Stanly Halder

Hi, I'm Stanly Halder.

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Self-driven, quick starter, passionate programmer with a curious mind who enjoys solving a complex and challenging real-world problems.I am a computer science and engineering student with a love for finance and travel. When I'm not in the classroom, you can find me trading on the forex market and constantly seeking new challenges. But my interests go beyond just tech and finance - I'm a voracious reader and love to learn about a variety of topics. Join me on my journey as I share my insights, experiences, and adventures with the world.

About

I am a highly ambitious and driven computer science and engineering student at the Canadian University of Bangladesh. I enjoy problem-solving and coding. Always strive to bring 100% to the work I do. I have worked on technologies like Python, Django, Flask, MySQL, MongoDB, HTML5, CSS, Java, C/C++ during my bachelor's. I have 19 months of professional work experience which helped me strengthen my experience in Python, Flask, and Django. I am passionate about developing complex applications that solve real-world problems impacting millions of users.

Languages: Python, Java, JavaScript, C, C++, HTML/CSS, Bash
Databases: MySQL, MongoDB
Libraries: NumPy, Pandas, OpenCV, BacktestingPy
Frameworks: Flask, Django, Node.js, TensorFlow, PyTorch, Bootstrap
Tools & Technologies: Git, Docker, Scene Builder, Pine Script

Looking for an opportunity to work in a challenging position combining my skills in Software Engineering, which provides professional development, interesting experiences and personal growth.

Experience

Zhiffy

Software Engineer

Developed and managed the backend of an e-commerce platform using Flask, MongoDB, and AWS.
Worked on three web applications targeting customers, selling vendors, and admin users; built 50+ RESTful APIs with functionalities such as login/sign up, view a product, add a product to cart, checkout the order, etc.
Improved the response time by 20% by refactoring the codebase and changing database design and queries.
Added a bulk upload feature which reduced the manual work of adding products into a database.
Tools: Python, Flask, MongoDB

July 2020 - Nov 2020 | Hyderabad, India

Meditab

Programmer Analyst

Customized a tree-based optimization algorithm that separates drugs into distinct groups to maximize the concurrent execution of drug dispenser robots; improved an optimization algorithm that reduced the cycle-time of the automation process by 25%.
Devised a customized recursion algorithm to extend the functionality of the current environment to a multi-robot and multi-system environment
Built a modular video analytics app using Flask, OpenCV that tracks the location of each human in a multi-camera environment; utilized perspective transformation, object detection, and object tracking to find the location of a human.
Increased the speed of the video analytics app by 20% by using a customized YOLOv3 algorithm to perform object detection and DeepSORT algorithm for multi-object tracking.
Tools: Python, Flask, OpenCV, Keras, Tensorflow, PyTorch

Dec 2018 - July 2019 | Ahmedabad, India

Mtag Innovations

Software Developer

Programmed a cloud-based web app using Flask and JavaScript aimed at storing, visualizing, and tracking temperature and humidity of each drug container to estimate the degradation of the drug.
Created an alert system to send notifications and emails when the parameters exceed the threshold.
Tools: Python, Flask, JavaScript

July 2018 - Nov 2018 | Ahmedabad, India

CIGNEX Datamatics

Project Trainee

Designed a library management system for a local library, where we undertook activities like requirement elicitation, preparing Data Flow and Entity-Relationship diagrams.
Delivered a solution for a POC involving Automatic Financial Document Classifier using Natural Language Processing and Support Vector Machines with 96% accuracy on the company’s data.
Tools: Python, Scikit-learn, NLTK

June 2017 - July 2017 | Ahmedabad, India

Projects

                
Music Player Web-App
                  A music streaming web app based on Django
                
AccomplishmentsTools: Django, HTML, CSS, Bootstrap, SQLite, AWS S3, Heroku
Register/login to the web app(with OAuth-based Google Sign-In).
Search and filter songs based on language and singer.
Create multiple playlists and add/remove songs to/from playlist.
Scroll through recently played/viewed songs.

Quiz Web-App
                  A quiz playing web app based on Django
                
AccomplishmentsTools: Django, HTML, CSS, Bootstrap, SQLite, Heroku
Register/login to the web app(with OAuth-based Google Sign-In).
Play Quiz and see the leaderboard

Blog Web-App
                  A simple and extensible blog web-app based on Flask.
                
AccomplishmentsTools: HTML, CSS, Bootstrap, Flask, SQLAlchemy, Postgresql, Python
Users can view posts and contact the admin via Contact Page.
Admin can Add, Delete, Update posts.

Visual Question Answering
                  An attention-based classification model that aims at generating an answer for a given input image.
                
AccomplishmentsIncorporated Convolution Neural Networks (CNN) for extracting image features and Long Short Term
                    Memory for extracting question
                    embeddings.
Tested the model on the COCO dataset, abstract scenes images, and got 69% overall accuracy on the
                    VQA evaluation metric.

Video Summarizer
                  A Seq2Seq model that generates a short summary of the given input video.
                
AccomplishmentsIncorporated CNN to detect and classify objects in the video frames and Long Short Term Memory for
                    generating a summary.
Evaluated the model on MSVD (Microsoft Video Description Corpus) dataset; achieved 0.77, 0.71,
                    0.52 scores respectively on ROGUE,
                    BLEU, METEOR evaluation metrics.

Image Generator
                  An image generator based on the concept of adversarial networks (GANs)
                
AccomplishmentsDeveloped system was tested on a human-face database and loss was calculated by comparing the PCAs
                    of generated and original image.
Calculated difference in PCA was less than 10%, depicting the successful generation of an image by
                    the generator.