- Location
- Toronto, Ontario, Canada
- Bio
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Hello, my name is Syed Tabish Rahman, and I am an aspiring Software Engineer. I am currently a student at York University studying Information Technology. I am skilled in Python, JavaScript, React, HMTL, CSS.
In my free time, I enjoy working out, trying new food spots, martial arts, and gaming!
Please feel free to reach out to me at tabishrahman2002@gmail.com or through LinkedIn if you would like to start a conversation anything related to tech or just in general if you have any questions.
- Portals
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Toronto, Ontario, Canada
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Toronto, Ontario, Canada
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- Categories
- Security (cybersecurity and IT security) Software development
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Achievements



Recent projects
Work experience
fullstack software developer
Society for AI literacy
Toronto, Ontario, Canada
July 2025 - August 2025
• Co-founded the Rural Opportunity Hub (ROH), a web platform designed to help rural Canadian students access scholarships, volunteer opportunities, and mentorship, targeting 1,000+ students annually.
• Led frontend development of a multi-page, mobile-responsive website with a clean and accessible UI, ensuring cross-browser and device compatibility.
• Implemented core functionalities including scholarship filtering, opportunities directory, community forum, login/signup system, and lightweight admin panel, translating a PRD into functional features in 5 weeks.
• Collaborated with cross-functional teammates on UX/UI design and technical implementation, aligning platform features with user needs and accessibility standards.
• Delivered a scalable MVP on schedule, bridging the educational access gap and demonstrating measurable impact on rural student engagement.
Education
Bachelor of Arts (B.A.), Information Technology
York University
September 2021 - December 2025
Personal projects
Bioinformatics Hackathon (University of Toronto Temerity Faculty of Medicine)
September 2025 - September 2025
https://github.com/tabish-2002/Stock-market-predictor• Served as the sole Full stack developer on a multidisciplinary team of 5 biomolecular researchers.
• Built and delivered a functional prototype within 24 hours, featuring an NLP pipeline extracting 100+ protein–protein interactions, an interactive knowledge graph, and a React + TypeScript front end.
• Enabled researchers to explore 50+ protein networks across multiple cellular contexts, reducing manual literature review time by an estimated 70%.
• Presented the project to pharmaceutical CEOs and research leaders, showcasing its potential to accelerate drug discovery workflows and context-specific molecular insights.