21st May 2024 – 10:30 AM
Politecnico di Torino – Sala Ciminiera
Please, remember that registration is required to attend the event.
Abstract
Heat stress, a consequence of climate warming and the heightened milk production
demands on dairy cattle, poses a significant threat to the welfare of the animals and the
overall sustainability—economic, environmental, and social—of dairy farming worldwide.
Identifying cows experiencing heat stress promptly is essential for enhancing animal welfare,
minimizing milk production losses, and conserving water and energy resources required for
cooling. This talk introduces our multidisciplinary research on precision dairy farming using
wearable technology and machine learning. I will introduce our novel system for detecting
heat stress in a timely manner and machine learning approaches on multi-modal sensing. I
will talk about our multi-phase development and evaluation of the proposed system and
present how we collaborate with animal scientists and biosystems engineers for closed-loop
control of the barn.
Dr. Younghyun Kim
Younghyun Kim is an Associate Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University. Before joining Purdue in 2024, he was with the University of Wisconsin-Madison from 2016 to 2023. He was a Postdoctoral Research Assistant at Purdue University from 2013 to 2016. He received his Ph.D. degree in Electrical Engineering and Computer Science in 2013 and B.S. degree (highest honor) in Computer Science and Engineering in 2007, both from Seoul National University. His Ph.D. dissertationwon the EDAA Outstanding Dissertation Award (2013). He is a recipient of the NSF CAREER Award (2019), Meta Research Faculty Research Award (2021), and other awards for designs and demonstrations. His research interests include security and privacy for embedded computing systems, energy-quality scalable computing, machine learning at the edge, and cyber-physical systems.
Abstract
In the last few years, our perception of what constitutes a “tinyML device” has shifted from simple
microcontrollers to complex heterogeneous SoCs suited to execute DNNs directly at the extreme
edge in real time and at minimal power cost. These devices provide ultra-low latency and high
energy efficiency necessary to meet the constraints of advanced use cases that can not be satisfied
by cloud solutions. However, how can tinyML hardware keep up with the evolution of the AI
landscape, continuously pushing towards much larger and more complex models? The costs to
develop new accelerators and Neural Processing Units for each evolutive step in AI are hard to
sustain. A possible way forward is given by the open-source model for digital hardware, popularized
by RISC-V: multiple actors – both academic and industrial – collaborate on the development of
digital technology that can benefit all parties. In this presentation, I discuss a 10+-year “quest” to
push the performance and energy efficiency of tinyML further and further by exploiting a fully opensource model based on the PULP Platform initiative. I show how the open-source cooperative model
makes it possible to combine different ideas and contributions in a technologically portable way,
acting as an innovation catalyst and enabling the fast pace of evolution required to keep up with
new ideas in AI within a tiny power budget.
Dr. Francesco Conti
Francesco Conti holds the position of Tenure-Track Assistant Professor in the Department of Electrical, Electronic, and Information Engineering at the University of Bologna, Italy. He completed his Ph.D. in electronic engineering at the same university in 2016 and worked as a Post-Doctoral Researcher at ETH Zürich between 2016 and 2020. His research is centered on hardware acceleration in ultra-low power and highly energy efficient platforms, with a particular focus on System-on-Chips for Artificial Intelligence applications. He is a senior contributor to the open-source PULP Platform project initiative, and has focused also on technology transfer, most notably as a consultant for the development of the GAP9 Systemon-Chip with GreenWaves Technologies. Over his career, he has contributed to over 90 international conference presentations and journal articles, earning him multiple accolades, such as the 2020 IEEE Transactions on Circuits and Systems Darlington Best Paper Award and the 2018 ESWEEK CODES+ISSS Best Paper Award. He is a member of the IEEE Circuits and Systems Society, Solid-State Circuits Society, and Council for Electronic Design Automation, and serves as Associate Editor for the IEEE Transactions on Computer-Aided Design of Circuits and Systems.
Be the first to comment on "Double Tech Talk! Younghyun Kim (Purdue University) And Francesco Conti (University of Bologna)"