The 2nd Workshop on Recommender Systems for Human Resources (RecSys in HR 2022) was co-located with the 16th ACM Conference on Recommender Systems, in Seattle, WA, USA, 22nd September 2022.

0:00 Opening by Toine Bogers

4:41 Keynote 1: Robyn Rap (
38:22 Keynote 1 Q&A

53:31 [Paper] Closing the Gender Wage Gap: Adversarial Fairness in Job Recommendation. Presented by Clara Rus
1:09:09 [Paper] End-to-End Bias Mitigation in Candidate Recommender Systems with Fairness Gates. Presented by Adam Mehdi Arafan

1:27:03 Panel
1:28:06 Panelist introductions
1:36:25 Panel topic 1: Global Labor Shortage
1:46:26 Panel topic 2: Fair AI in Practice
2:07:38 Panel topic 3: Multi-stakeholder development
2:32:28 Panel topic 4: Regulation and Accountability
2:42:20 Panel: Closing thoughts

2:49:00 Keynote 2: Liangjie Hong (LinkedIn)
3:28:29 Keynote 2 Q&A

3:36:14 [Paper] Model Threshold Optimization for Segmented Job-Jobseeker Recommendation System. Presented by Yichao Jin
3:52:48 [Paper] Design of Negative Sampling Strategies for Distantly Supervised Skill Extraction. Presented by Jens-Joris Decorte
4:07:47 [Paper] Flexible Job Classification with Zero-Shot Learning. Presented by Thomas Lake
4:22:06 [Paper] Explainable Career Path Predictions using Neural Models. Presented by Roan Schellingerhout

4:35:57 Break-out session (Intro + Recap)
4:45:45 Closing

Virtual paper session (papers accepted at the workshop but not chosen for oral presentations)
4:52:03 [Paper] Skill Extraction from Job Postings using Weak Supervision. Presented by Mike Zhang
5:01:47 [Paper] Using vector representations for matching tasks to skills. Presented by Miriam Amin
5:13:09 [Paper] DGL4C: a Deep Semi-supervised Graph Representation Learning Model for Resume Classification. Presented by Wissem Inoubli
5:23:56 [Paper] Beyond human-in-the-loop: scaling occupation taxonomy at Indeed. Presented by Suyi Tu
5:33:27 [Paper] Automated Personnel Scheduling with Reinforcement Learning and Graph Neural Networks. Presented by Ben Platten