UMass Boston

The program follows a hybrid schedule with in-person sessions on Monday and Friday at the University of Massachusetts Boston, where lunch is provided, and virtual sessions on Tuesday through Thursday.

Week 1 - Introduction to AI & Machine Learning

Students will start their journey by understanding the foundations of how computers learn from data. They will go from a "curious beginner" to a "confident AI builder" in just five days. 

• Key Takeaways: Learning how to train an AI model and improve it through simple experiments. 
• Cool Projects: Building a personal image classifier and working with the same "AI coding assistants" used by engineers at Google and Microsoft. 
• College Prep: Students demonstrate initiative by solving an original problem, which makes for a compelling personal narrative in application.
•  (See attached syllabus)                   

Week 2 - From Neural Networks to Intelligent Machines

This week brings code to life. Students will learn how AI allows robots to "see" and interact with the physical world using specialized hardware. 

• Key Takeaways: Understanding how neural networks recognize patterns and how to run AI on small, portable computers like the Raspberry Pi. 
• Cool Projects: Using a robotic arm to pick up objects and creating a custom system that can detect things through a camera in real-time. 
• College Prep: Hands-on experience with hardware integration and professional equipment like robotic arms and GPU servers. 
• (See attached syllabus)

Week 3 - Speech and Natural Language Processing

We pull back the curtain on how tools like ChatGPT work. Students discover that these complex systems are "prediction machines," not magic. 

• Key Takeaways: Understanding how computers process human language and the ethics behind "deepfakes" and voice cloning. 
• Cool Projects: Creating a "Mood Detector" and testing whether people can tell the difference between student-written essays and AI-summarized text. 
• College Prep: Developing critical thinking skills about technology's impact on society and learning the technical pipeline behind voice-activated tools. 
• (See attached syllabus)

Week 4 - Generative AI & Creativity

This week explores the "creative power" of AI. Students learn to use AI for generating text, images, and audio while thinking like investigators. 

• Key Takeaways: Mastering "prompt design" (the art of talking to AI) and investigating why AI sometimes makes mistakes (hallucinations). 
• Cool Projects: Creating a multimedia production, like a narrated story or a podcast introduction, using a mix of AI tools. 
• College Prep: Students have the opportunity to turn their creative projects into professional research posters or papers.
• (See attached syllabus)

Week 5: From Curiosity to Creation: Build Your First AI Project & Research Portfolio

The final week is about "From Curiosity to Creation." Students focus on high-level research and preparing their work for the world. 

• Key Takeaways: Learning how to ask "meaningful questions" and seeing how AI models make decisions behind the scenes. 
• Cool Projects: Conducting tests for machine "self-awareness" and creating a professional, portfolio-ready project to show off. 
• College Prep: Students produce a formal "research-style write-up" perfect for college essays or major research competitions like ISEF.
•  (See attached syllabus)

AI in One Day

The one-day event is about "Immersive AI in a Single Day." Students step into the world of artificial intelligence through a project-based experience that connects them to the broader AI Summer Research Camp community. 

• Key Takeaways: A clear picture of what AI is, how it's used in the real world across areas like machine learning, computer vision, and natural language processing and what learning AI actually looks like in practice. 
• Cool Projects: Building and presenting a mini AI project individually or in small teams applying what they've learned to create simple AI-driven solutions in just one day. 
• Skills Gained: Problem-solving, critical thinking, and collaboration: applied through hands-on activities and guided instruction from experienced mentors. 

Special Perk: Participants attend the AI Summer Research Camp's final showcase, watching real student projects and getting a firsthand look at what deeper engagement with AI can produce.

• AI Foundations: Develop a strong understanding of how AI models are built, trained, and evaluated across areas such as machine learning, computer vision, and language processing. Apply these concepts through hands-on experimentation and problem-solving.
• Portfolio Projects: Complete an end-to-end AI project that demonstrates technical skills, creativity, and real-world application. Build a portfolio piece suitable for academic programs, competitions, or future opportunities.
• Presentation and Leadership: Present projects clearly and confidently while leading discussions and collaborative work. Strengthen communication, critical thinking, and the ability to apply AI responsibly in real-world settings.

• All 5 weeks: $4,495 (Recommended) 
• Any 4 weeks: $3,596
• Any 3 weeks: $2,697
• Any 2 weeks, $1,798
• Any 1 week: $899
• AI in One Day - $399

To successfully complete your registration, please follow the steps below: 

• Students or parents access the Registration Form
• Complete all required information and submit any necessary materials 
• Proceed to the payment section within the same form to complete payment 
• Upload the payment receipt within the form 
• Submit the form to finalize registration 
• If space becomes unavailable for a selected week, the program team will follow up directly with the family regarding next steps. 

Registration will be handled on a first-come, first-served basis, with a maximum of 20 spots available per week.

• Dr. Wei Ding, Executive Director of the Paul English Applied Artificial Intelligence Institute and Professor of Computer Science at UMass Boston
• Dr. Ping Chen, Full Professor of Computer Engineering and Director of the Artificial Intelligence Lab at UMass Boston
• Dr.  Xiaohui Liang, Associate Professor of Computer Science at UMass Boston, leads the Mobile Computing and Privacy Lab
• Dr. Shichao Pei, Assistant Professor in Computer Science at UMass Boston, whose research interests include machine learning, foundation models, and AI safety
• Dr.  Bo Sheng, Professor of Computer Science at UMass Boston, whose research includes edge computing, mobile systems, cloud computing, robotics, and cybersecurity
• Dr. Yinxin Wan, Assistant Professor in Computer Science at UMass Boston, whose interests include secure and trustworthy AI, IoT, and networked systems
• Chengjie Zheng, PhD Candidate of Computer Science
• Ajanee Igharo, MBA Candidate and BA in Psychology
• Dora (Dawn) Nguyen, Undergraduate in Accounting, Minor in Psychology
• Rebaz Kamal, Undergraduate in Computer Engineering, Minor in Computer Science
• Rami Huu Nguyen, PhD Student in Computational Science, Data Analytics