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Department of Electrical and Computer Engineering

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Scholarly Works by Year

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TypeCount
Academic Publications13
Academic Conferences20

Scholarly Works by Year

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YearTypeCount
2020Academic Publications1
2021Academic Publications1
2022Academic Publications2
2023Academic Publications3
2024Academic Publications2
2025Academic Publications2
2026Academic Publications2
2021Academic Conferences2
2022Academic Conferences2
2024Academic Conferences8
2025Academic Conferences6
2026Academic Conferences2

Department Research Summary

The Department of Electrical and Computer Engineering at San Diego State University has a strong research focus on developing innovative solutions in artificial intelligence, machine learning, computer architecture, and edge computing. Recent works showcase expertise in co-design approaches for accelerating AI workloads, including software-hardware co-optimization, algorithm-architecture co-design, and processing-in-memory techniques.

Researchers in the department are exploring applications of these technologies in various domains, such as healthcare (e.g., glucose level prediction), environmental monitoring, and mass spectrometry analysis. The department's research also emphasizes energy efficiency, low-power design, and novel memory technologies, including hyperdimensional computing and resistive random-access memory.

Generated using Llama 3.1 based on recent grants, publications, and conferences.

Department Scholarship

Academic Publications

AA-DiT: An Algorithm-Architecture Co-Design for Diffusion Transformer Acceleration
Siqi Li; Flavio Ponzina; Tajana Rosing
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2026, journal article, Cited by: OpenAlex: 1
Artificial intelligence Computer architecture Machine learning Transformers
Constraint-Scheduled Bayesian Optimization for Software-Hardware Co-Optimization on HDnn-PIM
Chien-Yi Yang; Flavio Ponzina; Minxuan Zhou; Raid Ayoub; Pietro Mercati; Tajana Rosing
IEEE Embedded Systems Letters, 2026, journal article
Artificial intelligence Computer architecture Machine learning Neural networks (Computer science)
GlucoseHD: Predicting Glucose Levels Using Hyperdimensional Computing
Flavio Ponzina; Mialyssa Gomez; Congge Xu; Tajana Šimunić Rosing
IEEE Design & Test, 2025, journal article, Cited by: OpenAlex: 4
Artificial intelligence Bioinformatics Diabetes Machine learning
LionHeart: A Layer-Based Mapping Framework for Heterogeneous Systems With Analog In-Memory Computing Tiles
Corey Lammie; Yuxuan Wang; Flavio Ponzina; et al.
IEEE Transactions on Emerging Topics in Computing, 2025, journal article, Cited by: OpenAlex: 10
Computer architecture Electronic circuits Heterogeneous distributed computing systems Information storage and retrieval systems
An Energy Efficient Soft SIMD Microarchitecture and Its Application on Quantized CNNs
Pengbo Yu; Flavio Ponzina; et al.
IEEE Transactions on Very Large Scale Integration (Vlsi) Systems, 2024, journal article, Cited by: OpenAlex: 7
Artificial intelligence Computer architecture Neural networks (Computer science) SIMD (Computer architecture)

SpecPCM: A Low-Power PCM-Based In-Memory Computing Accelerator for Full-Stack Mass Spectrometry Analysis
Keming Fan; Ashkan Moradifirouzabadi; Xiangjin Wu; Zheyu Li; Flavio Ponzina; et al.
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2024, journal article, Cited by: OpenAlex: 8
Mass spectrometry
An Error-Based Approximation Sensing Circuit for Event-Triggered Low-Power Wearable Sensors
Silvio Zanoli; Flavio Ponzina; Tomás Teijeiro; Alexandre Levisse; David Atienza
IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2023, journal article, Cited by: OpenAlex: 4
Electronic circuits Wearable technology
Bit-Line Computing for CNN Accelerators Co-Design in Edge AI Inference
Marco Rios; Flavio Ponzina; Alexandre Levisse; Giovanni Ansaloni; David Atienza
IEEE Transactions on Emerging Topics in Computing, 2023, journal article, Cited by: OpenAlex: 16
Artificial intelligence Computer architecture Natural language processing Neural networks (Computer science)
Overflow-free Compute Memories for Edge AI Acceleration
Flavio Ponzina; Marco Rios; Alexandre Levisse; Giovanni Ansaloni; David Atienza
Acm Transactions on Embedded Computing Systems, 2023, journal article, Cited by: OpenAlex: 8
Artificial intelligence Edge computing Machine learning Microprocessors
Using Algorithmic Transformations and Sensitivity Analysis to Unleash Approximations in CNNs at the Edge
Flavio Ponzina; Giovanni Ansaloni; Miguel Peón-Quirós; David Atienza
Micromachines, 2022, journal article, Cited by: OpenAlex: 1
Algorithms Approximation theory Deep learning (Machine learning) Neural networks (Computer science)
A Hardware/Software Co-Design Vision for Deep Learning at the Edge
Flavio Ponzina; et al.
IEEE Micro, 2022, journal article, Cited by: OpenAlex: 15
Computer hardware description languages Deep learning (Machine learning) Edge computing Machine learning
E2CNNs: Ensembles of Convolutional Neural Networks to Improve Robustness Against Memory Errors in Edge-Computing Devices
Flavio Ponzina; Miguel Peon-Quiros; Andreas Burg; David Atienza
IEEE Transactions on Computers, 2021, journal article, Cited by: OpenAlex: 23
Edge computing Ensemble learning (Machine learning) Robust control
Impact of Memory Voltage Scaling on Accuracy and Resilience of Deep Learning Based Edge Devices
Benoit W. Denkinger; Flavio Ponzina; et al.
IEEE Design & Test, 2020, journal article, Cited by: OpenAlex: 14
Deep learning (Machine learning) Edge computing Energy consumption Resilience (Personality trait)

Academic Conferences

HeteroRAGCache: Software-Hardware Co-Design for Efficient RAG Caching using Emerging Memories
Jangseon Park; Kiseok Suh; Flavio Ponzina; Tajana Rosing
2026, conference paper
Cache memory Computer architecture Computer engineering Heterogeneous distributed computing systems
QMC: Efficient SLM Edge Inference via Outlier-Aware Quantization and Emergent Memories Co-Design
Nilesh Prasad Pandey; Jangseon Park; Onat Gungor; Flavio Ponzina; Tajana Rosing
2026, conference paper
Artificial intelligence Electronics in military engineering Machine learning Neural networks (Computer science)
E-QUARTIC: Energy Efficient Edge Ensemble of Convolutional Neural Networks for Resource-Optimized Learning
Le Zhang; Onat Gungor; Flavio Ponzina; Tajana Rosing
2025, conference paper
Artificial intelligence Edge computing Machine learning Neural networks (Computer science)
DPQ-HD: Post-Training Compression for Ultra-Low Power Hyperdimensional Computing
Nilesh Prasad Pandey; Shriniwas Kulkarni; David Wang; Onat Gungor; Flavio Ponzina; Tajana Rosing
2025, conference paper
Computer engineering Electronics Machine learning Neural networks (Computer science)
Offload Rethinking by Cloud Assistance for Efficient Environmental Sound Recognition on LPWANs
Le Zhang; Quanling Zhao; Run Wang; Shirley Bian; Onat Gungor; Flavio Ponzina; et al.
2025, conference paper
Cloud computing Environmental monitoring Machine learning Sustainability

FeNOMS: Enhancing Open Modification Spectral Library Search with In-Storage Processing on Ferroelectric NAND (FeNAND) Flash
Sumukh Pinge; Ashkan Moradifirouzabadi; Keming Fan; Prasanna Venkatesan Ravindran; Tanvir H. Pantha; Po-Kai Hsu; Zheyu Li; Weihong Xu; Zihan Xia; Flavio Ponzina; et al.
2025 IEEE/Acm International Conference on Computer Aided Design (Iccad), 2025, conference paper
Information storage and retrieval systems Machine learning Natural language processing Semiconductor storage devices
HyperDrone: An Accurate, Robust, Fast, and Energy-Efficient Approach for Drone Classification
Shriniwas Kulkarni; Flavio Ponzina; Tajana Rosing
2025 IEEE 43Rd International Conference on Computer Design (Iccd), 2025, conference paper
Artificial intelligence Computer vision Drone aircraft Machine learning
SmartMS: Efficient Hierarchical Database Search for Mass Spectrometry via Processing-in-Memory
Flavio Ponzina; et al.
2025 IEEE/Acm International Symposium on Low Power Electronics and Design (Islped), 2025, conference paper
Computer architecture Database searching Mass spectrometry Parallel processing (Electronic computers)
DBFS: Dynamic Bitwidth-Frequency Scaling for Efficient Software-defined SIMD
Pengbo Yu; Flavio Ponzina; et al.
2024 IEEE Computer Society Annual Symposium on Vlsi (Isvlsi), 2024, conference paper
Computer architecture Computer network architectures Energy consumption SIMD (Computer architecture)
HDXpose: Harnessing Hyperdimensional Computing's Explainability for Adversarial Attacks
Fatemeh Asgarinejad; Flavio Ponzina; Onat Gungor; Tajana Rosing; Baris Aksanli
2024, conference paper
Artificial intelligence Computer security Machine learning
Multi-Objective Software-Hardware Co-Optimization for HD-PIM via Noise-Aware Bayesian Optimization
Chien-Yi Yang; Minxuan Zhou; Flavio Ponzina; et al.
2024, conference paper
Artificial intelligence Computer architecture Machine learning
Resource-Efficient Continual Learning for Personalized Online Seizure Detection
Amirhossein Shahbazinia; Flavio Ponzina; Jose A. Miranda; Jonathan Dan; Giovanni Ansaloni; David Atienza
2024 46Th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Embc), 2024, conference paper
Artificial intelligence Deep learning (Machine learning) Machine learning National Institute of Neurological Disorders and Stroke (U.S.)
Using ensemble learning to improve radiation tolerance of CNNs in space applications
Flavio Ponzina; et al.
Spaice, 2024, conference paper
Computer science Ensemble learning (Machine learning) Exploration of outer space
Filament-Free Bulk RRAM with High Endurance and Long Retention for Neuromorphic Few-Shot Learning On-Chip
Ashwani Kumar; Yucheng Zhou; Sai Praneeth Potladurthy; Jeong-Hoon Kim; Weihong Xu; Flavio Ponzina; et al.
2024 IEEE International Electron Devices Meeting (Iedm), 2024, conference paper
Electronics Machine learning Neural networks (Computer science) Nonvolatile random-access memory
HyperECG: ECG Signal Inference From Radar With Hyperdimensional Computing
Matilda Gaddi; Flavio Ponzina; Fatemeh Asgarinejad; Baris Aksanli; Tajana Rosing
2024 IEEE 24Th International Conference on Bioinformatics and Bioengineering (Bibe), 2024, conference paper
Biomedical engineering Electrocardiography Machine learning Signal processing
Multi-Model Inference Composition of Hyperdimensional Computing Ensembles
Flavio Ponzina; Rishikanth Chandrasekaran; Anya Wang; Seiji Minowada; Siddharth Sharma; Tajana Rosing
2024 IEEE 42Nd International Conference on Computer Design (Iccd), 2024, conference paper
Artificial intelligence Ensemble learning (Machine learning) Heterogeneous distributed computing systems Neural networks (Computer science)
Error Resilient In-Memory Computing Architecture for CNN Inference on the Edge
Marco Rios; Flavio Ponzina; Giovanni Ansaloni; Alexandre Levisse; David Atienza
Proceedings of the Great Lakes Symposium on Vlsi 2022, 2022, conference paper
Artificial intelligence Deep learning (Machine learning) Edge computing Machine learning
An Accuracy-Driven Compression Methodology to Derive Efficient Codebook-Based CNNs
Flavio Ponzina; Miguel Peon-Quiros; Giovanni Ansaloni; David Atienza
2022 IEEE International Conference on Omni-Layer Intelligent Systems (Coins), 2022, conference paper
Artificial intelligence Deep learning (Machine learning) Efficiency wage theory
A Flexible In-Memory Computing Architecture for Heterogeneously Quantized CNNs
Flavio Ponzina; Marco Rios; Giovanni Ansaloni; Alexandre Levisse; David Atienza
2021 IEEE Computer Society Annual Symposium on Vlsi (Isvlsi), 2021, conference paper
Artificial intelligence Deep learning (Machine learning) Neural networks (Computer science) Parallel processing (Electronic computers)
Running Efficiently CNNs on the Edge Thanks to Hybrid SRAM-RRAM In-Memory Computing
Marco Rios; Flavio Ponzina; Giovanni Ansaloni; Alexandre Levisse; David Atienza
2021 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (Date), 2021, conference paper
Artificial intelligence Edge computing Machine learning Neural networks (Computer science)