Young Professionals Networking

Date :
Thursday, 18 April 2024
6:30PM – 8:30PM

Loccation :  E5-E6, 3F 


Event Description:
Join the IEEE Signal Processing Society Young Professionals after the conference sessions for a networking reception to unwind with your colleagues to discuss careers, entrepreneurship, and opportunities in a fun and casual setting.

Young Professionals Panel Discussion: Career development for signal processing students, researchers and practitioners

This panel discussion will bring together scientists from the industry and academia to share their career stories and experiences, including the main challenges they had to face and valuable advice for engineers and scientists in the field of signal processing. They will talk about the hiring and transition processes in industry and academia. The panel will also address the importance of technical and soft skills and their role in the creation of an effective career development plan.

Stefan Vlaski

Biography: Stefan Vlaski is Lecturer (analogous to Assistant Professor) at Imperial College London, where he conducts research at the intersection of machine learning, network science and optimization with applications in signal processing and communications. Stefan received the B.Sc. degree from Technical University Darmstadt, Germany, in 2013, and the M.S. as well as Ph.D. degree from the University of California, Los Angeles, USA, in 2014 and 2019, respectively. From 2019 to 2021 he was Postdoctoral Researcher with the Adaptive Systems Laboratory at École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. He was recipient of the German National Scholarship at TU Darmstadt and the Graduate Division Fellowship at UCLA. His papers have been recognized at Best Student Paper contests at IEEE ICASSP 2016 and IEEE CAMSAP 2019, and his research has led to patents which have been assigned to UCLA and Amazon.

Ehsan Variani

Biography: Ehsan Variani is a researcher in machine learning and information theory, with a focus on the fields of speech recognition and natural language processing. Currently, he holds the position of senior staff research scientist at Google, where he contributes to the advancement of these domains. He earned a Ph.D. and M.Sc. in Electrical and Computer Engineering from Johns Hopkins University.

Subhro Das

Biography: Subhro Das is a Staff Research Scientist at the MIT-IBM AI Lab in IBM Research, Cambridge, USA. His research interests are broadly in the areas of Representation Learning, Generative AI, Foundation Models, Trustworthy Machine Learning, Large Language Models, Reinforcement Learning, Dynamical Systems and ML Optimization methods. He received the BTech degree in Electronics & Communication Engineering from IIT Kharagpur, and MS and PhD degrees in Electrical & Computer Engineering from Carnegie Mellon University. He is an IEEE Senior Member, Chair of the SPS Young Professional Committee, Elected Member of the IEEE Machine Learning for Signal Processing (MLSP) Technical Committee, and serves as an Senior Area Editor for the IEEE Transactions on Signal Processing.