HOW I THINK ABOUT RESEARCH
Professor Alan V. Oppenheim ,
Massachusetts Institute of Technology (MIT) –
In the context of our roles in mentoring doctoral students, there are many ways of finding and formulating research problems and ideas. My own approach over many decades has been to focus on a style that gives students the experience as much as possible of an initially unstructured intellectual adventure with a safety net underneath. I like to describe the style as : “Having fun, chasing interesting ideas, which lead to solutions, in search of problems.” In this talk I will say a little more about this style and illustrate it with a few examples. In the examples, the focus is not on the details of the solution, but on how the topic originated and where it led to in terms of potential practical applications.
Professor Alan V. Oppenheim is a Principal Investigator in the Research Laboratory of Electronics (RLE) and Ford Professor of Engineering at the Massachusetts Institute of Technology (MIT). He received the S.B. and S.M. degrees in 1961 and the Sc.D. degree in 1964, all in Electrical Engineering, from the Massachusetts Institute of Technology. He is also the recipient of an honorary doctorate from Tel Aviv University. During his career he has been closely affiliated with MIT Lincoln Laboratory and with the Woods Hole Oceanographic Institution. His research interests are in the general area of signal processing algorithms, systems and applications. He is coauthor of the widely used textbooks Digital Signal Processing, Discrete-Time Signal Processing, (currently in its third edition) Signals and Systems, (currently in its second edition), and most recently Signals, Systems & Interference published in 2016. He is also editor of several advanced books on signal processing. Throughout his career he has published extensively in research journals and conference proceedings. Dr. Oppenheim is a member of the National Academy of Engineering, a Life Fellow of the IEEE, a member of Sigma Xi, and Eta Kappa Nu. He has been a Guggenheim Fellow and a Sackler Fellow.
Isabel Maria Martins Trancoso
Centro de Congressos do IST
Mathematics, Physics & Machine Learning Seminar Series (Online)
The Mathematics, Physics & Machine Learning seminar series has started on October 2020 and runs until March 2021.
The seminars aim to bring together mathematicians and physicists interested in machine learning (ML) with ML and AI experts interested in mathematics and physics, with the goal of introducing innovative Mathematics and Physics-inspired techniques in Machine Learning and, reciprocally, applying Machine Learning to problems in Mathematics and Physics.
Attendance is free but registration is required.
More information is available here.
International European Conference on Parallel and Distributed Computing
The 27th International European Conference on Parallel and Distributed Computing (Euro-Par 2021) will take from August 30 to September 3 2021 in Lisbon.
Euro-Par is the prime European conference covering all aspects of parallel and distributed processing, ranging from theory to practice, from small to the largest parallel and distributed systems and infrastructures, from fundamental computational problems to full-fledged applications, from architecture, compiler, language and interface design and implementation, to tools, support infrastructures, and application performance aspects.
The 2021 edition of Euro-Par will be organized as a collaboration between INESC-ID and Instituto Superior Técnico (IST).
– Abstract Submission: February 5, 2021
– Paper Submission Deadline: February 12, 2021
– Author Notification: April 30, 2021
– Camera-Ready Papers: June 6, 2021
More information is available here.