publications

2026

1. BMVC

   A Feasibility Study on Self-Supervised LLM-Inspired Training for Generalizable Human Motion Understanding

   Mohammadreza Baharani, Ghazal Alinezhad Noghre, Armin Danesh Pazho, and 2 more authors

   In British Machine Vision Conference, 2026

   Accepted

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   A feasibility study of self-supervised, LLM-inspired training for generalizable human motion understanding using discrete motion tokenization and Vision Transformer pretraining, achieving 89.4% action classification and 76.56% AUC-ROC on anomaly detection.

2025

1. US Patent

   AI Powered Mobility Assessment System

   Hamed Tabkhivayghan, Mohammad Azarbayjani, and Mohammadreza Baharani

   Jul 2025

   US Patent 12,343,138 B2

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   An AI-powered mobility assessment system enabling automated fall risk evaluation and real-time exercise coaching via 3D skeleton modeling from monocular video on mobile devices.

2023

1. IEEE IoT

   Ancilia: Scalable Intelligent Video Surveillance for the AIoT

   Armin Danesh Pazho, Christopher Neff, Ghazal Alinezhad Noghre, and 4 more authors

   IEEE Internet of Things Journal, 2023

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   Ancilia presents a scalable intelligent video surveillance architecture for the AIoT, enabling distributed processing across edge and cloud infrastructure with privacy-preserving analytics.

2022

1. ACM TECS

   ATCN: Resource-Efficient Processing of Time Series on Edge

   Mohammadreza Baharani and Hamed Tabkhi

   ACM Transactions on Embedded Computing Systems, 2022

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   ATCN presents attention-based temporal convolutional networks enabling fast time-series classification on resource-constrained embedded devices with formalized hyperparameters for application-specific architecture tuning. Deployed on Cortex-M7 consuming only 49% of 320KB RAM and 15% of 1MB flash.

2. IEEE TITS

   

   DeepTrack: Lightweight Deep Learning for Vehicle Trajectory Prediction in Highways

   Vinit Katariya, Mohammadreza Baharani, Nichole Morris, and 2 more authors

   IEEE Transactions on Intelligent Transportation Systems, 2022

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   This paper presents DeepTrack, a lightweight deep learning approach for vehicle trajectory prediction in highways using Temporal Convolutional Networks with depthwise separable convolutions, achieving state-of-the-art accuracy with significantly reduced computational complexity for IoT deployment.

2019

1. IEEE IoT

   Real-Time Deep Learning at the Edge for Scalable Reliability Modeling of Si-MOSFET Power Electronics Converters

   Mohammadreza Baharani, Mehrdad Biglarbegian, Babak Parkhideh, and 1 more author

   IEEE Internet of Things Journal, 2019

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   A real-time LSTM-based reliability prediction system for power electronics converters, achieving scalable monitoring on IoT edge devices at 1.87W power budget.

2. IEEE IoT

   REVAMP2T: Real-Time Edge Video Analytics for Multicamera Privacy-Aware Pedestrian Tracking

   Christopher Neff, Matias Mendieta, Shrey Mohan, and 3 more authors

   IEEE Internet of Things Journal, 2019

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   An end-to-end scalable intelligent video surveillance system enabling privacy-aware multi-camera pedestrian tracking with real-time edge inference across distributed infrastructure on NVIDIA Jetson Xavier.