Loriano Storchi, PhD

Taught General and Inorganic Chemistry courses, guiding hundreds of students in Biomedical Engineering and foundational sciences.

Managed and optimized network, servers, and HPC resources for the Theoretical Inorganic Chemistry Group, ensuring 99.9% system uptime for critical research.

Collaborated on interdisciplinary research projects, applying Machine Learning and Deep Learning techniques to bio- and cheminformatics.

Contributed to the development of advanced computational methods, enhancing research capabilities in complex chemical systems.

Developed and enhanced relativistic Density Functional Theory (DFT) software, contributing to cutting-edge computational chemistry research.

Collaborated on projects related to hybrid and organic photovoltaics, advancing materials science for sustainable energy applications.

Contributed to the Computational Laboratory for Hybrid and Organic Photovoltaics (CLHYO) initiatives, fostering inter-institutional research.

Developed and rigorously tested track fitting algorithms for the CMS experiment's L1 Track Triggering, ensuring efficient real-time trace reconstruction of charged particles.

Implemented algorithms on FPGA using Associative Memory, significantly optimizing data processing for the Large Hadron Collider (LHC) upgrade.

Engineered a PCA fitter for L1 track finding (github.com/lstorchi/pca_fit) and integrated it into the CMSSW framework (github.com/lstorchi/cmssw), enhancing system capabilities.

Presented research findings and project progress at numerous CERN meetings and Tracker week Phase II upgrade days, contributing to collaborative scientific advancement.

Led research into innovative cloud computing paradigms for the CMS experiment, optimizing infrastructure for future computing models.

Contributed to Open Cloud Platform (OCP) projects, enhancing distributed computing solutions for large-scale scientific data.

Awarded an Iron Medal at 'Innovate FPGA2018' for contributions to 'Reconfigurable Computing,' demonstrating leadership in hardware acceleration.

Applied Machine Learning techniques to HEP and medical data, improving data analysis and interpretation for complex datasets.

Developed and optimized core components for commercial software including libgrid/grid, MoKa, and DeepGrid, enhancing drug discovery and molecular analysis capabilities.

Contributed to the development of in-silico pKa computation (MoKa), tautomer enumeration (libtaut/tauthor), and logD/logP prediction (liblogd), improving predictive modeling accuracy.

Enhanced molecular interaction field (MIF) analysis and protein pKa prediction (MoKaBio), leading to more robust and reliable computational results.

Acquired and applied proficiency in the Qt framework for commercial software development, improving user interface and application functionality.

Taught General and Inorganic Chemistry courses, educating students and contributing to curriculum development over nine years.

Administered systems and networks for the Theoretical Inorganic Chemistry Group, maintaining essential research infrastructure.

Collaborated on Computational Finance projects, developing High-Performance Computing code for financial risk evaluation.

Contributed to bio and cheminformatics research, leveraging computational methods for scientific discovery and analysis.

Implemented and optimized non-relativistic and relativistic DFT codes for parallel computing architectures, including GPU, enhancing computational efficiency.

Developed software and computational techniques for the simulation and characterization of TiO2 nanostructured materials, advancing materials science research.

Improved Python programming and Visualization Toolkit (VTK) skills, applying them to complex computational geometry problems.

Optimized and ported meteorological platform codes to multi- and many-core HPC environments, achieving substantial performance improvements for climate simulations.

Provided scientific consulting and programming expertise, contributing to advanced climate modeling initiatives.

Developed a Python-based tool for database synchronization on the Joomla! platform, ensuring efficient data management for the 'Tazebao of the XXI century' project.

Developed and optimized codes for gravitational signal analysis within the Einstein Telescope project, leveraging Many-Core (GPGPU) programming techniques.

Co-wrote the Design Study for the Einstein Telescope, providing critical input for project planning and execution.

Acquired foundational skills in Digital Signal Processing (DSP) and advanced Many-Core programming.

Served as a staff organizer for HOPV2010 as a consultant for the Italian Chemical Society.

Developed and parallelized code for the theoretical study of lifetimes of ionized states, advancing research in non-Hermitian Green functions.

Administered systems and networks for ISTM and the Department of Chemistry, ensuring robust IT infrastructure for research activities.

Provided scientific consulting and programming for the CRC, optimizing and managing parallel codes for convective weather simulation in HPC environments.

Successfully completed Ph.D. with a thesis on 'Innovative computational strategies for ab-initio Quantum Chemistry: Grid Computing and novel Green's function techniques'.

Administered and configured network and servers (DNS, mail, DHCP, web servers) and clustered HPC Beowulf resources for ISTM and the Department of Chemistry.

Developed the not-Dyson ADC(3) method for molecular ionization spectra and a Java Servlet portal for potential energy surface simulations on a computing grid.

Contributed to the architectural and software aspects of the Chemgrid project, enhancing distributed computing for chemical applications.

Developed codes for the ASSIST parallel environment, contributing to chemical applications on high-performance distributed platforms.

Created a methodology for dynamic memory allocation within the ASSIST framework, optimizing resource utilization and system efficiency.

Programmed in diverse scientific fields, supporting skilled personnel in system management and networking activities.

Conducted research on parallelization of computational chemistry programs using Message Passing and Shared Memory techniques, improving computational speed.

Developed ASSIST patterns and parallel programs, collaborating with the Italian Space Agency (ASI) and the Department of Computer Science (University of Pisa).