Rate My Professor Anand Panangadan

California State University, Fullerton

Computer Science Engineering Geoscience Health Science Social Science Artificial Intelligence Machine Learning Big Data Data Mining Computer Vision

4.5

2 reviews · out of 5

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Ratings & reviews

5.05/4/2026

Makes learning interactive and engaging.

4.06/27/2025

Creates a positive and welcoming vibe.

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About Anand

Anand Panangadan is Professor of Computer Science in the College of Engineering and Computer Science at California State University, Fullerton. He received his Ph.D. and M.S. in Computer Science from the University of California, Los Angeles, and his B.Tech. in Computer Science and Engineering from the Indian Institute of Technology, Bombay. Before joining CSUF as an assistant professor in fall 2015, he held positions as Senior Research Associate at the University of Southern California, Post-doctoral Affiliate at the NASA Jet Propulsion Laboratory/Caltech, and Research Specialist at Children’s Hospital Los Angeles. At CSUF, he advises junior and senior Computer Science students and serves on academic senate committees.

Dr. Panangadan's research focuses on applications of artificial intelligence and machine learning to real-world problems in homelessness, transportation, healthcare, earth science, sensor networks, and robotics. His specific interests include machine learning, text mining, social network analysis, and sensor data processing, the latter evidenced by two US patents. He has published over 50 peer-reviewed conference papers and journal articles. Recent publications include "zSHIFT: A Siamese Hierarchical Transformer Network for Zero Shot Time Series Forecasting" (2025, IEEE International Conference on Information Reuse and Integration and Data Science), "Design and Development of a Real-Time Camera-Based Smart Cooking Assistant" (2025, IEEE IRI), "Quantitative Evaluation of AI-Generated Recipes for Health Recommender Systems" (2025, IEEE IRI), "Visual and Thermal Imaging Camera-Based System for a Smart Cooking Assistant" (2024, IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability), and "Integration of Multiple Sensor-Based Wellness Systems for Supportive Housing Using Bluetooth Low Energy" (2024, IEEE ECBIOS, Best Paper Award). Highly cited works from Google Scholar include "Logistic LASSO regression for dietary intakes and breast cancer" (2020, 297 citations), "Fast high-resolution terahertz radar imaging at 25 meters" (2010, 131 citations), and "Clinical evaluation of a novel interstitial fluid sensor system for remote continuous alcohol monitoring" (2008, 93 citations). As Principal Investigator, he has obtained grants from the National Science Foundation, USDA, Air Force Research Laboratory, University of California Center on Economic Competitiveness in Transportation (US Department of Transportation and Caltrans), Cisco Systems, GE Digital, CSU Chancellor’s Office, and CSU Fullerton. His awards include the NASA Space Act Award, Course Redesign with Technology grant from the CSU Chancellor’s Office, Research, Scholarship and Creative Activity Incentive Grants from CSU Fullerton, FDC Faculty Recognition in Teaching, Faculty Advisor of Distinction, and Faculty Recognition of Extraordinary and Sustained Service at CSUF. He teaches courses such as CPSC 375: Introduction to Data Science and Big Data, and CPSC 481: Artificial Intelligence.