Arshia Ilaty

University of California, Irvine, 2024 - will be announced later :)

Doctor of Philosophy, Computer Science and Engineering

San Diego State University, 2024 - will be announced later :)

Doctor of Philosophy, Computational Science

University of Nevada, Reno, 2022 - 2023

Master of Science, Computer Science and Engineering

University of Tabriz, Iran, 2017 - 2021

Bachelor of Science, Computer Engineering

• Architected and managed a robust CI/CD pipeline using Kubernetes across bare-metal servers, AWS, and GCP, ensuring seamless deployment and high availability of microservices
• Developed critical software components in Rust and Haskell, focusing on advanced smart contract implementations, secure transaction processing, and distributed back-end services
• Optimized back-end infrastructure leveraging Redis, PostgreSQL, and other web2 technologies to enhance scalability, performance, and data integrity in decentralized environments
• Spearheaded the integration of blockchain technologies with cloud-based solutions, driving innovation in the development of decentralized applications and services
• Collaborate with the CBO and COO on business planning and marketing strategies to drive company objectives.
• Work closely with the Nevada Regional Manager to provision antennas, nodes, and other infrastructure components for network deployment.
• Partner with growth specialists to identify and acquire customers in the US market.
• Contribute to network engineering efforts, leveraging technical expertise to optimize network performance and scalability.
• Played a pivotal role as one of the earliest hires in the US, contributing to the establishment and expansion of operations and products in the region.

• Create Kubernetes applications and establish GF1 CI\CD pipeline and utilize Jenkins and Docker to build image/container, facilitating efficient deployment and automation of DevOps processes and enhancing development workflow and ensuring consistent application deployment
• Develop JFROG pipelines CI/CD solutions for DevOps automation, contributing to streamlined DevOps practices and enabling seamless automation across teams
• Design ignition pages, integrating them with databases to enhance user experience and data accessibility and reducing the number of clicks and automating data collection saves valuable time and minimizes errors and boosting team collaboration
• Proficiently design and executed ETL processes, harmonizing diverse data sources for accurate insights and facilitating data-driven decision-making.
• Automate and optimize the RTA (Repair Time Analysis) process, leading to improved efficiency and accuracy, while enhancing cross-team collaboration and informed decision-making
• Collaborate within a cross-functional team to track the impact of training initiatives on Mean Time to Repair (MTTR) measures and propose the exploration of Flux data to improve Maintenance KPI tracking

• Administered and performed troubleshooting for desktop computer operating systems
• Configured and implemented network infrastructure including routers, switches, wireless APs and controllers, and installed equipment, patching, Ethernet and fiber optic cabling

• Developed a comprehensive evaluation framework for synthetic healthcare data across diverse dimensions: bias and fairness, diversity, quality, privacy, and machine learning (ML) usability, ensuring robust performance across metrics
• Conducted empirical evaluations using GANs, Auto-variational encoder, diffusion-based models, Recurrent neural network, and transformer-based models for synthetic data generation

• Program and develop novel Android/IOS application in the Flutter platform for high-resolution imaging in open-pit mines using drones GitHub Link
• Use socket programming to build and release a mobile application to localize people during a disaster in order to guide them to a safety zone
• Develop a database schema and integrated it with the API server using MongoDB for data storage
• Collaborate with the UI/UX designer and bridge the gap between UI/UX design and technical implementation

• Conducted in-depth data analysis, utilizing data wrangling, cleaning, and manipulation techniques to generate meaningful insights
• Created visually compelling data visualizations using Tableau and Matplotlib to communicate research findings to stakeholders and team members
• Researched and gained a deep understanding of data modeling and data warehousing concepts and explored cutting-edge big data technologies such as Hadoop and Spark
• Utilized version control systems such as Git to effectively collaborate with team members and maintain organization and accuracy in research projects

San Diego State University

• CS 150 - Introductory Computer Programming (JAVA) - Fall 2024 - 4 Sections (Over 100 Students)
• CS 160 - Intermediate Computer Programming - Fall 2024

University of Nevada, Reno College of Engineering

• CPE 201 - Digital Design - Fall 2023 - 3 Sections (Over 75 Students)
• CS 447-677 - Analysis of Algorithms - Fall 20222 and Spring 2023 - Over 120 Students (Core Course)

University of Tabriz, Iran

• Computer Communication Networks
• Computer Networks Lab

• Programming Languages: Python, C/C++, Flutter (Dart), Java, Go, HTML + CSS, SQL
• Tools: Git, Github, Weka, RapidMiner, Webflow, Redis, MongoDB, SQL Server, MySQL, Hive, Airflow, Docker, Kubernetes, NGINX, Load Balancers, Tableau, Power BI, Pandas, Matplotlib, NumPy, Scrapy and BeautifulSoup, Scapy, SciPy, Scikit-Learn, TensorFlow, PyTorch, Hadoop, Spark, Kafka, Bazel, Buck, Superset, Pig, Iceberg, OpenNLP, NiFi, SQLAlchemy, Google Tag/AB Testing
• Cloud: AWS (S3, EC2, RDS, DynamoDB, CloudFront), Azure, GCP

• [2024] Presidential Research Fellowship (UCI/SDSU)
• [2023] Outstanding International Graduate Student Scholarship
• [2023] WAAIME Scholarship winner
• [2023] Graduate Students Association Travel Award
• [2017] Ranked within the top 1% among more than 295.000 students in the nationwide university entrance exam for B.S degree

COVID-19 Prediction using Machine Learning

I developed a machine learning-based prediction model for COVID-19 using the Johns Hopkins University Center for Systems Science and Engineering dataset. Using Python and deep learning techniques such as RNN and LSTM, I built a prediction model that could forecast the number of COVID-19 cases, deaths, and recoveries for different regions around the world GitHub Link

Twitter Watch

Built a system that tracks tweets and replies of some specific accounts from a specific date onwards and extracts some information. I used REST APIs to provide information about the accounts, including the conversation threads, active audiences, and sentiment analysis

Telco Customer Churn (IBM)

Executed end-to-end machine learning on the Telco Customer Churn dataset, involving data cleaning, visualization, and categorical-to-numeric transformation. Assessed six machine learning algorithms, optimizing the Gradient Boosting Classifier for an 80% accuracy, 6% higher than the baseline. Emphasized the iterative nature of the process, adapting to evolving problem dynamics.

Spearheaded the design and implementation of a comprehensive Fake News Detection System

Utilizing machine learning techniques and social network analysis to assess the credibility of media posts on social media platforms. Developed modules for text analysis, URL consistency checks, and network analysis, enhancing the system's ability to identify and mitigate the spread of misinformation.

More

Implemented Time Series Data analysis using recurrent neural networks (RNNs) in both PyTorch and TensorFlow frameworks. Explored patterns like seasonality and cycles present in time series data, vital in fields like finance, economics, and weather forecasting. Utilized TensorFlow's tf.keras.layers.RNN API, employing various RNN cell types (Basic RNN, LSTM, GRU) for sequential data analysis. Demonstrated stock price prediction using Google Colaboratory, showcasing real-time series data analysis.

Developed an AutoEncoder-based anomaly detection model for Google Ads time-series data, minimizing downtime. Established role-based alerts for on-call engineers to enhance response efficiency.

Developed and implemented a machine learning solution to detect and flag potential bot accounts on social media platforms, addressing deep class imbalance through oversampling and intelligent batching strategies, and evaluating model performance based on metrics such as accuracy, false positives, false negatives, and fairness across groups.

• Data Analysis with Python
• Google Data Analytics Capstone: Complete a Case Study
• Text Mining and Analytics
• Data Visualization with Python

• Cisco Certified Network Associate (CCNA)
• Cisco Certified Network Professional (CCNP)

• MikroTik Certified Network Associate (MTCNA)
• MikroTik Certified Routing Engineer (MTCRE)
• MikroTik Certified Traffic Control Engineer (MTCTCE)
• MikroTik Certified User Management Engineer (MTCUME)
• MikroTik Certified Wireless Engineer (MTCWE)
• MikroTik Certified IPv6 Engineer (MTCIPv6E)

• Member of Aztec Robotics
• Member of the SDSU ACM Club
• Member of SIAM (Society for Industrial and Applied Mathematics)
• Member of SDSU AI CLUB - SDSU
• Member of the Society for Mining, Metallurgy, and Exploration(SME)
• President of the Mountaineering Club
• Treasurer of the Iranian Association Club
• Member of the Cybersecurity Club
• Member of the UNR ACM Club
• Member of the UNR 3D Printing Club
• Member of the John Mackay Club
• Member of the International Student Organization
• Member of the UNR Tennis Club

• 1. Researcher at Oregon State University under Dr. Bahman Abbasi's Supervision
  • Gain hands-on research experience in model predictive controls and machine learning within thermal fluids sciences.
  • Explore the mathematical foundations of machine learning approaches and contribute to optimizing algorithm performance parameters.
• 2. Voluntarily contribute as a Data Collector for the Human-Computer Interaction Lab
• 3. Serve as a Nevada Undergraduate Research Award (NURA) Reviewer, applying criteria aligned with NSF rubrics to rigorously evaluate research proposals, assess project viability, and allocate funding to innovative research endeavors, ensuring impactful contributions to academic and scientific advancements

• Computational Science Research Center (CSRC) at San Diego State University (SDSU)

• Farama-Foundation/Gymnasium