Pezhman Sheini
Data Scientist
Talent
McLean, FairfaxMember since September 19, 2023
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About
I am a research professional with a Ph.D. in Computer Science, specializing in NLP. My expertise includes anomaly detection, complex log analytics, large language models, security algorithms, and data privacy. Additionally, I am experienced in predictive and prescriptive analysis, pattern detection, and trend analytics.
Throughout my previous roles, I successfully implemented traditional machine learning and deep learning solutions from scratch. Currently, I am seeking opportunities as a data scientist, leveraging my unique blend of technical expertise, analytical skills, and strategic thinking to deliver results and achieve business objectives.
Experience
ArcSight, Micro Focus/OpenText Apr 2022– May 2023Data Scientist for Cybersecurity Research 40 Hours/Week
- Submitted a patent (pending) for automating the preprocessing of complex logs
- Developed a comprehensive data preparation process, including log parsing, ETL, and feature extraction and selection techniques
- Successfully implemented and deployed machine learning and deep learning solutions for log analysis and anomaly detection tools, significantly improving the decision-making process of ArcSight's support team. Implementation of these tools has resulted in a significant reduction in investigation time, and enhanced operational efficiency by an order of magnitude
- Prepared presentation materials and formal business case documents for senior management, effectively promoted findings and driving science-based decision support recommendations derived from the successful implementation and deployment of machine learning and deep learning solutions for log analysis and anomaly detection tools
- Characterized hostnames and built a model to compute a risk score for each hostname. When utilizing this score to predict malicious hostnames, we achieved a 30% reduction in false positives and improved the overall accuracy greater than 27% compared to the legacy approach
- Skills: Exploratory Data Analysis, Anomaly detection, LLM, Transformer, Generative AI (OpenAI), Pattern detection, Event prediction, MLFlow, AI/ML development lifecycle, Vertica, Statistical modeling, Documentation
- Led the research and development efforts for pathogen surveillance software on persistent memory (Optane) in collaboration with Intel Corp and Columbia University
- Conducted a comprehensive analysis of traditional techniques for pathogen surveillance and identified trends to optimize strategies
- Developed a groundbreaking approach for DNA representation using image representation of DNA sequences, Self-supervised Learning (SSL), and information retrieval trajectories
- Implemented a novel k-mismatch similarity search by designing and implementing a hamming weight tree data structure
- Skills: Data Structures, Big Data, AWS, Computer vision, Self-Supervised Learning, Variational Autoencoder, ETL, Debugging, CI/CD, TensorFlow, MLOps, Spark, Classification, Information Retrieval, Data Visualization
- Designed and developed a novel approach to generate multilingual word embeddings using universal concepts and graph theories – PhD Dissertation
- Designed and developed sentiment analysis, information retrieval, and text classification applications that utilize multilingual word embeddings
- Contributed training resources (including quality assurance guidelines) for undergraduates and assisted the PI with data analysis and publications
- Skills: Artificial Intelligence, Natural Language Processing (NLP), Social media data analysis, User modeling, XLNET, TensorFlow, Sentiment Analysis, Information Retrieval, Social Media Event Detection, Quantitative Modeling, BERT, Web Scrappers, ML Algorithms, Predictive Analysis, Language Modeling, Transfer Learning
- UA - Social Media Data Analytics, grading weekly projects in Python-Java
- UA - Intro to the Internet (HTML) – 16 hour per week + grading (280 students)
- UA - Cloud Computing – substitute lecturer, exam supervisor
- UA - Database Management Systems
- Designed, implemented, and consulted the company employees about “Disaster Recovery Procedures and Protocols” for “The Data Center”
- Performed full spectrum CNO.
Assessed cyber security vulnerabilities (CNA & CNE) and implemented a mitigation solution (CND) tailored for the company’s goals and objectives
- Provided technology planning, design, and administration for “The Data Center” and its network infrastructure
- Supported more than 40 remote web servers
- Identified the requirements and implemented the most efficient and cost-effective solutions for the resilient network system
- Implemented research objectives, provided research support, and mentored undergraduates
- Skills: Cloud Architecture, OpenStack, Hypervisors, Linux, Bash, Cyber Security, Network/Cloud Security, Cyber-attacks, DDoS Attacks
Education
The University of Alabama, College of Engineering - Tuscaloosa, AL 35487 Aug 2016 – Aug 2020Ph.D. of Computer Science GPA: 3.9/4.0
- Dissertation titled “Multilingual Word Embeddings with Universal Concepts and their Applications.”
- Other related research: Cyber Security (e.g., DDoS attacks Mitigations)
- Courses: Robotics, Software Development and Testing, Web Applications and Databases, Algorithms and Data Structures, Compilers and Operating Systems, Adv.
Computer
Communication & Networks, Computer Security, Cryptography & Data Security
Master of Science GPA: 3.6/4.0
- Thesis titled “Performance Impact of DDoS Attacks on Three Virtual Machine Hypervisors”
- Other related research: Cloud Security and Attack Strategies
Bachelor of Engineering
- Major: Computer Engineering Hardware
- Capstone Project: Implementing follow liner robots
- Courses: Introduction to Software Engineering, Computer Organization, Applied Algorithms for Engineering, Microprocessors, Probability Theory, Systems Programming, Control Systems, Microcomputer Architecture
