Faculty of Electrical Engineering, University of Banja Luka, Bosnia and Herzegovina
Dr. Gordana Gardašević (Full Professor) received a Ph.D. degree in Electrical Engineering (with a specialization in Telecommunications) from the University of Banja Luka, Faculty of Electrical Engineering (FEE), Bosnia and Herzegovina, in Dec. 2008. She is the Head of Department of Telecommunications at FEE. Prof. Gardašević published three books and two monographs in the fields of wireless sensor networks, IoT and industrial IoT, as well as more than 80 research papers. She is a reviewer of IEEE Internet of Things Journal, Transactions of Emerging Telecommunications Technologies, Sensors, Journal of Network and Computer Applications, and Wireless Personal Communications. Prof. Gardašević has participated in many national and international projects. She was one of the B&H representatives for FP6 Projects and the Member of Republic of Srpska Government Workgroup for Information Technologies. She is a Director of GDLN (Global Distance Learning Network) center at FEE. She was a B&H MC Representative for COST Action CA15104 - IRACON (Inclusive Radio Communication Networks for 5G and beyond), 2016-2020. She organized the Workshop on "Next Generation Communication Technologies and Services" in Banja Luka, in 2018. She is the MC Representative for two COST Actions: CA19111 - NEWFOCUS (European Network on Future Generation Optical Wireless Communication Technologies), 2020-2024; and CA20120 - INTERACT (Intelligence-Enabling Radio Communications for Seamless Inclusive Interactions), 2021-2025. She is one of the Editors of the newly established ITU Journal of Future and Evolving Technologies (ITU J-FET). Prof. Gardašević was also leading the strategic project "Banja Luka - Smart City" (2017-2020) and has been awarded for scientific and research results. Key research interests include Internet of Things (IoT) protocols and applications, IoT for healthcare, Industrial IoT, next-generation network architectures and applications, cross-layer protocol design, wireless sensor networks. She is a member of the IEEE.
Imperial College, London, United Kingdom
Dr. Danilo Mandić received the Ph.D. degree in nonlinear adaptive signal processing in 1999 from Imperial College, London, London, U.K. where he is now a Professor. He specialises in Statistical Learning Theory, Machine Intelligence, and Statistical Signal Processing, and their applications especially in Biomedicine and Finance. He is a pioneer of Hearables (in-ear sensing of neural function and vital signs), an unobtrusive, discreet and long-term wearable solution for long-term physiological monitoring based on miniaturised sensors embedded on an earplug, an area where he holds several patents. He also specialises in Machine Intelligence for Finance, and is a Director of the Financial Signal Processing and Machine Learning Lab at Imperial. He has written over 500 journal and conference articles, and research monographs on Recurrent Neural Networks (with Wiley, 2001), Complex-valued Adaptive Filters and Neural Networks (Wiley 2009), Tensor Networks for Dimensionality Reduction and Large Scale Optimisation (Now Publishers, 2017) and Data Analytics on Graphs (Now Publishers, 2021). Prof Mandic is a 2019 recipient of the Dennis Gabor Award for "Outstanding Achievements in Neural Engineering", given by the International Neural Networks Society (INNS). He is also a 2018 winner of the Best Paper Award in IEEE Signal Processing Magazine, for his article on Tensor Decompositions for Signal Processing Application, and the 2021 winner of the Outstanding Paper Award at the IEEE ICASSP conference. He has co-authored 6 more award-winning articles. He is a Core Member of the Machine Learning Initiative at Imperial. Danilo is a Vice-President of the International Neural Networks Society, and a past Technical Chair of ICASSP 2019, held in Brighton UK. He also received the President's Award for Excellence in Research Supervision at Imperial College in 2014. His current research interests are Adaptive Learning Theory, Big Data, Machine Learning on Graphs, Neural Networks, and Complexity Science, and their applications in Biomedicine and Financial Engineering.
Petar M. Djurić
Stony Brook University, Stony Brook, NY, USA
Petar M. Djurić received the B.S. and M.S. degrees in electrical engineering from the University of Belgrade, Belgrade, Yugoslavia, respectively, and the Ph.D. degree in electrical engineering from the University of Rhode Island, Kingston, RI, USA. He is a SUNY Distinguished Professor and currently a Chair of the Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, USA. His research has been in the area of signal and information processing with primary interests in the theory of Monte Carlo-based methods; Bayesian machine learning; signal modeling, detection, and estimation; signal and information processing over networks; RFID and the IoT. Recently, his research has been applied to problems related to machine learning methods for intrapartum fetal monitoring and brain signals. He has been invited to lecture at many universities in the United States and overseas. Djurić was a recipient of the IEEE Signal Processing Magazine Best Paper Award in 2007 and the EURASIP Technical Achievement Award in 2012. In 2008, he was the Chair of Excellence of Universidad Carlos III de Madrid-Banco de Santander. From 2008 to 2009, he was a Distinguished Lecturer of the IEEE Signal Processing Society. He has been on numerous committees of the IEEE Signal Processing Society and of many professional conferences and workshops. In 2019, he was the co-Chair of the Technical Program of ICASSP. This year, he serves as a General co-Chair of EUSIPCO. He was Editor-in-Chief of the IEEE Transactions on Signal and Information Processing over Networks. Djurić is a Fellow of IEEE and EURASIP.
Local Arrangements Team
- Jovan Galić, Department of Telecommunications, Faculty of Electrical Engineering, University of Banja Luka
- Boris Malčić, Department of Telecommunications, Faculty of Electrical Engineering, University of Banja Luka
- Milan Mlađen, Department of Telecommunications, Faculty of Electrical Engineering, University of Banja Luka
With the support of
2022 IEEE-SPS/EURASIP SUMMER SCHOOL ON NETWORK- AND DATA-DRIVEN LEARNING
Business Centre “Integra”, Banja Luka