activity
20192025
most citedAn Automated Spectral Clustering for Multi-scale Data

24 citations · 26 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2025

Context-aware LLM-based AI Agents for Human-centered Energy Management Systems in Smart Buildings

Tianzhi He, Farrokh Jazizadeh

This study presents a conceptual framework and a prototype assessment for Large Language Model (LLM)-based Building Energy Management System (BEMS) AI agents to facilitate context-…

cs.LG2022★ 1 cited

DEGAN: Time Series Anomaly Detection using Generative Adversarial Network Discriminators and Density Estimation

Yueyan Gu, Farrokh Jazizadeh

Developing efficient time series anomaly detection techniques is important to maintain service quality and provide early alarms. Generative neural network methods are one class of…

cs.LG2022★ 1 cited

Using Statistical Models to Detect Occupancy in Buildings through Monitoring VOC, CO, and other Environmental Factors

Mahsa Pahlavikhah Varnosfaderani, Arsalan Heydarian, Farrokh Jazizadeh

Dynamic models of occupancy patterns have shown to be effective in optimizing building-systems operations. Previous research has relied on CO sensors and vision-based technique…

eess.SP2020

Two-stage building energy consumption clustering based on temporal and peak demand patterns

Milad Afzalan, Farrokh Jazizadeh, Hoda Eldardiry

Analyzing smart meter data to understand energy consumption patterns helps utilities and energy providers perform customized demand response operations. Existing energy consumption…

cs.LG2019★ 24 cited

An Automated Spectral Clustering for Multi-scale Data

Milad Afzalan, Farrokh Jazizadeh

Spectral clustering algorithms typically require a priori selection of input parameters such as the number of clusters, a scaling parameter for the affinity measure, or ranges of t…