Title: Statistical Inference over Networks: Decentralized Optimization Meets High-dimensional  Statistics

Abstract: Abstract: There is growing interest in solving large-scale statistical learning problems over decentralized networks, where data are distributed across the nodes of the network and no centralized coordination is present (we termed these systems as “mesh” networks). Inference from massive datasets poses  a fundamental challenge at the nexus of the computational and statistical sciences: ensuring the quality of statistical inference when computational resources, like time and communication, are constrained.   While statistical-computation tradeoffs have been largely explored in the centralized setting, our understanding over mesh networks is limited: (i) distributed schemes, designed and performing well in the classical low-dimensional regime, can break down in the high-dimensional case; and (ii) existing convergence studies may fail to predict algorithmic behaviors, with some findings directly contradicted by empirical tests. This is mainly due to the fact that the majority of distributed algorithms  have been designed and studied only from the optimization perspective, lacking the statistical dimension. This talk will discuss some vignettes from  high-dimensional statistical inference suggesting  new analyses (and designs) aiming at bringing statistical thinking in distributed optimization.
Speaker: 

Abstract: In this presentation, we delve into the transformative effects of cutting-edge technologies on the efficiency of wireless networks that underpin the Internet of Things (IoT), with a focus on eco-friendly wireless networks. We will unveil the latest developments in wake-up radio technologies equipped with semantic addressing, showcasing their ability to drastically reduce packet delivery times and achieve significant energy savings—by up to five orders of magnitude. Furthermore, we'll demonstrate how integrating energy harvesting techniques, such as solar and wind, with wake-up radios can lead to sustainable networked systems that rival the performance of traditional battery-powered nodes. Lastly, we'll explore the advantages of employing intelligent forwarding methods based on optimized learning algorithms. While acknowledging the noticeable costs associated with such methods, we'll also make a case for employing more cost-effective heuristic approaches derived from learning-based models.

Bio: Stefano Basagni holds a Ph.D. in electrical engineering from the University of Texas at Dallas (December 2001) and a Ph.D. in computer science from the University of Milano, Italy (May 1998). He received his B.Sc. degree in computer science from the University of Pisa, Italy, in 1991. He is currently a professor in the Department of Electrical and Computer Engineering at Northeastern University, in Boston, MA. He is also a core faculty of Northeastern's Institute for the Wireless Internet of Things.

Dr. Basagni's current research interests concern research and implementation aspects of mobile networks and wireless communications systems, wireless sensor networking for IoT (aerial, underwater and terrestrial), definition and performance evaluation of network protocols and theoretical and practical aspects of distributed algorithms.

Dr. Basagni has published over twelve dozens of highly cited, refereed technical papers and book chapters. His h-index is currently 52. He is also co-editor of three books. Dr. Basagni served as a guest editor of multiple international ACM/IEEE, Wiley and Elsevier journals. He has been the TPC co-chair of international conferences such as ACM Dial M for Mobility (2004), Med Hoc Net (2006), IEEE SECON (2010), IEEE Globecom (AHSN Symposium, 2012), IEEE MASS (2012), IEEE WiMob 2013, IEEE ICNC (NAPE Symposium, 2015), IFIP Wireless Days 2016, ACM WUWNet (2017), IEEE ICNC (WAHS Symposium, 2018), Med Hoc Net (2018), IEEE ICNC (NAPE Symposium, 2019), IEEE DCOSS 2021, ACM WUWNet 2022, IFIP WONS 2023, and IEEE PIMRC 2023. He was the general co-chair of IEEE SECON 2019 and of ACM WiNTECH 2020.

Dr. Basagni serves as a member of the editorial board, the organizing committee and of the technical program committee of ACM and IEEE journals and international conferences. He is a distinguished scientist of the ACM, a senior member of the IEEE, a member of ASEE (American Society for Engineering Education) and of CUR (Council for Undergraduate Education).

We are thrilled to announce that we will explore the vast realm of astrophysics with our esteemed invited speaker, Dr. Akhter. Dr. Akhter serves as a lecturer in Astrophysics and Physics at the University of Wollongong, bringing a wealth of expertise and knowledge to our event. In this talk, our esteemed speaker will impart knowledge and inspire individuals to embark on an exciting journey in engineering, with a specific focus on the captivating realm of astrophysics. Her presentation aims to dismantle barriers and extend encouragement to everyone, irrespective of gender, inviting them to delve into the boundless mysteries of the cosmos. Delving into the prerequisites for joining this field, she will highlight the importance of cultivating a robust foundation in mathematics and physics. Acknowledging the challenges that may surface, especially for women, she will share personal experiences, emphasizing resilience as a pivotal factor in overcoming gender-related obstacles. The speaker will underscore the significance of staying motivated through a genuine passion for astrophysics, advocating for the development of a supportive community and the ability to learn from setbacks. Reflecting on her journey, she will offer valuable advice to her younger self, promoting curiosity, embracing challenges as opportunities, and prioritizing well-being. Additionally, the talk will include a cautionary note, advising against pitfalls such as imposter syndrome and burnout, while emphasizing the importance of maintaining balance. We invite you to join this enlightening session with our exceptional speaker and contribute to the success of the event.

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