Hamed Janani, Ph.D.
About Hamed Janani, Ph.D.
Hamed Janani, Ph.D., is a Senior Data Scientist with extensive experience in machine learning and big data technologies. He has a strong academic background, including a Ph.D. from the University of Manitoba, and has worked in various research and engineering roles across multiple organizations.
Work at Verint
Hamed Janani has been employed at Verint as a Senior Data Scientist since 2020. In this role, he applies his extensive knowledge in data science and machine learning to develop solutions that enhance data analysis capabilities. His focus includes building big data pipelines and deploying machine learning models, contributing to the company's objectives in data-driven decision-making.
Education and Expertise
Hamed Janani holds a Ph.D. in Machine Learning from the University of Manitoba, where he studied from 2012 to 2016. He also completed a Post-doctoral Research Fellowship in Statistical Machine Learning at the same institution from 2016 to 2017. Prior to that, he earned a Master's degree from Amirkabir University of Technology - Tehran Polytechnic, achieving a GPA of 3.9/4. His educational background equips him with advanced skills in deep learning techniques and statistical analysis.
Background
Before joining Verint, Hamed Janani worked as a Machine Learning Researcher at the University of Manitoba from 2012 to 2016. He later served as a Machine Learning Postdoctoral Researcher in the Complex Analysis Research Lab for one year. Additionally, he was employed at Powertech Labs Inc. as an Engineer/Researcher from 2017 to 2020. His diverse experiences in academia and industry have shaped his expertise in data science.
Technical Skills
Hamed Janani possesses advanced technical skills in various programming languages and technologies. He is proficient in Python, R, C++, TensorFlow, PyTorch, Matlab, SQL, and CQL. His expertise includes building big data pipelines using technologies such as Apache Kafka, Druid, Cassandra, and Spark. He also specializes in anomaly detection, segment/cluster analysis, and deploying machine learning models using Docker, Jenkins, and DCOS/AWS.
Research and Development
Hamed Janani has developed a strong foundation in deep learning techniques, including CNNs, RNNs, LSTMs, and GANs, with applications in computer vision and natural language processing (NLP). His experience encompasses time series analysis and pattern recognition, enabling him to tackle complex data challenges effectively. His research contributions have been instrumental in advancing the field of machine learning.