Lectures: Access Zoom Room
This course is running online at Penn during Spring of 2021. We meet on Mondays, Wednesdays and Fridays at 10am EST in the ESE224 zoom room. To access this room you need to have a password that has been provided by your instructor. We understand that attending lectures live could be a challenge. We will therefore release recordings right after each lecture. We still ask you to please attend live. Who knows? Maybe if there are enough of us in attendance the meetings end up being fun. I am sure we can agree on the need for a source of entertainment other than rewatching The Mandalorian.
We will use slides during lectures. You can access them in the lectures section of the course’s site. Lecture notes are also available. They are not the most polished work, but we believe most of you will find them to be of reasonably good value.
We will have 13 lab assignments during the term at a clip of one per week. They are designed to take about 10 hours to complete. If they are taking more time than that, please consider increasing your use of teaching assistance. Follow this link to access lab assignments.
You have been divided in groups of 6 to 8 students made up of two teams of 3 or 4 students each. Groups meet twice a week with an assigned teaching assistant for an interactive session. Within a group you collaborate with the members of your team to prepare a solution and write a report. You must have received an email with your group and team assignment. If you haven’t received such note, send an email to email@example.com so that we can make proper adjustments.
You may notice from the above numbers that we are making a big effort to offer personalized instruction. We encourage you to develop a strong professional relationship with your teaching assistants. This is the reason why we are dividing you in small groups. We also encourage you to form a strong working relationship with your team. There is much you can learn through interaction with your peers. This is the reason why we are choosing to keep the teams together throughout the term.
We are running a discussion forum on Piazza. Please be engaged. Submit questions. Answer questions. Offer comments. Offer help.
As you probably know, Penn has spread out the Spring break as individual single day holidays throughout the semester. This makes the task of keeping a course calendar a little complicated because we have to move due dates around. To help you stay organized we have created the ESE224 calendar. The calendar has reminders for the lecture times which will hopefully prevent you from showing up for lectures on a vacation day. More importantly, it has the release and due dates for the lab assignments and the midterms.
We encourage you to merge this calendar with yours. Homework due dates begin on Mondays, they then move on to Tuesdays and back to Mondays. That is before moving to Fridays and back to Wednesday on the last week. You get the picture.
We have 13 lab assignments during the term. Each of them is graded in a scale from 0 to 4. You get no points if you don’t turn it in. You get 1 point for a poor job, 2 points for an OK job, 3 points for a good job and 4 points for an excellent job. These points are assigned to your group based on your lab report. The idea is for all of you to get a 4 in all 13 reports and therefore accumulate 52 points total. If you get anything less than a 4 in a lab report we will point out your mistakes and we will offer you the chance to submit corrections within the week. The only way for you to get less than 52 points in your lab assignments is for you to skip some work. Please avail yourself of this opportunity.
In addition, we are going to have two take-home midterms. Midterm 1 is to be released on March 8 and it is due on March 17 by 5 pm. Midterm 2 is to be released on April 28 and it is due on April 29 at 5pm. Each of the midterms is worth a total of 26 points.
The grand total of points that can be earned in ESE224 is therefore 104. You pass with at least 60 points, you get a C with at least 70 points, a B with at least 80, and an A with at least 90 points. Within each letter range you get a minus decoration in the first 3 points of the range (for example, you get a B- for 80, 81, or 82 points). You get a plus decoration in the last three points of the range (for example, you get a B+ for 87, 88, or 89 points). This is true except of A+ grades. You get this only for perfect scores.
Luana Ruiz is halfway through the 4th year of her doctoral studies at Penn. Her main research interests are in the areas of signal processing and machine learning. She brings a lot of experience on Graph Neural Network research. She is particularly well known for her work on graphon signal processing and its implications in the transferability properties of graph neural networks. You can reach her at firstname.lastname@example.org and you can learn more about her research by visiting her webpage.
Juan Cervino is very happy to be a TA for this course. Juan is halfway through the 2nd year of his doctoral studies at Penn. His main research interests are in the intersections between optimization, control, and machine learning. Juan’s work has taken to investigate cross learning problems in which several related but different tasks are cross fertilized during the learning process. You can reach him at email@example.com and you can learn more about his research by visiting his webpage or asking him.
Zhiyang Wang is equally happy to be TA for this course. She is a 2nd year PhD student at Penn. Her research interests include wireless communication networks and machine learning. In the last year Zhiyang has been working on the use of graph neural networks to design algorithms for distributed allocation of resources in wireless communication networks. More recently, she has worked on beautiful analyses of the limits of graph neural networks when graphs are sampled from manifolds. Her email address is firstname.lastname@example.org. She doesn’t have a webpage but is happy to tell you about her research if you ask.
Zhan Gao is, what else, very happy to be a TA for this course. Zhan is on the 3rd year of his doctoral studies at Penn. His main research interests are in the intersections between optimization, machine learning and wireless networks. Zhan has been working on distributed learning with graph neural networks and its applications in wireless networks. You can reach him at email@example.com if you have any questions about the course.
Vinicius Lima is on the 3rd year of his doctoral studies at Penn. His main research interests lie in the intersections between controls, machine learning and wireless networks. Vinicius has been working on resource allocation for wireless control systems and on distributed optimization with graph neural networks. You can reach him at firstname.lastname@example.org if you have any questions about the course or his research.
Professor Alejandro Ribeiro
This class is been taught by me, Alejandro Ribeiro. I am very happy to have a captive audience to listen attentively while I talk about my chosen research area. I have been doing research on signal processing for 17 years. My group is well known for our contributions to graph signal processing, optimization, and collaborative systems. If you want to get a better sense of my research and teaching activities please visit my lab’s website which has descriptions of my research vision and provides access to the sites for the courses I teach, including this one.
Academicians are always eager to flaunt the awards they have received and I am not going to be the exception. Papers I have coauthored have received the 2014 O. Hugo Schuck best paper award and paper awards at ICASSP 2020, EUSIPCO 2019, CDC 2017, SSP Workshop 2016, SAM Workshop 2016, Asilomar SSC Conference 2015, ACC 2013, ICASSP 2006, and ICASSP 2005. I received a 2019 Outstanding Researcher Award from Intel, the 2017 Penn’s Lindback award for distinguished teaching and the 2012 S. Reid Warren, Jr. Award presented by Penn’s undergraduate student body for outstanding teaching. I am a Fulbright scholar class of 2003 and a PennFellow class of 2015.