Adnaan chose the Computer Vision track in 2022-2023. He now works for a start-up in the United States.
What was your background before starting the MPhil?
I completed my undergraduate studies with degrees in Computer Science and Business Administration at the University of California, Berkeley. I completed internships at VMware, Apple, and Scale in software engineering and had conducted machine learning research at Berkeley's RISE lab. My main interest at the time was in computer vision and graphics, but I also had experience in general software engineering, project management, and management consulting.
What did you get out of the course?
Although my track was Computer Vision, I was able to take courses in language models, human-computer interaction, and core machine learning to develop a broad knowledge of the different branches of machine learning. I especially learned a lot about Bayesian and probabilistic machine learning, as most of my prior experience was in vision, graphics, and neural networks. I got valuable experience from my thesis project with Dr Ignas Budvytis, where I conducted deep research into large language models, foundation models, and graphics. In addition, I met many accomplished, intelligent, and friendly students in the programme, and some of them are my close friends to this day.
What were the highlights?
I really enjoyed the drinks receptions we had each term, where students could catch up and chat with the professors advising the programme. I also enjoyed MLMI 4, Advanced Machine Learning, as it covered a variety of modern topics and introduced me to various new areas. Another highlight was spending time with my friends from the course and my college, including going to salsa classes at Darwin, grabbing lunch together every day, swimming in Grantchester, and watching football games in London.
What have you gone on to do after the course and what are your longer-term plans?
I decided to go into industry after my MPhil and joined a start-up. My role is a mix of software engineering, machine learning, and general operations, and my experience from the MPhil has played a crucial role in my day-to-day work. My long-term plans are quite open, as I could see myself starting a company, taking on machine learning engineering roles, or doing a PhD a few years down the line.
What advice would you give to people applying for the course?
I'd highly recommend taking a look at the course outline on the website to determine which modules you're interested in, and therefore which track to select. It's also important to have a solid understanding of mathematics, probability, and linear algebra, as lectures can get quite technical. Highlighting this background and your passion for machine learning will strengthen your application, especially if you do not have much experience with it. If you're on the fence about applying, do it! This programme provides great career opportunities and Cambridge is an amazing city to live in.
What advice would you give to people taking the course?
For me, Cambridge's biggest strength is its people. It is one of the few places around the world where it is easy to meet some of the brightest minds in all of academia, in both STEM and the humanities. I highly recommend taking extra time to get to know your professors, as they can give some great advice and have tons of experience as leaders of their fields. Your fellow MLMI course mates are extremely friendly and some of the smartest people in the world, and I learned a lot from studying with students in my cohort. Outside of the programme, you can meet amazing people with unique backgrounds and interests in your college. Finally, there is so much to learn in this programme, but there is also so much to experience outside of academics. Make sure to be proactive in your coursework but also give yourself time to meet new people, explore the city, and spend time with your friends!