Hey there I engineer the software solutions

• MS in Data Science
  Information Technology University Lahore

• BS in Computer Science
  Government College University Lahore

• Languages: JavaScript, TypeScript, SQL, Python, Java
• Frameworks: Node, Express, React
• Technologies: AWS, Docker, GraphQL
• Databases: MySQL, Postgres, MongoDB, DynamoDB, Apache Cassandra

• Development Tools & IDEs: VS Code
• DevOps: Docker, Jenkins, GitHub Actions
• Cloud Platforms: AWS (Lambda, EC2, ECR, S3, DynamoDB, API Gateway)
• Version Control: Git, GitHub, Bitbucket
• Project Management: Jira, Asana
• Web Servers: Nginx
• Monitoring: Newrelic, CloudWatch
• Other: Sonar, Memcache

• Data Engineer Certificate | Mangtas 2023
• Machine Learning, Data Science, and Deep Learning with Python | Udemy 2022

Master's Thesis: Automated Pest Detection in Crops using Deep Learning

• Abstract:
  Crops are a vital part of the economy and livelihood, making crop protection crucial. In this research, we explored the application of deep learning techniques for automating the detection of pests in crops. Using the IP102 dataset and ensemble pre-trained deep CNN models, we developed a weighted ensemble technique with learnable parameters. Additionally, we utilized pretrained vision transformers to classify stem rust, leaf rust, and healthy wheat from a small dataset sourced from the ICLR challenge. Through experimentation with CNN architectures and ViT models, we demonstrated the effectiveness of large-scale pretrained vision transformers on small datasets, outperforming state-of-the-art CNN architectures. Our research highlights the importance of leveraging pretrained models and the transferability of features learned from ImageNet21 in agricultural applications.

• Key Contributions

  • Developed a weighted ensemble technique with learnable parameters for pest detection.
  • Demonstrated the effectiveness of pretrained vision transformers on small agricultural datasets.
  • Achieved competitive performance in the ICLR challenge through the use of ViT models pretrained on ImageNet21.

• Learnings

  • Pretrained vision transformers are effective for small datasets in agricultural contexts.
  • Features learned from ImageNet21 are transferable to diverse datasets, such as wheat plant images.

stealth25519 Python Package

• Description:
  The Stealth25519 Python package provides functionality for the generation, verification, and signing of stealth addresses using the standard ed25519 algorithm with the ECDH protocol.

• Features

  • The sender can generate a stealth address using the public view and spend key of the recipient.
  • The recipient can use their public spend key and private view key to identify transactions intended for them.
  • The recipient can sign transactions for all transactions that belong to them.
  • The signature generated by the recipient can be verified by anyone with the stealth address public key.

• Code Example

  from stealth25519.generator import StealthAddressGenerator
  
  public_spend_key_bytes = bytes.fromhex('18a498c68461e39dd180745e5aa1faacbc9b8a5f74a7eb25b5038b66db0a4af6')
  public_view_key_bytes = bytes.fromhex('b52c33b513c26e17b7105cb1ed1c7022ef00f3967aaac0ff8bd9d15ccee4d94e')
  
  public_spend_key = PublicKey(public_spend_key_bytes)
  public_view_key = PublicKey(public_view_key_bytes)
  
  generator = StealthAddressGenerator(public_spend_key, public_view_key, hash_function = sha512)
  stealth_address = generator.generate()
  print('Stealth Address\n', stealth_address)

• Documentation: stealth25519

• Source code: stealth-py

• Description
  Nitro is a metaverse game project integrating blockchain technology. It features a Node.js backend with TypeScript and DynamoDB for data storage. The frontend is developed using React.js, and deployment is managed using Docker containers on AWS EC2 instances and Lambda functions.

• Role and Responsibilities
  As the lead software engineer, my responsibilities included designing the backend architecture, implementing new features, and providing support for existing features.

• Challenges Faced

  1. Slow performance due to poor queries of DynamoDB.
  2. Poor performance of asset retrieval from the blockchain.

• Solutions Implemented

  1. Implemented query optimization techniques and indexing to improve DynamoDB performance.
  2. Implemented Redis cache to store frequently accessed assets and implemented asset refreshing to fetch the latest assets if not already cached.

• site

• Description
  TechPurview is a society management system built with a Node.js backend and PostgreSQL database. The frontend is developed using Next.js, and the application is deployed on AWS EC2 instances using Docker containers.enhancements.

• Role and Responsibilities
  As the lead software engineer, my responsibilities included architecting the backend infrastructure, implementing database connectivity, and coordinating with the frontend team for UI/UX enhancements.

• Challenges Faced
  Managing multiple connections to the database, leading to potential performance issues and resource wastage.

• Solutions Implemented
  Implemented the singleton design pattern to ensure that only one instance of the database connection is initiated and served for all requests. This optimized resource usage and improved overall system performance.

• site

• Description
  Tossdown is a multivendor ecommerce engine developed using Node.js, CodeIgniter (PHP framework), and MySQL database. The backend is primarily implemented in Node.js, while certain functionalities are handled by serverless Lambda functions.

• Role and Responsibilities
  As a senior software engineer on the Tossdown project, my responsibilities included optimizing performance, analyzing database queries, and implementing search functionalities.

• Challenges Faced

  1. Slow performance of certain endpoints, impacting user experience and system efficiency.
  2. Redundant search results affecting search accuracy and relevance.

• Solutions Implemented

  1. Identified endpoints with poor performance and analyzed database queries and code execution. Optimized MySQL queries using the "EXPLAIN" keyword to identify bottlenecks and removed unnecessary iterations to improve query efficiency.
  2. Implemented a solution to periodically move data from MySQL to Elasticsearch, ensuring that product data is indexed and searchable with full-text search capabilities. This approach improved search accuracy and reduced redundant search results.

• site

• Description
  Alpolink is a platform for selling exam dumps, developed using PHP and the CodeIgniter framework, with MySQL as the database management system.

• Role and Responsibilities
  As a senior software engineer for Alpolink, my responsibilities included addressing architectural challenges and optimizing system performance.

• Challenges Faced
  Architectural issue: Each website had its own frontend and database instance, leading to complexities in managing and maintaining multiple codebases and databases.

• Solutions Implemented
  Implemented a unified backend architecture where a single backend serves multiple websites. This approach reduced complexity by consolidating codebases and databases, allowing for easier maintenance and scalability. Each site is now served by the same backend, streamlining operations and improving efficiency.

• site

• Description
  Aanganpk is a multivendor ecommerce platform specializing in Pakistani women's handcrafted items. The platform is built using WordPress with WooCommerce plugin, leveraging PHP for customizations and extensions.

• Role and Responsibilities
  As a senior software engineer for Aanganpk, my responsibilities included addressing platform limitations and customizing functionalities to meet business requirements.

• Challenges Faced
  Lack of reporting capabilities from the WooCommerce WordPress plugin, hindering the organization's ability to generate essential reports for business analysis and decision-making.

• Solutions Implemented
  Updated the WooCommerce plugin code to retrieve and generate custom reports tailored to the organization's specific needs. This involved modifying the plugin codebase to extract and present relevant data in a format conducive to business insights and analysis.

• site

• Description
  The Information Retrieval System is designed to retrieve relevant documents from a corpora using machine learning techniques. It utilizes Support Vector Machine (SVM) algorithms for classification and is implemented in Python within Jupyter Notebook environment. Data is stored and managed in a Cassandra database.

• Role and Responsibilities
  As the sole architect and developer of the Information Retrieval System, I assumed complete ownership of all project aspects. My role involved the design and implementation of sophisticated machine learning algorithms tailored for document classification and retrieval. This project epitomizes my capacity to conceive, execute, and refine complex technical solutions independently.

• Challenges Faced
  Document and query indexing posed significant challenges in organizing and efficiently retrieving information from the corpora.

• Solutions Implemented
  Implemented the TF-IDF (Term Frequency-Inverse Document Frequency) algorithm for document and query indexing. This approach simplified the indexing process while improving retrieval effectiveness. The system achieved better evaluation metrics in terms of precision and recall, ensuring more accurate document retrieval.

• Description
  The Clause Generation project focuses on generating legal clauses using advanced natural language processing techniques. It leverages Large Language Models (LLMs), prompt engineering methodologies, and the Hugging Face library for model training and inference. Quantization techniques are employed for model optimization, with GPU acceleration for faster computation. The project also utilizes Llama and Falcon frameworks for specific functionalities.

• Role and Responsibilities
  As a senior software engineer for the Clause Generation project, my responsibilities included implementing and optimizing the clause generation pipeline, model training, and evaluation.

• Challenges Faced
  The LLMs utilized in the project were too large to fit in the available GPU memory, posing challenges in model training and inference.

• Solutions Implemented
  To address the GPU memory limitations, we conducted testing using EC2 g5.2xlarge instances, which provided sufficient resources for model training and inference. Additionally, for local development and testing, we implemented quantization techniques to optimize model size and memory usage. This allowed us to generate outputs using quantized LLMs and evaluate them based on syntax and semantic similarity metrics.

• Description
  Stealth Addresses is a cryptographic project focused on generating secure and private addresses for transactions. It utilizes the x25519 algorithm for shared secret generation and the ed25519 algorithm for signature generation and verification.

• Role and Responsibilities
  As the sole proprietor and developer of the Stealth Address Library project, I assumed full ownership and accountability throughout its lifecycle. Responsibilities encompassed every aspect, from conceptualization and design to implementation and refinement. This project epitomizes my capacity to initiate, execute, and deliver complex technical initiatives independently.

• Challenges Faced
  Integrating the x25519 and ed25519 algorithms posed challenges due to their different purposes and implementations.

• Solutions Implemented
  Implemented an initial stealth address generation mechanism using the shared secret methodology of x25519. Then, instead of using standard libraries for ed25519, a custom core implementation was developed based on RFC8032 specifications. Mathematics and cryptographic principles were utilized to generate stealth addresses seamlessly using the ed25519 algorithm, ensuring compatibility and security.

• Description
  Products Pair is a system designed to predict the probability of items being sold together. The Apriori algorithm is utilized to calculate these probabilities based on transactional data.

• Role and Responsibilities
  As a senior software engineer for the Products Pair project, my responsibilities included designing and implementing the predictive algorithm and optimizing system performance.

• Challenges Faced
  Implementing the Apriori algorithm was successful, but retrieving probabilities of product pairs from the transactional database each time resulted in high latency, impacting system performance.

• Solutions Implemented
  Implemented a solution to periodically update data in a denormalized data store from the transactional database (MySQL). This denormalized data store contains pre-calculated probabilities of product pairs. By querying this denormalized database, the system achieves significantly lower latency, ensuring smooth and efficient operation.

• Description
  The Reporting System is designed to generate multitenant reports using data cubes and slices. It provides insights into various dimensions such as time, product, category, branch, and brand, catering to the diverse reporting needs of hundreds of clients. Reports can be saved and they're continuesly updated.

• Role and Responsibilities
  As a senior software engineer for the Reporting System project, my responsibilities included designing and implementing the reporting functionalities, ensuring scalability and efficiency.

• Challenges Faced
  Making reports generic for hundreds of clients posed a significant challenge, especially in calculating dimensions from transactional data for each client.

• Solutions Implemented
  Implemented a solution to calculate dimensions for data cubes (e.g., time, product, category, branch, and brand) from transactional data. These dimensions are then pre-calculated and stored in cache (e.g., Memcached) for efficient retrieval. This approach significantly reduced the computational overhead and time required for generating reports, ensuring scalability and responsiveness.

• Description
  KidSafe is an application designed to provide a safe environment for children to watch YouTube videos. It utilizes the YouTube API to curate a selection of kid-friendly content.

• Role and Responsibilities
  As a senior software engineer for the KidSafe project, my responsibilities included implementing features, integrating APIs, and ensuring child safety and usability.

• Challenges Faced
  Initially, the app was designed to allow parents to manually select videos for their children, but this approach proved cumbersome. Integrating functionality to automatically include all videos from a YouTube channel posed a challenge, as the YouTube API does not provide direct access to fetch videos by channel name.

• Solutions Implemented
  Developed a Python service to overcome the challenge by utilizing web scraping techniques with Beautiful Soup to fetch the YouTube channel ID using the channel name. Once the channel ID was obtained, the YouTube API was invoked recursively to fetch all videos associated with the channel. This solution provided a seamless way to include all videos from a specified YouTube channel in the KidSafe app, enhancing user experience and content accessibility for parents and children.

• Description
  The Notifications Service is designed to deliver up to 1,000 notifications per minute efficiently. It utilizes Firebase Cloud Messaging (FCM) for message delivery, Cassandra for data storage, and supports features such as retry mechanisms and recurring/one-time notifications.

• Role and Responsibilities
  As a senior software engineer for the Notifications Service project, my responsibilities included architecting the system, optimizing performance, and ensuring reliable delivery of notifications.

• Challenges Faced
  The partition key was set as the job_id, and the sort key was the next notification trigger time. However, the presence of the same next notification trigger time in multiple partitions led to slower query performance, as queries for next jobs to be executed were scanned across all partitions.

• Solutions Implemented
  To address the query performance issue, we redesigned the data model by setting the next notification timestamp as the partition key and the job_id as the sort key. This ensured that all notifications scheduled for the same time would be stored within the same partition. As a result, querying for next notifications to be triggered became more efficient, improving overall system performance and reducing latency.

• Description
  The Google Map Scraper is a tool designed to extract information about stores from Google Maps based on location and store type. It is built using Python, with Beautiful Soup and Selenium utilized for web scraping.

• Role and Responsibilities
  As the sole creator and developer of the Google Map Scraper, I orchestrated all facets of the project, from conceptualization to implementation. My responsibilities encompassed designing the scraping process, integrating essential web scraping libraries, and fine-tuning data extraction mechanisms. This project underscores my adeptness in independently driving and delivering complex technical solutions.

• Challenges Faced
  The dynamic rendering of Google Maps posed challenges for web scraping, as Beautiful Soup could not access dynamically loaded content.

• Solutions Implemented
  To overcome the limitation of Beautiful Soup, Selenium was employed to open a browser and wait for the complete rendering of the Google Maps webpage. Once the page was fully loaded, metadata for the stores (such as location and store type) was extracted using Selenium. Subsequently, Beautiful Soup was utilized to iterate through the metadata and extract detailed information for each store, including address, star ratings, phone numbers, and photos. This combined approach ensured comprehensive data extraction from Google Maps despite the dynamic rendering challenges.