[08.01.2021] Welcome! I coded this website from scratch. Contact me if you see any bugs here. [08.01.2021] Welcome! Contact me if you see any bugs here.
[10.28.2021] My single-authored JPSP is forthcoming. To access the preprint, visit this link. [10.28.2021] Visit here for the preprint of my forthcoming paper.

Dawei "David" Wang

PhD Candidate at Northwestern Kellogg School of Management
CV Linkedin GScholar GScholar

Dawei Wang

PhD Candidate at Northwestern Kellogg
CV Linkedin GScholar GScholar

About Me

I am a PhD candidate in Management & Organizations at Northwestern Kellogg School of Management (expected to graduate in 2022). I am also a visiting PhD student at the Amaral Lab at Northwestern's McCormick School of Engineering. I am on the job market for tenure-track research faculty position starting this academic year (2021-2022). You can access my resume here.
My research focuses on human decision-making, artificial intelligence and bounded rationality. The recent advancements in processing speed, data storage and algorithms have inevitably brought us to an age of artificial intelligence and big data. In light of these discussions, my research aims to explore the limits and bounds of artificial intelligence, as well as theorize the benefits and disadvantages associated with various forms of intelligent systems, such as collective, organizational and human intelligence. In answering these questions, I hope to create a framework to navigate this rich but chaotic digital age.
I will receive my PhD in Management & Organizations from Northwestern Kellogg School of Management in 2022, under the supervision of Ed Zajac. My dissertation committee also includes Luis Amaral, Maryam Kouchaki and Hatim Rahman. I received my MsC in Management & Organizations in 2019 from Northwestern Kellogg School of Management and my BBA in Business Administration in 2014 from National University of Singapore Business School. My education prior to college was received from Raffles Institution.


Artificial intelligence, machine learning, deep learning, intelligent systems, decision-making, limits of rationality, decision-biases, computational social science, Carnegie School.
Machine learning, deep neural network, convolutionary neural network, videometric analysis, ensemble learning, LSTM, transfer learning, adversarial machine learning, StyleGan.
Python, TensorFlow, Stata, HTML5, CSS, SASS, Bootstrap, JavaScript, Amazon AWS.
Wang, D., Nair, K., Kouchaki, M., Zajac, E., & Zhao, X. (2019). A Case of Evolutionary Mismatch? Why Facial Width-to-Height Ratio May Not Predict Behavioral Tendencies. Psychological Science.
Wang, D., Presentation in Self-Posted Facial Images Can Expose Sexual Orientation; Implications for Research and Privacy. Forthcoming at Journal of Personality and Social Psychology, Attitudes and Social Cognition Section.
Ma. A., Chun. JS., Wang, D., & Zhao, X. A Conscientious Leader or a Conscientious Asian? Perceived Conscientiousness is Less Strongly Tied to Leadership Evaluations for Asians Americans (Review and resubmit at Journal of Applied Psychology).
Wang, D., Rahman, H. Algorithmic Face-ism: Uncovering and Mitigating Algorithmic Bias in Decision-Based Facial Recognition Systems (Reject and resubmit at Management Science).
Wang, D., Evaluation of the Generalizability of Deep Learning Algorithm on Predicting Interview Outcomes Using Videos (Presenting at Symposium in the Upcoming 2021 Academy of Management).


At Kellogg, I was mainly involved in assisting Dashun Wang and Hyejin Youn in the Social Dynamics and Network Analysis class, where we teach MBA students social network analysis. Outside of Kellogg, I taught an 8-hour workshop at Peking University—an introduction on different computational methods, including agent-based modelling, machine learning, social network analysis. Informally, I taught my research assistants Python and machine learning. One of my them successfully transitioned from chemistry to data science through my help.

My Apps

I assisted the development of two open-source, non-commercial web applications, mostly used in hiring situtaions. I built the AI technology in these applications, as well as helped in the development of these platforms. These apps are built to test the limits and objectiveness of AI technology. They are both currently under beta-testing.

VuePrep - Online interview preparation platform

VuePrep is a smart online application to help people prepare for online interviews. It provides instant feedback, unlimited playbacks of past sessions and customizable interview questions. It is a helpful tool for job candidates to ace the online interview format.

Rugoo - AI-powered online interview platform

Rugoo is an AI-powered online interview platform. It is based on similar technology as VuePrep as well as other automated hiring platforms. It provides potential recruiters with automated insights and ability to quickly evaluate interview candidates. The goal of creating this website is to identify potential biases in automated hiring contexts.