Events

Create4Good Innovation Fund 23/24 – Opens 1 Aug 2023

17th International Conference Magnetic Resonance Microscopy 2023

WiOpt 2023 (https://esd.sutd.edu.sg/wiopt2023/), the 21st International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks, will be held during 24-27 August 2023 in Singapore. WiOpt 2023 will showcase state-of-the-art research contributions from different fields in networks. It welcomes original and high-quality submissions related to modeling, performance evaluation, and optimization of networks. The focus includes but is not limited to mobile networks, edge computing, intelligent networks, content-driven networks, cognitive networks, vehicular networks, robotic systems, Internet. In addition to the three-day main conference, which features 3 keynote speeches and approximately 50 paper presentations, WiOpt 2023 will host 5 workshops comprising an additional 50 presentations on the first day. These workshops will delve into cutting-edge subjects within the realms of communications, networking, and AI. The detailed program can be found in https://esd.sutd.edu.sg/wiopt2023/program

ACE X SUTD Founder Matching Program Part II

ARISE: Venture – Regulatory & Certification Considerations for Medtech & Engineering Teams

ARISE: Venture – Team Formation: Building An Ideal Team

HASS Conversations in Design, Technology, and Society Series | Hazardous Data: The Entanglements of Digital Debt in India

ARISE: Venture – Deep Tech Commercialization Process, Strategies and Operation Plans

In this talk, first, I will present an efficient data-driven computational solution and bounding approach for emergency medical service (EMS) fleet allocation and redeployment, i.e., (re-)positioning ambulances to bases to maximize the system’s service level. Using a discrete-event simulator at the core, we first model ambulance allocation as an approximately-submodular-maximization problem, and devise a simple and efficient greedy algorithm that is applicable for both static allocation and dynamic redeployment. Second, to better evaluate the efficiency of dynamic redeployment, we develop novel penalized information-relaxation bounds that avoid incurring the curse of dimensionality common to such approaches. Our bounding methods solve a hitherto open problem and help tighten regret bounds for large classes of online resource allocation problems beyond the EMS setting.

Traditional AI algorithms entail resourceful and reliable computation infrastructure, whereas their efficacy cannot be ensured in many emerging distributed systems (e.g., sensor networks, vehicular networks, edge networks etc.). Deploying AI algorithms in these distributed systems entail many new concerns including fault tolerance, resource efficiency, privacy preservation etc. Furthermore, recent years have witnessed the development of AI algorithms, which provides a new way to improve the intellectuality of the distributed systems such that the efficacy of the systems can be guaranteed in application scenarios with uncertainty. In this talk, by following the above roadmap, I will highlight several research projects conducted by myself and my collaborators in the areas of distributed intelligence, mainly from an algorithmic perspective.