Rohan Tinna

Rohan Tinna

M4X 0A1, Toronto, CA.
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About

Highly motivated Bachelor of Commerce student with a Minor in Computer Science, specializing in Management, AI, and Data Analysis. Proven ability to lead initiatives, secure significant funding (over $15,000), and drive impactful projects in technology and business development. Combines strong analytical and technical skills in machine learning and embedded systems with effective communication and strategic planning to deliver measurable results and enhance organizational efficiency.

Work

UofT AI Group

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Partnerships Team Lead

Toronto, ON, Canada

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Summary

Led a 4-member team and managed communication with stakeholders, successfully securing significant sponsorship for key AI events.

Highlights

Led a 4-member team, coordinating cross-functional communication with sponsors and internal departments to ensure seamless execution of club initiatives.

Successfully secured over $15,000 in sponsorship funds for two major AI conferences, ProjectX and GenAI Genesis, significantly exceeding fundraising targets.

Woodsworth College, University of Toronto

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Marketing & Communications Assistant

Toronto, ON, Canada

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Summary

Supported student transition and resource availability through direct collaboration with the Student Life & Equity Coordinator and strategic event planning.

Highlights

Collaborated with the Student Life & Equity Coordinator to enhance new student onboarding and resource accessibility for over 1,000 upper-year students.

Designed and executed engaging student events, significantly enhancing the overall student experience and fostering community engagement for hundreds of students.

Developed and implemented a centralized events calendar, streamlining information sharing across multiple departments within Woodsworth College, improving coordination and efficiency.

Gurugram Police Mentorship

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Cyber Security Intern

Remote, ,

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Summary

Gained practical insights into cybersecurity and contributed to problem-solving through engagement with law enforcement and industry leaders.

Highlights

Collaborated with senior law enforcement officers and industry leaders to analyze complex issues in online fraud, cyber law, and hacking techniques, gaining practical insights into cybersecurity operations.

Contributed to solving a "Hack Quest" challenge as part of a 4-person team, demonstrating collaborative problem-solving and technical application in a simulated cybersecurity environment.

Authored a comprehensive individual paper on cybersecurity, earning excellent feedback for its depth and insights from program instructors.

Education

University of Toronto

Toronto, ON, Canada
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Bachelor of Commerce Management; Computer Science Grade: 2.83/4.0

Courses

Financial Markets

Operations & Supply Chain Management

Software Engineering

Data Analysis

Artificial Intelligence

St. Theresa's Convent School

Karnal, Haryana, India
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High School Diploma Non-Medical Stream Grade: Class XII: 90%; Class X CGPA: 9.6/10.0

Languages

English

Native

Mandarin Chinese

Conversational

Hindi

Native

Awards

Academic Excellence Award

St. Theresa's Convent School

Awarded for outstanding academic performance during high school.

Skills

Programming Languages

Python, C, C++, Javascript, R, MIPS Assembly, Shell Scripting.

Data Analysis & Machine Learning

NumPy, Pandas, Matplotlib, SQL, Excel, Machine Learning, Neural Networks, kNN.

Web Development

HTML, CSS, React, Django.

Cloud & DevOps

AWS, Heroku, Netlify, Git.

Embedded Systems

STM32, SPI, I2C, UART, Mbed.

Project Management

Team Leadership, Cross-functional Coordination, Stakeholder Management, Strategic Planning, Event Management.

Communication & Marketing

Marketing Strategy, Content Creation, Event Planning, Public Relations, Interdepartmental Communication.

Cybersecurity

Cyber Law, Online Fraud Analysis, Hacking Techniques, Security Operations.

Projects

JuLIAH (#EmbeddedSystems #Mbed)

github.com/BobShoaun/JuLIAH

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Summary

Developed a prototype pet monitor utilizing an STM32 microcontroller, integrating various communication interfaces and a web application for real-time audio monitoring.

Digit Recognition

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Summary

Explored and compared various machine learning models for classifying handwritten digits from the MNIST dataset, optimizing model parameters for performance.