Page 175 - tech fest 2025 ב״ש חוברת תקצירים

JARVIS: AI-Based Personal Assistant
SE-C-06
Mohamad Abu Jafar; mohamadaj310@gmail.com Lidor Feldman; lidorfeldman2121@gmail.com
Advisor: Dr. Karim Abu-Affash
SCE - Shamoon College of Engineering, Be'er-Sheva
JARVIS (just a rather very intelligent system) is a high-level personal assistant developed to increase productivity through cleverly automating tasks on personal computers. In contrast to traditional voice assistants, JARVIS combines sophisticated context-aware automation, natural language processing (NLP), and optical character recognition (OCR) abilities to address intelligent reminders, autofill online forms, summarize documents, and automate tedious digital chores. Our literature review highlighted the present shortcomings in virtual assistants—voice recognition and rudimentary commands, for the most part—underlining the need for end-to-end solutions that work in a specific user context. The ultimate, long-term aim of JARVIS is to fundamentally change the relationship between the user and technology, making it efficient and convenient, and allowing the user to allocate their focus elsewhere.
Keywords: ai, automation, NLP, OCR, productivity, personal assistant, task management
Finvestify
SE-C-07
Hai Haim Maimon; haimaimon5@gmail.com Linoy Rachel Torogeman; linoyt456@gmail.com
Advisor: Dr. Alexander Churkin
SCE - Shamoon College of Engineering, Be'er-Sheva
Finvestify is a real-time trading platform designed to simplify portfolio management and improve investment decisions. It addresses challenges like information overload and lack of automation by providing automated trading bots, personalized analysis tools, and real-time sentiment analysis. The platform allows users to build and simulate long-term trading strategies based on historical data, enabling them to evaluate potential outcomes and make informed decisions about specific stocks. Finvestify uses technologies such as MongoDB and delivers an intuitive and responsive user experience.
Keywords: automated trading, machine learning, mongodb, sentiment analysis, stock market, trading strategies
Book of Abstracts | 2025
175