Muhammad Uzair Ul Haq

      Ritratto di Muhammad Uzair Ul Haq

Computer Science and Innovation for Societal Challenges, XXXVII series 

Grant sponsor
Amajor SRL SB

Alessandro Sperduti



Project description
21st century has seen a paradigm shift as the focus is shifting towards globalization. In the competitive market, the organizations tend to be kept up-to-date with the latest technological advancement. Human Resource Management (HRM) is a critical task for any organization or a company whether it is developed or in developing phase. The organization performance heavily relies on the HRM, whether it is for recruitment of new candidates or evaluation of candidates in the organization itself. With the advancement of modern Artificial Intelligence and Machine Learning, it is possible to automate the hiring process that previously had to be carried out by humans. The proposed project aims to automate the recruitment process by using the state-of-the-art tools of computer vision, machine learning and Natural Language Processing (NLP). The proposed technique will remove the subjectivity and accelerate the hiring process in terms of time and cost. The use of AI for candidates’ assessment for hiring process is not new for researchers. However, most of the current AI based HRM suffers from the limited datasets availability, ethical questions related with the fair assessment, and adaptability by the organizations. These factors introduce bias in the ML models and ultimately leads to poor evaluation. The proposed project aims to solve these problems by using machine learning to gather massive data and develop questioners according to company’s need. In the proposed project, the video, audio and textual data of the candidate will be used for assessment. Video data will be analyzed using the computer vision and deep learning approaches for evaluation, the audio will be analyzed using the machine learning techniques and textual information will be assessed using NLP. The results of this project will be a single AI and ML based model which will be used to replace a person as an interviewer.