2022

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2022

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2022

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2021

Collaborators (9)

ANDREA ROSARIO BECCARI

Head of EXSCALATE

Dompé farmaceutici SpA

ITALY

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Danilo Ardagna

Associate Professor

Politecnico di Milano

ITALY

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Christian Pilato

Associate Professor

Politecnico di Milano

ITALY

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Jan Martinovič

VSB - Technical University of Ostrava

CZECH REPUBLIC

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Elisabetta Boella

University of Lancaster

UNITED KINGDOM

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CRISTINA SILVANO

Full Professor

Politecnico di Milano

ITALY

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Murugan Natarajan Arul

KTH Royal Institute of Technology

SWEDEN

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Katerina Slaninova

VSB - Technical University of Ostrava

CZECH REPUBLIC

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João Cardoso

Full Professor (Informatics Engineering Department)

Universidade do Porto Faculdade de Engenharia

PORTUGAL

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GIANLUCA PALERMO

Research Interests

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About

Articles (13)

Molecular docking via weighted subgraph isomorphism on quantum annealers

Harnessing quality-throughput trade-off in scoring functions for extreme-scale virtual screening campaigns

To repair or not to repair: Assessing fault resilience in MPI stencil applications

Efficient parameter tuning for a structure-based virtual screening HPC application

Enabling performance portability on the LiGen drug discovery pipeline

GPU-optimized approaches to molecular docking-based virtual screening in drug discovery: A comparative analysis

Integrating Bayesian Optimization and Machine Learning for the Optimal Configuration of Cloud Systems

EXSCALATE: An Extreme-Scale Virtual Screening Platform for Drug Discovery Targeting Polypharmacology to Fight SARS-CoV-2

Quantum molecular unfolding

Pegasus: Performance Engineering for Software Applications Targeting HPC Systems

Dynamically-Tunable Dataflow Architectures Based on Markov Queuing Models

A Review on Parallel Virtual Screening Softwares for High-Performance Computers

An Efficient Monte Carlo-Based Probabilistic Time-Dependent Routing Calculation Targeting a Server-Side Car Navigation System

Collaborators (9)

ANDREA ROSARIO BECCARI

Danilo Ardagna

Christian Pilato

Jan Martinovič

Elisabetta Boella

CRISTINA SILVANO

Murugan Natarajan Arul

Katerina Slaninova

João Cardoso

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