Guest Lecture by Professor Paul Cuff

Guest Lecture by Professor Paul Cuff

How do our cell phones work?

How are emails and text messages work?

Why is data never lost in space?

All of these questions were answered on Wednesday, October 26 from 3:00 to 4:00 p.m. when Professor Paul Cuff enhanced the MHS STEM experience through an intriguing guest lecture titled "The Digital Age: How Math Enables Digital Communication, Data Compression, and Data Encryption". Paul Cuff is a professor of Information Science and Systems (ISS, under Electrical Engineering) at Princeton University who works primarily with sophomores and juniors. His primary interests include information theory, secure communication, and machine learning, and his secondary interests include voting theory, investment theory, communication for control, ranking algorithms, and audio processing.

During his lecture, Professor Cuff focused primarily on the concept of information theory , audio processing, and secure communication.

He introduced his topics by explaining to us some of the unique projects which he has completed with his students. Two such projects are:

1) Designing a face-recognition based program. When a camera attached to a TV captured an individual's face, it would search the Princeton University website for that face. If there was a match, the screen would display a message in the form "Hi name of individual".

2) Recreating Shazam- Using the concept of sound waves and integrals (calculus) to replicate Shazam, which a music recognition app.

Professor Cuff further went on to explain how data is compressed. Attendees of the lecture were taught how computers calculate bits using logarithmic functions and relatively simple equations. To conclude his lecture, Mr. Cuff gave a brief synopsis of data encryption, and how messages are sent from one cellular device to another without being tampered with.

In order to captivate the attention of listeners, Professor Cuff filled his presentation with real life examples, and allowed students to come up and try sample problems. Clara Yu, for example, was asked to complete a task involving data compression. Savan Patel and David Young were asked to use what they had learned about data encryption to create a secret message.

By Mihir Doshi, TEAMS