University of Illinois at Urbana-Champaign (UIUC)

Sharif University of Technology

AmirKabir University of Technology

Adjunct Assistant Professor University of Illinois at Urbana-Champaign

• I offer Cloud Computing and Big Data courses, delivered online through Coursera.org
• In My Cloud Computing Cpstone Course, I lead students' research projects in the areas of Cloud Computing and Distributed Systems

Founder Research and Engineering Frontier Labs

• I led the development of an industrial machinery failure prediction system for a major industrial customer, from ideation to deployment, assembling and managing the team to achieve the goal. We built a complete ML data science pipeline using Python and Pandas. The pipeline incorporates data cleaning, correlation, deductive logic for feature engineering, time-series analysis, historical knowledge embeddings, and training an XG-Boost ML model for prediction. We used HTML, CSS, Bootstrap, and a Grafana Dashboard to monitor the system's performance, and the product was successfully deployed in multiple factory settings.
• I conceptualized, led a team, and developed a tool to extract knowledge from PDF files, trained NLP models (RASA Engine), and deployed an NLP-based Chatbot with web frontend and microservice-based backend as a web service. The tool was deployed in the customer service organization, resulting in a 20% measured reduction in workload for the targeted product.
• I led and managed cross-functional teams of 5 to 9 people utilizing agile methodologies (Scrum), and helped the project by being hands-on in technical work.

Data Engineering Manager Capital One

• I developed a Cross-Data-Center Disaster Recovery (DR) solution for an HDFS-based Data Lake, resulting in risk reduction for the data lake and increased adoption by the company.
• I built an ML-based image recognition product that identifies credit cards in social media images, reducing the incidence of compromised credit card information. The development process included synthetic dataset generation, training image segmentation Deep Learning models, analyzing their performance and behavior, and conducting interpretability and explainability analysis using LIME. The model was deployed for inference using Python, Pytorch, and Keras.
• I led a team in developing an internal data science pipeline with similar capabilities to AWS Sagemaker, integrated with the internal Data Lake, Utilizing AWS services, CUDA, Tensorflow, Keras, and Python. The pipeline was widely adopted and used by many data analysts and scientists within the organization.
• I established joint research programs between Capital One and the University of Illinois (UIUC) faculty and the National Center for Supercomputing Application (NCSA), and then managed $600K+ research funds.
• I participated in a rapid cycle innovation model and team, resulting in hundreds of published patents from the Capital One Illinois Digital Campus Lab (iDCL). This work helped establish the lab as a premier research organization within and outside the company and helped the company grow its patent portfolio.
• I led teams from 3 to 8 people while at Capital One.

Senior Software Engineer Yahoo!

• I worked on core open-source Apache Storm, Hadoop and Spark frameworks on new features and issues.
• I developed a 'Resource-aware-scheduler' for Apache Storm, created a watchdog system for Apache ZooKeeper, and researched the Storm, Flink, and Spark Streaming performance co-authored and published each as a paper.
• I gained skills in Software Development Life Cycle, Clojure, Java, Scala, Test-Driven-Development (TDD), CICD with Jenkins, Git, and Linux.

Co-founder Accelerated Genomics

• I developed and patented a GPU-accelerated parallel gene sequence alignment algorithm (CUDA) and C during my postdoctoral research at the University of Illinois.
• I started this startup company to commercialize the product, and learned many aspects of entrepreneurship from this experience.

Research Assistant NEC Laboratories of America

• Developed a Distributed Programming Model and Framework: Partitioned Iterative Convergence, in JAVA
• I published this work as a conference paper, and then patented it. I then used it as the basis of my PhD thesis.

Intern StateFarm Research Center

• I developed and deployed the first proof of concept mobile application with bank/check OCR services in the insurance industry using the Cloud Computing model. I wrote the mobile application, using Objective C, to connect to a backend server through API calls, and the backend system performed the OCR work.
• The system has been integrated into the StateFarm mobile app and used in production

Intern NVIDIA

• I worked on functional chip verification for the Fermi architecture, specifically the Tessellation unit