Summary
Hamidreza Hosseinkhani is an Applied AI researcher, machine learning engineer, and university lecturer with a decade of professional experience and 15+ years in the broader AI/software arena. He has led AI and data platform efforts at high-scale consumer businesses (SnappFood) and built applied neuroengineering and energy-disaggregation products, demonstrating strength in taking ML from research to production. As an adjunct faculty at Sharif University he teaches advanced programming and core CS topics while maintaining hands-on engineering roles, blending pedagogy with product delivery. His platform expertise spans modern data infrastructure (Kafka, Spark, Airflow, Snowplow, Feast) and ML frameworks (TensorFlow, Keras, XGBoost, LangChain), enabling end-to-end ML systems including real-time dispatching, dynamic pricing and fraud detection. He has repeatedly combined mobile and embedded IoT signals with deep learning in startups (Caro.ai, Inpin), showing a knack for resource-constrained, low-power inference systems. Based in Toronto, he brings a pragmatic mix of research depth, platform-scale engineering, and teaching experience that accelerates teams from prototypes to production.
9 years of coding experience
10 years of employment as a software developer
Bachelor of Science (BSc) Computer Engineering, Bachelor of Science (BSc) Computer Engineering at Islamic Azad University Central Tehran Branch
Master of Science (M.Sc.) Artificial Intelligence, Master of Science (M.Sc.) Artificial Intelligence at Islamic Azad University, Science And Research Branch