• Engineered intricate SQL queries, seamlessly integrated with .NET, enhancing user mapping efficiency and saving hours of development work.
• Implemented Entity Framework, LINQ, Dapper to streamline data retrieval, ensuring efficient querying and seamless SQL database interaction.
• Created a POC for Kafka pipeline for seamless client-to-development data transfer, improving data synchro- nization and collaboration.
• Technologies used: Asp.NET, Entity Framework, LINQ, MySQL, Dapper, Azure Function, Kafka
• Achievement of better Artificial Intelligence Model on Chat-bot Industry in Nepal after researching almost a year
• Contributed on development of SaaS platform of chat-bot, resulting on 10+ clients
• Deployed by many big companies of Nepal like Nepal Telecom (Biggest Telecom Company in Nepal) and many more
• Contributed Technologies: Sanic, React.js, MongoDB, REST API, Natural Language Processing
• Organized an event i.e Make In Nepal
• Presented Robots at the event with different ideas and protoype for preventing crimes
• Met and discussed about Robotics and AI (Future of Man Kind) with Hon'ble Prime Minster Of Nepal
• Conducted hiring of new interns
• Managed finances of the company
• Conducted client outreach; pitched projects to new clients
• Took lead in projects
• Innovative software solution implemented in Asp.NET for Microfinance operations.
• Orchestrated a comprehensive suite of transactional functionalities, adeptly encompassing client onboarding.
• Coded semaphore locking mechanisms to establish data integrity, data consistencies during pivotal transactions.
• Technologies used: .NET 6.0, Entity Framework, LINQ ,SQL Server, Docker, Kubernetes.
• Created a dynamic webiste for visa consulting company aka Visa Alliance
• Technologies: Python, Django, HTML5, CSS3, JavaScript, AWS Lightsail
• Came in under budget for the client and completed the work well before the deadline
• Features:
1. Signup/Login, Email notification
2. Dashboard for each users
3. Website contents are dynamic i.e changable
4. Blogs section
• E-commerece website where users can order products
• Features
1. Singup/Login, Email notification
2. Dashboard of each users, change thier profile information, can view past order
3. Admin can add/edit/delete products details
4. Appointment system
5. Downloadable bill
• Created a mobile app using flutter that connects different ethnic groups
• Created a encoder-decoder network for language translation and GRU, attention models for effectiveness.
• Implemented YOLO for object detection
• Used ngrok and stored URL in firebase
• Technologies: Python, Dart, Flutter, CNN, Computer Vision, YOLO, Tesseract OCR, NLP, RNNs.
• Developed a mobile application using flutter for Attendance marking purpose using mobile bluetooth
• Separate interface and database was created for Teacher and Student using Firebase
• Technologies: Flutter, Dart, Firebase
• Developed a Machine Learning based model that detects deases based on provided symptoms.
• Technologies: Python, Machine Learning, Naive-Bayes, Tkinter
• Developed a mobile app that sends an alert notification to people within certain radius at once.
• Firebase was used to store user's data.
• We managed to early predict the occurrence of fire using Deep Learning.
• Won in National Level and selected for Global Nominees.
• Technologies: Python3, Dart, Flutter, Firebase Computer Vision, ResNet50
• Created a mobile app using flutter that connects different ethnic groups
• Created a encoder-decoder network for language translation and GRU, attention models for effectiveness.
• Implemented YOLO for object detection
• Used ngrok and stored URL in firebase
• Technologies: Python, Dart, Flutter, CNN, Computer Vision, YOLO, Tesseract OCR, NLP, RNNs.
• Given the Job Description my model will predict the required skills and Job titles.
• Technologies: Python, Deep Learning, RNNs, LSTM.
• Analyze the feed back of customer.
• FeedBacks: Very Postive, Positive, Neutral, Negative, Very Negative.
• Technologies: Python, Deep Learning, RNNs, LSTM
• Automatic facial expression recognition.
• Distinguish the Seven universal emotions: disgust, anger, fear, happiness, sadness, surprise and normal.
• Technologies: Python, Deep Learning, Image Processing, Computer Vison, ResNet
• Created a program that allows you to write on laptop's screen virtually.
• Technologies: Computer Vision, openCV
• The project was in response to the global pandemic, recognizing that social distancing is one of the most effective ways to compact the virus. Here, it makes shopping, one of the most common activities, safer and easier
• It uses a facial recognition system to recognize the customer.
• It stores the bill of each item, that customer picked from the store into a database.
• Technologies: Python, Machine Learning, Computer Vision, openCV
• Developed a Machine Learning based model that detects deases based on provided symptoms.
• Technologies: Python, Machine Learning, Naive-Bayes, Tkinter
• Developed a mobile app that sends an alert notification to people within certain radius at once.
• We managed to early predict the occurrence of fire using Deep Learning.
• Won in National Level and selected for Global Nominees.
• Technologies: Python3, Dart, Flutter Computer Vision, ResNet50
• Developed a mobile application using flutter for Attendance marking purpose using mobile bluetooth
• Separate interface and database was created for Teacher and Student using Firebase
• Technologies: Flutter, Dart, Firebase
• Created a mobile app using flutter that connects different ethnic groups
• Created a encoder-decoder network for language translation and GRU, attention models for effectiveness.
• Implemented YOLO for object detection
• Used ngrok and stored URL in firebase
• Technologies: Python, Dart, Flutter, CNN, Computer Vision, YOLO, Tesseract OCR, NLP, RNNs.