Zahra Ghorrati

Computer Science · Purdue University West Lafayette

Early career · publishing since 2018Rising activity

Context-Aware Activity Recognition Systems Metaheuristic Optimization Algorithms Research Neural Networks and Applications Time Series Analysis and Forecasting IoT and Edge/Fog Computing

Publications

Citations

Est. group size

Recurring co-author estimate

Active years

Publishing since 2018

Research summary

AI-generated

Zahra Ghorrati's work focuses on machine learning methods for analyzing time series data, especially for recognizing human activities using wearable sensors, and on designing neural network architectures and optimization algorithms. Earlier work also included computational modeling of eye movement control systems and optimization techniques for changing (dynamic) environments. This research combines deep learning, sensor data processing, and algorithm design, with applications relevant to health monitoring and smart devices.

Human activity recognition from wearable sensorsDeep learning architectures for time series dataNeural network training algorithmsOptimization and metaheuristic algorithmsComputational modeling of biological systems

Publication output has grown over the last decade, rising from occasional single papers before 2021 to a more steady pace of 2-5 papers per year since 2022.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence

Publications per year over the last 10 years — averaging 3.0/year recently

Recent publications

SCALABLE HIERARCHICAL DEEP NEURAL NETWORK
Purdue · 2026
SCALABLE HIERARCHICAL DEEP NEURAL NETWORK
Purdue · 2026
Scalable Hierarchical Deep Neural Network for Time Series Analysis in Wearable Sensor-based Human Activity Recognition
Proceedings of the AAAI Conference on Artificial Intelligence · 2025
A full-featured cooperative coevolutionary memory-based artificial immune system for dynamic optimization
Applied Soft Computing · 2021
A Computational System-Level Model of Oculomotor Pathways Accounting for the Representation of Eye Biomechanics in the Cerebellar Vermis
IEEE Access · 2020
A New Adaptive Learning algorithm to train Feed-Forward Multi-layer Neural Networks, Applied on Function Approximation Problem
2020

Publishes in

arXiv (Cornell University)×4
Lecture notes in computer science×3
IEEE Access×2
Purdue×2
Systems×1

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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 20, 2026.

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