Applied AI in Engineering Summer Institute at University of California, Berkeley

Course Description: Applied AI in Engineering Summer Institute at University of California, Berkeley

This fully immersive 2-week residential summer programme is designed for undergraduate students (18+) who want to explore applied artificial intelligence and its transformative role in engineering fields. Set on the historic campus of the University of California, Berkeley—ranked #3 in engineering globally—students engage with world-leading faculty to understand how AI is revolutionizing energy systems, robotics, autonomous vehicles, sustainable manufacturing, and beyond.

Combining faculty-led lectures on cutting-edge AI applications, hands-on research projects, industry site visits to Amazon and Intel Museum, and exploration of Silicon Valley's innovation ecosystem, the programme provides authentic exposure to how AI shapes the future of engineering. Students return home with completed AI capstone projects, professional networks, and clarity about their engineering career direction.

📍 Location & Campus Experience

Students live and study on UC Berkeley's historic campus in the San Francisco Bay Area—the epicentre of global AI and engineering innovation.

• One of the world's most prestigious engineering schools (#3 Best Engineering School, U.S. News & World Report 2024)

• Heart of Silicon Valley, less than 15 miles from San Francisco

• Easy access to leading technology companies: Amazon, Intel Museum, Stanford University

• Vibrant campus culture with diverse international student community

• Modern residential facilities within walking distance of engineering labs and lecture halls

• Gateway to San Francisco's cultural attractions, Golden Gate Bridge, and Bay Area outdoor recreation

Berkeley, California embodies innovation and academic excellence. The city offers a youthful atmosphere with eclectic shops, street art, and diverse food scene. Historic Telegraph Avenue showcases the university's cultural heritage, while beautiful city parks and the nearby Bay provide outdoor experiences. The location places students at the intersection of world-class research and industry application—where AI theory meets real-world engineering practice.

🌐 English Language Requirements

This programme is designed for undergraduate students with strong English proficiency to engage with advanced engineering content and faculty lectures.

Recommended English Levels:

• IELTS: 6.5

• TOEFL: 4.0

• PTE Academic: 58

• DET: 115

• iTEP: 4.5 or equivalent

Waivers are available for students who demonstrate strong academic motivation and engineering potential despite not meeting standard benchmarks. Students may interview with the admission office for alternative pathways.

📚 Academic & Research Curriculum

The Applied AI in Engineering Summer Institute features a hands-on, applied curriculum delivered by UC Berkeley faculty experts. Students explore how artificial intelligence transforms engineering practice across multiple domains.

Focus Areas:

Students examine AI applications in:

• Clean & Renewable Energy Systems – AI optimization in geothermal, solar, ocean, and nuclear energy infrastructure

• Biomedical & Biomechanical Engineering – AI-driven analysis and design in healthcare and human performance applications

• Data Analysis, Manufacturing & Supply Chain Systems – AI for predictive modeling, process optimization, and industrial efficiency

• Robotics, IoT, and Smart Infrastructure – Autonomous systems, perception, control, and real-world deployment

• Computer Vision and AI Ethics – Visual intelligence systems and responsible AI development

Faculty-Led Lecture Series:

World-leading UC Berkeley engineering faculty deliver seminars exploring applied AI across three core themes spanning the two-week programme.

🎓 Core Seminar Themes

Theme 1: AI, Computation, and the Foundations of Intelligent Systems

This foundational theme introduces core principles underlying modern AI systems, emphasizing how technical design choices intersect with human behavior, trust, and societal impact. Students examine machine learning fundamentals alongside critical questions of ethics, transparency, and governance.

Representative topics include:

• Machine learning fundamentals and recommendation systems

• Algorithmic evaluation and performance metrics

• Human-centred AI and trust in AI-assisted systems

• Social, political, and ethical implications of computing

• Values embedded in smart systems and digital infrastructure

Theme 2: AI for Energy, Sustainability, and Industrial Systems

This theme explores how AI is applied to energy systems, industrial processes, and large-scale infrastructure, with a focus on sustainability, resilience, and efficiency. Students engage with examples spanning renewable energy, nuclear systems, advanced manufacturing, and materials science, highlighting AI's role in optimizing complex, high-impact systems.

Representative topics include:

• Geothermal, solar, ocean, and nuclear energy systems

• AI-driven optimization and predictive modelling in energy infrastructure

• Advanced manufacturing and semiconductor technologies

• Sustainable materials and electronics

• Industrial supply chains and systems-level sustainability

Theme 3: Robotics, Autonomy, and AI in Motion

This theme focuses on embodied and autonomous AI systems operating in dynamic, real-world environments. Emphasis is placed on perception, planning, control, and safety-critical decision-making in robotic and autonomous platforms.

Representative topics include:

• Legged robotics and loco-manipulation

• Aerial robotics and autonomous flight

• Perception-aware planning and navigation

• Safety-critical control and learning-based autonomy

• Autonomous vehicles and intelligent transportation systems

🔬 Capstone Project: AI in Practice

The capstone brings the program’s AI lectures and technical workshops together in a team project. During the first week, students explore topics such as deep learning, generative modeling, and AI tools while developing their project ideas in hands-on labs. In the second week, they refine their work with guidance from the program team and present it at a final showcase. Students leave with a completed project they can add to their portfolio.

👨‍🏫 World-Leading Faculty

The programme is taught by pioneering UC Berkeley engineering researchers advancing the frontier of applied artificial intelligence.

Mohammed-Reza Alam – Professor, Mechanical Engineering

Professor Alam is the American Bureau of Shipping Chair in Ocean Engineering and Professor and Vice Chair of the Department of Mechanical Engineering at UC Berkeley. His research interests include theoretical and experimental fluid dynamics, ocean and coastal wave phenomena, dynamical systems and nonlinear dynamics, and fluid flow controls. He received his PhD from MIT in 2008 and joined UC Berkeley in 2011. Professor Alam serves as director of the "Ocean and Coastal Science and Engineering" programme and the "Theoretical and Applied Fluid Dynamics Laboratory" at UC Berkeley.

Dr. Koushil Sreenath – Associate Professor, Mechanical Engineering

Dr. Sreenath is an Associate Professor of Mechanical Engineering at UC Berkeley. His research interest lies at the intersection of highly dynamic robotics and applied nonlinear control. His work on dynamic legged locomotion was featured on The Discovery Channel, CNN, ESPN, FOX, and CBS. His work on dynamic aerial manipulation was featured on IEEE Spectrum, New Scientist, and Huffington Post. His work on adaptive sampling with mobile sensor networks was published as a book. He received the NSF CAREER, Hellman Fellow, Google Faculty Research Award in Robotics, and Best Paper Awards at Learning for Dynamics and Control (L4DC) and Robotics: Science and Systems (RSS).

Mark Mueller – Professor, Mechanical Engineering

Professor Mueller joined the Mechanical Engineering Department at Berkeley in August 2016. He received a bachelor's degree from the University of Pretoria, followed by a masters (2011) and doctorate (2015) from ETH Zurich, all in Mechanical Engineering. Mark heads the High Performance Robotics Laboratory, with a research focus on the design, dynamics, and control of autonomous aerial systems. He is also organiser of the Bay Area Robotics Symposium and serves as an Associate Editor for IEEE Robotics and Automation Letters and Unmanned Systems. He received the 2016 George Giralt PhD award for the best robotics-related PhD thesis defended during the year 2015 at a European PhD-awarding institution, as well as the 2011 Jacob Ackeret prize from the Swiss Association of Aeronautical Sciences for his Masters Thesis.

Dr. Kosa Goucher-Lambert – Assistant Professor, Mechanical Engineering

Dr. Kosa Goucher-Lambert is an Assistant Professor of Mechanical Engineering at UC Berkeley. He is also affiliated with the Jacobs Institute of Design Innovation and the Berkeley Institute of Design. Kosa received his B.A in Physics from Occidental College and his M.S. and Ph.D. in Mechanical Engineering from Carnegie Mellon University. His research focuses on decision-making in engineering design, using mathematical analyses, computational modelling, human cognitive studies, and neuroimaging approaches. He is a recipient of the National Science Foundation CAREER Award, 2019 Excellence in Design Science Award, and several best paper awards.

Dr. Zakaria Al Balushi – Assistant Professor, Materials Science and Engineering

Dr. Zakaria Al Balushi is an Assistant Professor in the Department of Materials Science and Engineering at UC Berkeley, co-Director of the Berkeley Emerging Technologies Research (BETR) Center, and a faculty scientist at the Lawrence Berkeley National Laboratory. He has degrees in Engineering Science and Materials Science and Engineering from Penn State. His research has spanned silicon nanowire devices, group-III nitride semiconductors, and low-dimensional materials. Before Berkeley, he was a postdoctoral fellow at Caltech. He has received several awards, including the NSF CAREER and Micron Corporation Early Career Awards.

Dr. Josh Hug – Associate Professor, Electrical Engineering and Computer Sciences

Dr. Josh Hug has been an Associate Teaching Professor at UC Berkeley in Electrical Engineering and Computer Sciences since August 2014. His research includes computational models of bacterial signal processing. He was a former lecturer at Princeton University and has also worked at perfectrec.com. He received his PhD from UC Berkeley and a B.S. in Electrical Engineering from the University of Texas at Austin. Awards include the Diane S. McEntyre Award for Excellence in Teaching Computer Science, the Jim and Donna Gray Award for Excellence in Undergraduate Teaching, and the Distinguished Teaching Award.

🗓️ Daily Routine & Programme Schedule

Each day balances intensive academic instruction, hands-on lab work, site visits, and social engagement to create a rich immersive experience.

Typical Weekday Schedule:

• 08:00 – Breakfast

• 09:30–10:30 – Core Lecture (faculty-led seminar on AI theme)

• 11:00–12:30 – Research Seminar (hands-on capstone project guidance)

• 12:30–13:30 – Lunch

• 13:30–14:30 – Core Lecture (continued theme exploration)

• 15:00–16:30 – Research Seminar or Self-Guided Project Work

• 17:00–18:00 – Guest Speaker, or Campus Tour

• 18:00–19:00 – Dinner

• 19:00–20:00 – Evening Activities (social events, community building)

Sample Week 1 Itinerary:

• Monday: Cohort arrival, check-in, campus tours, orientation, safety induction

• Tuesday: Core lecture, research seminar, Amazon and Intel Museum visit (9am–6pm)

• Wednesday: Core lecture, research seminar

• Thursday: Core lecture, research seminar, guest speaker seminar

• Friday: Core lecture, research seminar

• Saturday: San Francisco Big Bus tour and cultural exploration

• Sunday: Outlet Shopping and Sunset Hike

Sample Week 2 Itinerary:

• Monday–Thursday: Core lectures, research seminars, campus facility tours (Wind Tunnel, Jacobs Institute of Design Innovation)

• Friday: Final AI research presentations, graduation ceremony

• Saturday: Cohort departure

🏠 Accommodation & Campus Living

Students stay on the UC Berkeley campus in modern residential facilities with experienced residential staff supervision.

Residence Hall Features:

• On-campus housing within walking distance of engineering facilities

• Comfortable rooms with individual furnishings

• High-speed internet and modern amenities

• Shared bathroom facilities

• Washer and dryer access within residence halls

• Fresh linens provided and changed regularly

• Common areas for relaxation, studying, and socialising

• Single room occupancy

• Safe, secure environment with 24/7 campus security

🍽️ Meals & Dining

All meals are included in the programme fee, providing nourishing options to support active learning.

Meal Service:

• Three nutritious meals daily (breakfast, lunch, and dinner)

• Variety of international and local cuisine options

• Modern dining facilities on campus

• Access to nearby cafés, restaurants, and shops

• Healthy, balanced meal planning supporting academic performance

🎭 Cultural Immersions & Social Life

Students explore the San Francisco Bay Area and Silicon Valley, engaging with American culture, innovation ecosystems, and building international friendships.

Bay Area & Campus Activities:

• Sunset Hike – Outdoor exploration of local nature

• Talent Show – Creative expression and community celebration

• Board Game Nights – Evening social gatherings

• Bobba Tea Night – Casual social time at local venues

• Arts & Crafts Night – Creative activities and cultural exchange

• Movie Night – Film screening and group relaxation

San Francisco Area Exploration:

• Golden Gate Bridge – Iconic San Francisco landmark with stunning views

• Historic Telegraph Avenue – Berkeley's cultural hub with shops, restaurants, and street life

• Campus landmarks – Sather Tower, iconic bear statues, historic architecture

Industry Site Visits:

• Amazon – Visit to Amazon Fulfillment Center exploring AI and logistics innovation

• Intel Museum - Explore the evolution of semiconductor technology and its role in advancing AI and modern computing.

🌍 Why UC Berkeley & the Bay Area

UC Berkeley's College of Engineering stands as a beacon of innovation and research excellence, making it an ideal setting for an advanced AI programme.

Rankings & Recognition:

• #3 Best Engineering School (U.S. News & World Report, 2024)

• #4 Best Global Universities

• #11 Best Global Engineering Programs

• #5 America's Top Colleges (Forbes)

Silicon Valley Innovation Ecosystem:

• Home to major technology companies and AI research organisations

• Proximity to industry leaders: Amazon, Stanford

• Gateway to understanding how AI transforms engineering practice in real-world settings

• Growing sustainability and clean tech sectors driving AI innovation

• Vibrant startup culture and entrepreneurship ecosystem

📅 Programme Dates, Duration & Pricing

2026 Summer Session:

• Dates: July 5–17, 2027

• Duration: 2 weeks (12 days residential)

• Cost: $8,750 USD

• Registration Deadline: April 30, 2027 (Early Registration Deadline: December 30, 2026 for a $250 discount)

What's Included:

• Programme tuition (all lectures, seminars, workshops)

• Student services (visa support, airport transfers, programme supervision)

• Programme activities (site visits, tours, social events, museum tickets)

• Residential accommodation on campus

• Three meals daily

• Linens and bedding

• Comprehensive travel and medical insurance

• Campus facilities access (libraries, labs, recreational spaces)

• Certificate of Achievement and Letter of Completion from UC Berkeley

• Completed AI Capstone Project

• Letter of Recommendation from programme faculty (at discretion)

What's Not Included:

• International airfare

• Visa application fees

• Personal expenses and pocket money

📋 Registration Requirements

Age Requirement: 18+ years old

Academic Background:

• Must be enrolled in a university or recently graduated from university

• Open to all undergraduate majors (engineering, business, humanities, sciences)

• No prior AI experience required

English Proficiency:

• IELTS: 6.5; TOEFL: 4.0; PTE Academic: 58; DET: 115; iTEP: 4.5 or equivalent

• Waivers available for qualified candidates; students may interview with the admission office

Visa Requirement: B1/B2 Tourist Visa (visa support provided)

🌟 Programme Highlights

✅ Elite Engineering Institution – Learn at UC Berkeley, ranked #3 globally for engineering

✅ Applied AI Across Domains – Explore energy systems, robotics, autonomous vehicles, sustainable manufacturing, and more

✅ Hands-On Capstone Project – Design and present an AI solution using real-world data and industry frameworks

✅ Industry Exposure – Visit Amazon, Intel Museum, see cutting-edge AI and robotics in action

✅ World-Class Faculty – Learn from UC Berkeley professors advancing robotics, sustainable energy, and AI ethics

✅ Silicon Valley Access – Located less than 15 miles from San Francisco, in the heart of global AI innovation

✅ Professional Development – Build career skills in design thinking, presentation, and networking

✅ Global Community – Build international friendships with ambitious peers from around the world

✅ Completed Portfolio Project – Leave with a capstone project to strengthen college applications and résumés

💡 Why Choose This Programme

Explore Applied AI in Engineering Gain hands-on understanding of how artificial intelligence solves real engineering challenges. From renewable energy optimisation to autonomous robotics, see AI's transformative role across domains.

Develop Technical & Professional Skills Combine faculty instruction with design thinking, effective communication, and professional networking. Prepare for engineering careers in an AI-driven world.

Capstone Experience for Your Portfolio Complete a meaningful AI project demonstrating your technical growth and creative problem-solving. Strengthen college applications and graduate school prospects.

Connect Learning to Innovation Experience Silicon Valley's AI and engineering ecosystem. Visit industry leaders. Understand how research becomes practice. Gain clarity about your career direction.

Build Global Network Connect with world-leading faculty and peers pursuing engineering and AI careers globally. Develop relationships that support your academic and professional future.

Exposure to World-Class Institution Experience university life at one of the world's leading engineering schools. Access labs, facilities, and resources at the frontier of innovation.

🎤 Student Testimonials

"Come, 100%. You’re going to have a great time, learn a lot, and meet some really cool people."— Alvaro, Summer 2026 Participant, Spain

"This seminar ignites my passion on robotics and anatomy. I want to dive in robotics + AI and energy in the future." — Jimmy, Summer 2026 Participant, China

"The lessons were so valuable, and I'm grateful to have learned so much alongside such amazing people." — Marcos, Summer 2025 Participant, Brazil

"I think Berkeley is the most influential in terms of engineering. I came here to explore the potential of why AI will change the world. This program is very exciting!" — Zhu, Summer 2024 Participant, China

"I don't have any technology background at all in my previous experience. I did learn a lot of knowledge regarding AI, and all the people I met it was really fun. I enjoy it so much." — Jingwen, Summer 2025 Participant, China

"Every moment felt like learning — from applying for the visa, to traveling here, to writing daily reflections. Everything helped me grow." — Saniya, Summer 2025 Participant, India

🌟 Overall Experience

This programme offers an unparalleled opportunity to engage with applied artificial intelligence at one of the world's leading engineering institutions. Set on UC Berkeley's historic campus with direct access to Silicon Valley's innovation ecosystem and world-leading faculty, students gain practical understanding of AI's transformative role in engineering while developing critical thinking, professional skills, and career clarity.

Through intensive lectures, hands-on capstone projects, industry site visits, professional development workshops, and cultural immersion, students leave the programme with:

• Deep understanding of AI applications across energy, robotics, autonomous systems, and sustainable engineering

• Completed AI capstone project demonstrating technical competency

• Strong preparation for engineering careers or graduate study in AI-focused fields

• Global network of peers and faculty connections

• Clarity and confidence about future academic and career directions in engineering and AI

• Unforgettable memories and transformative personal growth

Join us for two weeks of intensive learning, innovation, and discovery in the world's AI and engineering capital—where artificial intelligence is engineered to solve humanity's greatest challenges and shape the future of technology.

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