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Information on didactic, research and institutional assignments on this page are certified by the University; more information, prepared by the lecturer, are available on the personal web page and in the curriculum vitae indicated on this webpage.
Information
LecturerIelmini Daniele
QualificationFull professor full time
Belonging DepartmentDipartimento di Elettronica, Informazione e Bioingegneria
Scientific-Disciplinary SectorIINF-01/A - Electronics
Curriculum VitaeDownload CV (361.15Kb - 13/01/2022)
OrcIDhttps://orcid.org/0000-0002-1853-1614

Contacts
Office hours
DepartmentFloorOfficeDayTimetableTelephoneFaxNotes
Elettronica e Informazione, via Golgi 40 (Ed. 16)------FridayFrom 10:00
To 12:00
0223996120------
E-maildaniele.ielmini@polimi.it
Personal websitehttp://www.dei.polimi.it/personale/docentidettaglio.php?id_docente=120&id_sezione=&lettera=I&idlang=

Data source: RE.PUBLIC@POLIMI - Research Publications at Politecnico di Milano

List of publications and reserach products for the year 2024 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Contributions on scientific books
Development of Crosspoint Memory Arrays for Neuromorphic Computing (Show >>)
Conference proceedings
Drift Compensation in Multilevel PCM for in-Memory Computing Accelerators (Show >>)
Journal Articles
Compact Modeling and Mitigation of Parasitics in Crosspoint Accelerators of Neural Networks (Show >>)
Hardware implementation of memristor-based artificial neural networks (Show >>)
Memristive tonotopic mapping with volatile resistive switching memory devices (Show >>)
Programming Characteristics of Electrochemical Random Access Memory (ECRAM)—Part I: Experimental Study (Show >>)
Programming Characteristics of Electrochemical Random Access Memory (ECRAM)—Part II: Physics-Based Modeling (Show >>)


List of publications and reserach products for the year 2023 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Contributions on scientific books
Memristive/CMOS devices for neuromorphic applications (Show >>)
Conference proceedings
Accelerating massive MIMO in 6G communications by analog in-memory computing circuits (Show >>)
An SRAM-based reconfigurable analog in-memory computing circuit for solving linear algebra problems (Show >>)
An Ultrafast (< 200 ns) Sparse Solution Solver made by HfWOx/VOy Threshold Tunable Neurons (Show >>)
Closed-Loop In-Memory Computing for Energy-Efficient Matrix Eigendecomposition (Show >>)
Compact Modeling of Resistive Switching Memory (RRAM) With Voltage and Temperature Dependences (Show >>)
Enhancing reliability of a strong physical unclonable function (PUF) solution based on virgin-state phase change memory (PCM) (Show >>)
In-memory neural network accelerator based on phase change memory (PCM) with one-selector/one-resistor (1S1R) structure operated in the subthreshold regime (Show >>)
NimbleAI: Towards Neuromorphic Sensing-Processing 3D-integrated Chips (Show >>)
TCAD Modeling of Germanium Behavior During Forming Operation in Ge-Rich ePCM (Show >>)
Thermal-Induced Multi-State Memristors for Neuromorphic Engineering (Show >>)
Unveiling Retention Physical Mechanism of Ge-rich GST ePCM Technology (Show >>)
Journal Articles
A Generalized Block-Matrix Circuit for Closed-Loop Analog In-Memory Computing (Show >>)
A Multilayer Neural Accelerator With Binary Activations Based on Phase-Change Memory (Show >>)
A self-adaptive hardware with resistive switching synapses for experience-based neurocomputing (Show >>)
Binary‐Stochasticity‐Enabled Highly Efficient Neuromorphic Deep Learning Achieves Better‐than‐Software Accuracy (Show >>)
Hybrid 2D-CMOS microchips for memristive applications (Show >>)
In-Memory Computing for Machine Learning and Deep Learning (Show >>)
In-Memory Principal Component Analysis by Analogue Closed-Loop Eigendecomposition (Show >>)
In-memory computing with emerging memory devices: Status and outlook (Show >>)
Modeling and Analysis of Virgin Ge-Rich GST Embedded Phase Change Memories (Show >>)
Process-Voltage-Temperature Variations Assessment in Energy-Aware Resistive RAM-Based FPGAs (Show >>)
Reservoir Computing with Charge-Trap Memory Based on a MoS2 Channel for Neuromorphic Engineering (Show >>)
Threshold Switching by Bipolar Avalanche Multiplication in Ovonic Chalcogenide Glasses (Show >>)
Tunable synaptic working memory with volatile memristive devices (Show >>)


List of publications and reserach products for the year 2022 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Patents
NANOWIRE-BASED DEVICE FOR IMPLEMENTING A RESERVOIR FOR A NEURAL NETWORK (Show >>)
Contributions on scientific books
Analogue In-Memory Computing with Resistive Switching Memories (Show >>)
Computing with nonvolatile memories for artificial intelligence (Show >>)
Conference proceedings
A Hybrid Memristor/CMOS SNN for Implementing One-Shot Winner-Takes-All Training (Show >>)
Characterization of reset state through energy activation study in Ge-GST based ePCM (Show >>)
Decision Making by a Neuromorphic Network of Volatile Resistive Switching Memories (Show >>)
End-to-end modeling of variability-aware neural networks based on resistive-switching memory arrays (Show >>)
Experimental verification and benchmark of in-memory principal component analysis by crosspoint arrays of resistive switching memory (Show >>)
Exploring Process-Voltage-Temperature Variations Impact on 4T1R Multiplexers for Energy-aware Resistive RAM-based FPGAs (Show >>)
Interaction between forming pulse and integration process flow in ePCM (Show >>)
Low-current, highly linear synaptic memory device based on MoS2 transistors for online training and inference (Show >>)
Mitigating read-program variation and IR drop by circuit architecture in RRAM-based neural network accelerators (Show >>)
Modeling Environment for Ge-rich GST Phase Change Memory Cells (Show >>)
Statistical model of program/verify algorithms in resistive-switching memories for in-memory neural network accelerators (Show >>)
Status and challenges of in-memory computing for neural accelerators (Show >>)
Thermal switching of TiO2-based RRAM for parameter extraction and neuromorphic engineering (Show >>)
Scientific Books
Resistive Switching: Oxide Materials, Mechanisms, Devices and Operations (Show >>)
Journal Articles
2022 roadmap on neuromorphic computing and engineering (Show >>)
A CMOS-memristor hybrid system for implementing stochastic binary spike timing-dependent plasticity (Show >>)
An analogue in-memory ridge regression circuit with application to massive MIMO acceleration (Show >>)
An energy-efficient in-memory computing architecture for survival data analysis based on resistive switching memories (Show >>)
BEOL Process Effects on ePCM Reliability (Show >>)
Forming-Free Resistive Switching Memory Crosspoint Arrays for In-Memory Machine Learning (Show >>)
HfO2-based resistive switching memory devices for neuromorphic computing (Show >>)
In-Memory Principal Component Analysis by Crosspoint Array of Resistive Switching Memory: A New Hardware Approach for Energy-Efficient Data Analysis in Edge Computing (Show >>)
Invited Tutorial: Analog Matrix Computing with Crosspoint Resistive Memory Arrays (Show >>)
Ionic-electronic halide perovskite memdiodes enabling neuromorphic computing with a second-order complexity (Show >>)
Low Conductance State Drift Characterization and Mitigation in Resistive Switching Memories (RRAM) for Artificial Neural Networks (Show >>)
Memtransistor Devices Based on MoS 2 Multilayers with Volatile Switching due to Ag Cation Migration (Show >>)
Modeling and Compensation of IR Drop in Crosspoint Accelerators of Neural Networks (Show >>)
Pavlovian conditioning achieved via one-transistor/one-resistor memristive synapse (Show >>)
Redox memristors with volatile threshold switching behavior for neuromorphic computing (Show >>)
Three-Terminal Ovonic Threshold Switch (3T-OTS) with Tunable Threshold Voltage for Versatile Artificial Sensory Neurons (Show >>)


List of publications and reserach products for the year 2021 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Patents
Dispositivo basato su nanofili per l’implementazione di un reservoir per una rete neurale (Show >>)
Contributions on scientific books
Drift Phenomena in Phase Change Memories (Show >>)
Conference proceedings
Conductance variations and their impact on the precision of in-memory computing with resistive switching memory (RRAM) (Show >>)
Improving Ge-rich GST ePCM reliability through BEOL engineering (Show >>)
Modeling of oxide-based ECRAM programming by drift-diffusion ion transport (Show >>)
Optimized programming algorithms for multilevel RRAM in hardware neural networks (Show >>)
Tackling the Low Conductance State Drift through Incremental Reset and Verify in RRAM arrays (Show >>)
Journal Articles
A Brain-Inspired Homeostatic Neuron Based on Phase-Change Memories for Efficient Neuromorphic Computing (Show >>)
A Drift-Resilient Hardware Implementation of Neural Accelerators Based on Phase Change Memory Devices (Show >>)
A Universal, Analog, In-Memory Computing Primitive for Linear Algebra Using Memristors (Show >>)
Accurate Program/Verify Schemes of Resistive Switching Memory (RRAM) for In-Memory Neural Network Circuits (Show >>)
Brain-inspired computing via memory device physics (Show >>)
Combining accuracy and plasticity in convolutional neural networks based on resistive memory arrays for autonomous learning (Show >>)
Empirical metal-oxide RRAM device endurance and retention model for deep learning simulations (Show >>)
In materia reservoir computing with a fully memristive architecture based on self-organizing nanowire networks (Show >>)
In-memory computing with resistive memory circuits: Status and outlook (Show >>)
Materials challenges and opportunities for brain-inspired computing (Show >>)
Optimization Schemes for In-Memory Linear Regression Circuit With Memristor Arrays (Show >>)
Redundancy and Analog Slicing for Precise In-Memory Machine Learning--Part II: Applications and Benchmark (Show >>)
Redundancy and Analog Slicing for Precise in-Memory Machine Learning--Part I: Programming Techniques (Show >>)
Standards for the Characterization of Endurance in Resistive Switching Devices (Show >>)
Switching Dynamics of Ag Based Filamentary Volatile Resistive Switching Devices--Part I: Experimental Characterization (Show >>)
Switching Dynamics of Ag-Based Filamentary Volatile Resistive Switching Devices--Part II: Mechanism and Modeling (Show >>)


List of publications and reserach products for the year 2020 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Contributions on scientific books
Applications of Resistive Switching Memory as Hardware Security Primitive (Show >>)
Synaptic realizations based on memristive devices (Show >>)
Conference proceedings
A SiOx RRAM-based hardware with spike frequency adaptation for power-saving continual learning in convolutional neural networks (Show >>)
A Spiking Recurrent Neural Network with Phase Change Memory Synapses for Decision Making (Show >>)
A bio-inspired recurrent neural network with self-adaptive neurons and PCM synapses for solving reinforcement learning tasks (Show >>)
Hardware implementation of PCM-based neurons with self-regulating threshold for homeostatic scaling in unsupervised learning (Show >>)
In-memory PageRank using a Crosspoint Array of Resistive Switching Memory (RRAM) devices (Show >>)
Modeling of virgin state and forming operation in embedded phase change memory (PCM) (Show >>)
Journal Articles
A Compact Model for Stochastic Spike-Timing-Dependent Plasticity (STDP) Based on Resistive Switching Memory (RRAM) Synapses (Show >>)
A spiking recurrent neural network with phase change memory neurons and synapses for the accelerated solution of constraint satisfaction problems (Show >>)
Analytical modeling of electrochemical metallization memory device with dual-layer structure of Ag/AgInSbTe/amorphous C/Pt (Show >>)
Bio-Inspired Techniques in a Fully Digital Approach for Lifelong Learning (Show >>)
Brain‐Inspired Structural Plasticity through Reweighting and Rewiring in Multi‐Terminal Self‐Organizing Memristive Nanowire Networks (Show >>)
Device and Circuit Architectures for In‐Memory Computing (Show >>)
In-Memory PageRank Accelerator With a Cross-Point Array of Resistive Memories (Show >>)
Integration and co-design of memristive devices and algorithms for artificial intelligence (Show >>)
In‐Memory Eigenvector Computation in Time O (1) (Show >>)
Memristive and CMOS Devices for Neuromorphic Computing (Show >>)
Neuromorphic Motion Detection and Orientation Selectivity by Volatile Resistive Switching Memories (Show >>)
One-step regression and classification with cross-point resistive memory arrays (Show >>)
Reliability of Logic-in-Memory Circuits in Resistive Memory Arrays (Show >>)
Time Complexity of In-Memory Solution of Linear Systems (Show >>)
Toward a generalized Bienenstock-Cooper-Munro rule for spatiotemporal learning via triplet-STDP in memristive devices (Show >>)
manifesti v. 3.7.1 / 3.7.1
Area Servizi ICT
24/07/2024