Farhan Naqvi

- Improved system reliability by designing and implementing garbage collection (GC) logic in StargateService, including proactive mount-level failure detection and recovery under high-load conditions. - Enhanced interoperability by enabling external metadata parsing in a Go-based adapter using Protobuf extensions, within a constrained proto environment. - Built and maintained high-performance services in C++ with gRPC and Protocol Buffers, focusing on concurrent file operations, thread safety, and stress-te

- Developing and maintaining high-performance services using gRPC and C++, focusing on concurrent file operations with thread safety. - Implementing and optimizing stress testing to ensure system robustness under high-load scenarios.

- Lead anomaly detection efforts in structured workloads (Oracle, MySQL) by designing and applying advanced statistical techniques and machine learning models to monitor data ingestion, deletion, and modification at a granular level, identifying malicious spikes and ensuring data integrity. - Enhancing system performance and security through proactive outlier detection, optimizing machine learning models for anomaly identification, and collaborating with cross-functional teams to enforce robust data governa

Responsible for spearheading research initiatives aimed at advancing Indian Sign Language Recognition through cutting-edge video processing techniques and state-of-the-art Deep Learning models. Key responsibilities and accomplishments include: 1. Developed and implemented feature-based models, achieving a remarkable maximum accuracy of 99.71%, and keypoint-based models with a maximum accuracy of 95.61%. 2. Investigated and evaluated emerging architectures such as Video Vision Transformers, transfer learnin

Engaged in pioneering research at the forefront of stock market prediction utilizing advanced statistical methods, regression models, and time series forecasting techniques. Key contributions and achievements include: 1. Spearheaded the application of cutting-edge machine learning algorithms to develop predictive models for the stock market, resulting in actionable insights for investors and stakeholders. 2. Leveraged a diverse array of statistical methods and regression models to analyze market trends an

- Collaborated with industry professionals to build a recommendation system that makes personalized suggestions. - Created raw data from scratch using python depending on the features required for the model. - Implemented machine learning algorithms that would help cluster users depending on their historical data and similarity between them.

- Performed Exploratory Data Analysis using Tableau to find out meaningful insights from the interactive graphs that were created from the datasets. - Implemented Supervised and Unsupervised machine learning models, trained them on the data so that they can predict results with high accuracy on the unseen test data.

Specialization: Autonomous Systems Relevant Coursework: Foundations of AI · Machine Perception and Learning · Information Visualization and Analytics · Data Warehousing, Data Mining, and OLAP · Cloud Computing · Mobile Robotics

Successfully completed Honors in Data Science from PICT, alongside my undergraduate studies

Relevant Coursework: Data Structures and Algorithms, Cloud Computing, Object Oriented Programming, Database Management Systems, Advanced Database Management Systems, Machine Learning, Deep Learning, Operating Systems, Data Science and Big Data Analysis, Blockchain Technology, Engineering Mathematic