Alireza Davoudi

General AIOps • Developing algorithms to detect anomalies in Time Series • Developed a library to query SQL databases with a PromQL like language using Python and LARK Parser (https://github.com/adavoudi/PromSQL) Scientific Knowledge Graph: • Extracting and classifying entities relations from natural text using a rule-based method • Performing graph analytics such as Link Prediction, Node Similarity (using embeddings), and Shortest Path using Neo4j

• Developed a framework to model Bayesian Networks for anomaly detection (https://github.com/adavoudi/bayesnet) • Developed several algorithms to detect time series anomalies using Linear models for Spatial Anomalies in multidimensional time series and Facebook Prophet for Temporal Anomalies • Developed a data ingestion pipeline to gather, transform and store all the data in the software data lake (using Python, Kafka, InfluxDB) • Developed Backend GraphQL API using Django and Graphene

• Developed an image tagging model for the images that clients upload on the company's public platform using PyTorch • Optimized the model to run on CPU using Knowledge Distillation

• Implemented a framework for surveillance camera monitoring. The pipeline included a video management system (using python, FFMpeg, MongoDB), an Object Detection and Tracking System (using Tensorflow, Tensorflow Serving, Kafka, Python), a complex event processing system (using apache Flink and python), and finally an alerting system.