Portfolio item number 1
Short description of portfolio item number 1
Posts by Collection
portfolio
Portfolio item number 2
Short description of portfolio item number 2
publications
Knot mosaics with corner connection tiles
Published in Pi Mu Epsilon Journal, 2023
This paper explores the efficiency of representing knot mosaics using new tiles where the connection points are in the corners, rather than midpoints of each edge.
Recommended citation: Heap, A., Donovan, U., Grossman, R., Laine, N., McDermott, C., Paone, M., & Southcott, D. (2023). Knot Mosaics with Corner Connection Tiles. Pi Mu Epsilon Journal 15, No. 9, 553-568.
Download Paper
A study of gdpr compliance under the transparency and consent framework
Published in Proceedings of the ACM Web Conference 2024, 2024
This paper evaluates whether the Interactive Advertising Bureau’s Transparency and Consent Frmaework truly protects user privacy on the Web and ensures publisher compliance with the General Data Protection Regulation.
Recommended citation: Smith, M., Torres-Agüero, A., Grossman, R., Sen, P., Chen, Y., & Borcea, C. (2024). A Study of GDPR Compliance under the Transparency and Consent Framework. In Proceedings of the ACM on Web Conference 2024 (pp. 1227-1236).
Download Paper
Explaining Clinical Outcome Predictions with Compositional Rationale Extraction Model
Published in 2025 IEEE International Conference on Big Data (BigData), 2025
This paper develops a composition-level rationale extraction model for explainable readmission prediction in a clinical setting.
Recommended citation: Gao, W., Grossman, R. & Chen, Y. (2025). Explaining Clinical Outcome Prediction with Compositional Rationale Extraction Model. In 2025 IEEE International Conference on Big Data (BigData).
Download Paper
Using Salient Object Detection to Identify Manipulative Cookie Banners that Circumvent GDPR
Published in Proceedings of the International AAAI Conference on Web and Social Media, 2026
This paper proposes the application of an unsupervised salient object detection model for detecting aesthetic manipulation in cookie banners. The results include showing that aesthetic manipulation is more prevalent than previously thought, and deserves considerable attention in future privacy regulations.
Recommended citation: Grossman, R., Smith, M., Borcea, C., & Chen, Y. (2026). Using Salient Object Detection to Identify Manipulative Cookie Banners that Circumvent GDPR. Forthcoming in Proceedings of the International AAAI Conference on Web and Social Media (ICWSM).
Download Paper
Inconsistencies in Classification of Online News Articles: A Call for Common Standards in Brand Safety Services.
Published in Proceedings of the International AAAI Conference on Web and Social Media, 2026
This paper documents the high-level of inconsistency in brand safety ratings from three main providers and discusses the implications for publishers and advertisers.
Recommended citation: Smith, M., Grossman, R., Torres-Agüero, A., Sen, P., Chen, Y., & Borcea, C. (2026). Inconsistencies in Classification of Online News Articles: A Call for Common Standards in Brand Safety Services. Forthcoming in Proceedings of the International AAAI Conference on Web and Social Media (ICWSM).
Download Paper
Zero-shot Large Language Models for Automatic Readability Assessment
Published in The 64th Annual Meeting of the Association for Computational Linguistics, 2026
This paper proposes LAURAE for the automatic readability assessment task, an ensemble method combining combining LLM and readability formula scores, where ensemble weights are determined from the LLM’s verbalized confidence scores.
Recommended citation: Grossman, R. & Chen, Y. (2026). Zero-shot Large Language Models for Automatic Readability Assessment. Forthcoming in the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026).
How Generative AI Disrupts Search: An Empirical Study of Google Search, Gemini, and AI Overviews
Published in 2026 ACM SIGIR Conference on Research and Development in Information Retrieval, 2026
This paper shows that Google’s generative search engines significantly differ from Google Search in terms of the retrieved sources for a user query. It further explores what types of content see substantial changes in visibility due to generative search and considers the implications for publishers and users.
Recommended citation: Grossman, R., Liu, S., Chen, M., Smith, M., Borcea, C., & Chen, Y. (2026). How Generative AI Disrupts Search: An Empirical Study of Google Search, Gemini, and AI Overviews. Forthcoming in the ACM SIGIR Conference on Research and Development in Information Retrieval.
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown file that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching Assistant Experience
TA, New Jersey Institute of Technology, Martin Tuchman School of Management, 2026
I have served as a TA for a wide range of courses during my PhD. This includes courses in data mining, machine learning, statistics, and information systems.
Teaching Experience
Undergraduate course, New Jersey Institute of Technology, Martin Tuchman School of Management, 2026
I am the instructor for Management 116: Quantitative Analysis with Application for Business in the Spring of 2026. The class has 43 students, and consists of a lecture and a lab component. I am fully responsible for both portions of the class.