Massoud Pedram
10 papers · 2019–2026 · 8 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Interdisciplinary Bridge π§ Keyword Pioneer π Academic Marathon (7) π Cross-Pollinator (9)
πΊοΈ
Taxonomy Completionist
(31)
π
Conference Polyglot
(8)
π
Grand Slam
π
Century Club
(10)
π
Conference Pioneer
Conferences
WACV (3)
AAAI (1)
EMNLP (1)
ICCV (1)
ICLR (1)
ICML (1)
IJCAI (1)
NIPS (1)
Top co-authors
Keywords
model compression
(4)
spiking neural network
(2)
neural network pruning
(2)
few-shot learning
(1)
knowledge distillation
(1)
conformal prediction
(1)
adversarial robustness
(1)
computer vision
(1)
model robustness
(1)
attention mechanism
(1)
neuromorphic hardware
(1)
adversarial training
(1)
task generalization
(1)
energy efficiency
(1)
accuracy robustness trade-off
(1)
transfer learning
(1)
spectral decomposition
(1)
adversarial attack
(1)
multi-task learning
(1)
image classification
(1)
Papers
FAIR-SIGHT: Fairness Assurance in Image Recognition via Simultaneous Conformal Thresholding and Dynamic Output Repair
WACV 2026
FACTER: Fairness-Aware Conformal Thresholding and Prompt Engineering for Enabling Fair LLM-Based Recommender Systems
ICML 2025
MambaExtend: A Training-Free Approach to Improve Long Context Extension of Mamba
ICLR 2025
Efficient Counterexample-Guided Fairness Verification and Repair of Neural Networks Using Satisfiability Modulo Convex Programming
IJCAI 2025
LaMDA: Large Model Fine-Tuning via Spectrally Decomposed Low-Dimensional Adaptation
EMNLP 2024
FLOAT: Fast Learnable Once-for-All Adversarial Training for Tunable Trade-Off Between Accuracy and Robustness
WACV 2023
Analyzing the Confidentiality of Undistillable Teachers in Knowledge Distillation
NIPS 2021
Spike-Thrift: Towards Energy-Efficient Deep Spiking Neural Networks by Limiting Spiking Activity via Attention-Guided Compression
WACV 2021
HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training With Crafted Input Noise
ICCV 2021
A Meta-Learning Approach for Custom Model Training
AAAI 2019