Title: Skill-oriented Task Allocation in Crowdsourcing

Speaker: Riya Samanta, Ph.D student at IIT Kharagpur

Date: 02/25/2022, 10:00 AM (CDT)

Abstract: A crowdsourcing (CS) system has four basic components: a client, a crowd-worker, and a platform. Clients submit "tasks," and the CS platform selects and assigns crowd-workers to those "tasks." Distributing assignments to potential crowd-workers not only improves job success rates and quality results, but also encourages long-term engagement. Allocating jobs to the most suitable crowd-workers has always been a classic CS problem. Particularly when it comes to complex tasks, skill become a primary criteria in the decision process. However, we see that research findings overlook the importance of workers' skill availability, potential, and willingness in making allocation decisions. Again, presently, due to the rapid growth of skill-based volunteerism, several new unique challenges are also coming up. Because volunteers are not bound workers, They have their own preferences, like work location and type, timings, remuneration, etc. Thus, choosing qualified volunteers for skilled activities and establishing a uniform working schedule for productive teamwork is always a difficulty. In this presentation, I'm going to focus on two research questions: How to achieve optimal online skill-oriented, complex task allocation for CS while considering crowd-workers’ willingness and budget constraints into account and keeping the CS platform’s utility gain high? And how to allocate difficult tasks optimally while considering volunteers' location and working preferences to maximize the CS platform's overall utility? Finally, I will discuss my solutions to these issues.

Bio: Riya Samanta received her BSc., B.Tech, and M.Tech degrees in computer science from the University of Calcutta, India, in 2014, 2017, and 2019 respectively. She has achieved University Rank 1 (Gold Medal) in her MTech curriculum. Riya was awarded the prestigious DST Inspire Fellowship and a UGC Research Fellowship for her doctoral study. She is currently pursuing a Ph.D. degree in computer science and engineering from the Indian Institute of Technology Kharagpur, India. Her research interests include crowdsourcing, task allocation optimization, algorithms, and matchmaking. And apart from academia, she is a profound Classical and Western dancer.