Publications & Research

• Decision-Focused Machine Learning for Optimal Business Resource Allocation Under Uncertainty (Matthew Lyle)
• Debiasing LLM-Generated Event Studies: Correcting Market Response Bias from AI-Generated Observations (William Schmidt, with Shawn Mankad)
• Augmenting Conjoint Analysis with Digital Twins (David Schweidel)
• Scaling CourseChat: A Self-Serve AI Teaching Assistant Platform for Faculty (Educational Grant) (William Mann and David Schweidel)
• Investing with Intelligence: Productivity and Creativity in Innovation with AI (Zhishuo Han, with faculty sponsors Wei Jiang and Gonzalo Maturana)
• Derivatives Usage by Mutual Funds in Stressed Market Conditions (Avinash Pandey, with faculty sponsor Tarun Chordia)
• Measuring AI Scribe's Financial Returns to Digital Investment in Healthcare (Yixuan Wang, with faculty sponsor Ruomeng Cui and collaborator Anwar Ferdinand)

2026

• Applying large language models to sponsored search advertising. M Reisenbichler, T Reutterer, DA Schweidel. Marketing Science 45(1), 123–141.
• Can GenAI Move from Individual Use to Collaborative Work? Experiences, Challenges, and Opportunities of Coordinating GenAI into Collaborative Newswork. Q Xiao, Q Hu, J Xiao, H Cao, H Shen. Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems.
• Commentaries on “Generative grounded theory (GGT): Inductive theory building in the age of generative AI”. G Tomaino, DA Schweidel, PY Dolbec, E Fischer, AN Smith, S Puntoni, et al. Journal of Consumer Psychology.
• Deep reinforcement learning for optimal portfolio allocation: A comparative study with mean-variance optimization. S Sood, K Papasotiriou, M Vaiciulis, T Balch. arXiv:2602.17098.
• From Production to Discernment: Evaluation-Centered Organization Design Under AI-Enabled Production Abundance. H Cao, R Zhu, H Shen, Q Xiao. Cornell SC Johnson College of Business Research Paper.
• From replication to redesign: Exploring pairwise comparisons for LLM-based peer review. Y Zhang, H Zhang, W Ji, T Hua, N Haber, H Cao, W Liang. Advances in Neural Information Processing Systems 38, 11778–11805.
• Human-AI Collaboration in Science at Scale: A Global Large-scale Randomized Field Experiment. B Wang, W Liang, J Xue, Y Zhang, H Cao, D Wang, Y Yin. arXiv:2605.24180.
• Human–AI Collaboration in Science at Scale: A Large-Scale Randomized Field Experiment. B Wang, W Liang, J Xue, Y Zhang, H Cao, D Wang, Y Yin. Academy of Management Proceedings 2026(1), 21478.
• Limited or Biased: Modeling Subrational Human Investors in Financial Markets. P Liu, K Dwarakanath, S Vyetrenko, T Balch. Journal of Behavioral Finance 27(2), 157–180.
• Method and system for detecting anomalous behavior in stream data. T Balch, V Bustamante, M Howard, M Kawawa-Beaudan, et al. US Patent 12,585,762.
• Method and system for forecasting time series by image inpainting. M Veloso, Z Zeng, N Cohen, S Sood, J Maat, T Balch. US Patent 12,541,828.
• Method and system for performing table question-answering tasks while preserving data security. W Watson, N Cho, T Balch, M Veloso. US Patent 12,596,838.
• Multi-agent teams hold experts back. A Pappu, B El, H Cao, C di Nolfo, Y Sun, M Cao, J Zou. arXiv:2602.01011.
• Picture perfect. M Heitmann, TPJ Jansen, M Reisenbichler, DA Schweidel.
• Preparing your brand for agentic AI. OA Acar, DA Schweidel. Harvard Business Review.
• Pricing of Multidimensional Skills in IT Labor Market: Complementarities between AI and Traditional IT Skills. S Nath, J Yeo, A Bharadwaj, S Bharadwaj. Available at SSRN 6188398.
• Seeing the Goal, Missing the Truth: Human Accountability for AI Bias. S Cao, W Jiang, H Xu. arXiv:2602.09504.
• Targeted Automation and Sustaining Human-AI Learning. C Imdahl, W Schmidt, K Hoberg. Production and Operations Management 35(4), 1520–1538.
• The Impact of AI Search on the Online Content Ecosystem: Evidence from Google and Reddit. P Zhang, R Cui, D Zhang. arXiv:2605.16428.
• Trusting AI Agents: Uncertainty Reduction by Design. E Hermann, S Puntoni, DA Schweidel. The Wharton School Research Paper.
• Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration. J Li, Y Hou, L Lin, R Zhu, H Cao, A El Ali. Proceedings of the 5th Annual Symposium on Human-Computer Interaction for Work.
• When your boss is an AI Bot: Exploring opportunities and risks of manager clone agents in the future workplace. Q Hu, Q Xiao, H Cao, H Shen. Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems.

2025

• Adaptagent: Adapting multimodal web agents with few-shot learning from human demonstrations. G Verma, R Kaur, N Srishankar, Z Zeng, T Balch, M Veloso. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics.
• AI and the Extended Workday: Productivity, Contracting Efficiency, and Distribution of Rents. W Jiang, J Park, RJ Xiao, S Zhang. National Bureau of Economic Research.
• AI Driven Fraud, Financial and Cybercrime: Emerging Threats and The Evolving Landscape of AI versus AI. E Kurshan, T Balch, D Mehta, D Byrd.
• AI Hasn't Fixed Teamwork, But It Shifted Collaborative Culture: A Longitudinal Study in a Project-Based Software Development Organization (2023–2025). Q Xiao, X Hu, M Whiting, A Karunakaran, H Shen, H Cao. arXiv:2509.10956.
• Auditing and enforcing conditional fairness via optimal transport. M Ghassemi, A Mishler, N Dalmasso, L Zhang, V Potluru, T Balch, et al. Proceedings of the AAAI Conference on Artificial Intelligence 39(16), 16808–.
• Beyond Fair Predictions: Auditing and Mitigating Disparity in Post-Hoc Model Explanations. IS Umuhoza, R Garg. 2025 IEEE 4th International Conference on Signal, Control and Communication.
• Blind spots in broad strokes: Caveats for the use of LLMs in marketing research. M Stromberg, WW Moe, T Reutterer, DA Schweidel. Available at SSRN 5145114.
• Calibrating non-identifiable high-dimensional simulation models: A framework via eligibility set. Y Bai, T Balch, H Chen, D Dervovic, H Lam, S Vyetrenko. ACM Transactions on Modeling and Computer Simulation 36(1), 1–50.
• Can GenAI Move from Individual Use to Collaborative Work? Experiences, Challenges, and Opportunities of Integrating GenAI into Collaborative Newsroom Routines. Q Xiao, J Xiao, H Cao, H Shen. arXiv:2509.10950.
• Conversational AI: The next frontier of digital platform monetization. E Hermann, S Puntoni, DA Schweidel. The Wharton School Research Paper.
• Corporate Finance and Governance with Artificial Intelligence: Old and New. W Jiang. Available at SSRN 5290033.
• Domain Anchorage in GPT-4: A Computational Linguistic Analysis of Lexicographic Profiling and Its Implications for Unintended Information Dissemination. L Challappa, Z Zhang, R Garg.
• Domain anchorage in LLMs: Lexicon profiling and unintended information leakage. L Challappa, Z Zhang, R Garg. Data & Policy 7, e73.
• Financial executives' responses to the use of artificial intelligence in financial reporting and auditing. P Csere, C Estep, E Griffith, N MacKenzie. Current Issues in Auditing, 1–9.
• Generative AI May Be Good For Artists: Understanding the Impact of Artistic Style on Preference and Willingness to Pay. W Wang, JJ Bell, JP Dotson, DA Schweidel.
• HashMark: Watermarking Tabular/Synthetic Data For Machine Learning Via Cryptographic Hash Functions. H Karthikeyan, L de Castro, A Polychroniadou, M Veloso, T Balch. NeurIPS 2025 Workshop: Generative AI in Finance.
• Is all the information in the price? LLM embeddings versus the EMH in stock clustering. B Wang, G Johnson, M Hybinette, T Balch. arXiv:2509.01590.
• LAW: Legal agentic workflows for custody and fund services contracts. W Watson, N Cho, N Srishankar, Z Zeng, L Cecchi, D Scott, et al. Proceedings of the 31st International Conference on Computational Linguistics.
• Lets-c: Leveraging text embedding for time series classification. R Kaur, Z Zeng, T Balch, M Veloso. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics.
• Method and system for analyzing natural language data by using domain-specific language models. N Cho, Z Zeng, W Watson, M Veloso, M Mackay, T Balch. US Patent 12,298,970.
• Method and system for automatic workflow generation by large language models. Z Zeng, W Watson, S Rahimi, T Balch, M Veloso. US Patent 12,399,691.
• Method and system for differentially private learning of Hawkes processes. M Ghassemi, E Kreacic, N Dalmasso, V Potluru, T Balch, et al. US Patent 12,223,088.
• Method and system for generating keywords. K Papasotiriou, T Balch, S Sood, S Reynolds, L Yong, N Akalin, et al. US Patent 12,235,907.
• Method and system for multi-modal time-series retrieval through latent space projections. A Coletta, F Elizabeth, S Gopalakrishnan, S Vyetrenko, T Balch, et al. US Patent 12,475,133.
• Mind the gaps: auditing and reducing group inequity in large-scale mobility prediction. A Kumar, H Zhang, DA Schweidel, W Yeoh. arXiv:2510.26940.
• Picture perfect: Engaging customers with visual generative AI. TPJ Jansen, M Heitmann, M Reisenbichler, DA Schweidel.
• Prototypical human-AI collaboration behaviors from LLM-Assisted writing in the wild. S Mysore, D Das, H Cao, B Sarrafzadeh. Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing.
• Quantifying large language model usage in scientific papers. W Liang, Y Zhang, Z Wu, H Lepp, W Ji, X Zhao, H Cao, et al. Nature Human Behaviour 9(12), 2599–2609.
• Snack and Snap: A Novel Recipe for Yelp Reviews with Explainable AI. Y Byarugaba, B Wang, R Garg.
• System and method for generating order agnostic dynamic citation network. W Watson, N Cho, T Balch, M Veloso. US Patent 12,443,662.
• System and method for watermarking tabular data while obscuring underlying data for improving data integrity and security. V Potluru, T Balch, M Veloso. US Patent 12,488,135.
• The agentic regulator: risks for AI in finance and a proposed agent-based framework for governance. E Kurshan, T Balch, D Byrd. arXiv:2512.11933.
• The Impact of Hospital Algorithm Adoption on Care Delivery, Outcomes, and Equity. Q Wang, J Liu, A Bharadwaj, R Aljafari, A Goyal.
• The widespread adoption of large language model-assisted writing across society. W Liang, Y Zhang, M Codreanu, J Wang, H Cao, J Zou. Patterns 6(12).
• Using colocation networks to predict customer acquisition: A deep heterogeneous network representation learning approach. H Zhang, K Zhang, DA Schweidel. Available at SSRN 5264915.
• Using computer vision to measure design similarity: An application to design rights. E Amoncio, T Chan, C Storz. Research Policy 54(9), 105309.
• Vibe Coding for UX Design: Understanding UX Professionals' Perceptions of AI-Assisted Design and Development. J Li, Y Hou, L Lin, R Zhu, H Cao, A El Ali. arXiv:2509.10652.

2024

• Abides-economist: Agent-based simulator of economic systems with learning agents. K Dwarakanath, T Balch, S Vyetrenko. arXiv:2402.09563.
• AI in investment analysis: LLMs for equity stock ratings. K Papasotiriou, S Sood, S Reynolds, T Balch. Proceedings of the 5th ACM International Conference on AI in Finance, 419–427.
• AI versus AI in financial crimes & detection: GenAI crime waves to co-evolutionary AI. E Kurshan, D Mehta, T Balch. Proceedings of the 5th ACM International Conference on AI in Finance, 745–751.
• AI versus AI in Financial Crimes and Detection: GenAI Crime Waves to Co-Evolutionary AI. E Kurshan, D Mehta, B Bruss, T Balch. arXiv:2410.09066.
• Applied AI for finance and accounting: Alternative data and opportunities. SS Cao, W Jiang, LG Lei. Pacific-Basin Finance Journal 84, 102307.
• Behavioral Sequence Modeling with Ensemble Learning. M Kawawa-Beaudan, S Sood, S Palande, G Mani, T Balch, M Veloso. arXiv:2411.02174.
• Boosted generalized normal distributions: Integrating machine learning with operations knowledge. R Gurlek, F de Véricourt, DKK Lee. arXiv:2407.19092.
• Can large language models provide useful feedback on research papers? A large-scale empirical analysis. W Liang, Y Zhang, H Cao, B Wang, D Ding, X Yang, K Vodrahalli, et al. NEJM AI 1(8).
• Differential privacy for axe obfuscation. A Polychroniadou, T Balch, G Cipriani. US Patent 12,100,044.
• Distributionally and adversarially robust logistic regression via intersecting wasserstein balls. A Selvi, E Kreacic, M Ghassemi, V Potluru, T Balch, M Veloso. arXiv:2407.13625.
• Downstream task-oriented generative model selections on synthetic data training for fraud detection models. Y Cheng, C Wang, V Potluru, T Balch, G Cheng. arXiv:2401.00974.
• Empirical equilibria in agent-based economic systems with learning agents. K Dwarakanath, S Vyetrenko, T Balch. arXiv:2408.12038.
• Ensemble methods for sequence classification with hidden Markov models. M Kawawa-Beaudan, S Sood, S Palande, G Mani, T Balch, M Veloso. arXiv:2409.07619.
• Evaluating and Designing Computing Systems for the Future of Work. H Cao. PhD dissertation, Stanford University.
• Evaluating large language models on time series feature understanding: A comprehensive taxonomy and benchmark. E Fons, R Kaur, S Palande, Z Zeng, T Balch, M Veloso, S Vyetrenko. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing.
• Fair wasserstein coresets. Z Xiong, N Dalmasso, S Sharma, F Lecue, D Magazzeni, V Potluru, T Balch, et al. Advances in Neural Information Processing Systems 37, 132–168.
• Fairwasp: Fast and optimal fair wasserstein pre-processing. Z Xiong, N Dalmasso, A Mishler, V Potluru, T Balch, M Veloso. Proceedings of the AAAI Conference on Artificial Intelligence 38(14), 16120–.
• How do financial executives respond to the use of artificial intelligence in financial reporting and auditing? C Estep, E Griffith, N MacKenzie. Review of Accounting Studies 29(3), 2798–2831.
• Lets-c: Leveraging language embedding for time series classification. R Kaur, Z Zeng, T Balch, M Veloso. arXiv:2407.06533.
• LLM-driven imitation of subrational behavior: Illusion or reality? A Coletta, K Dwarakanath, P Liu, S Vyetrenko, T Balch. arXiv:2402.08755.
• Mapping the increasing use of LLMs in scientific papers. W Liang, Y Zhang, Z Wu, H Lepp, W Ji, X Zhao, H Cao, S Liu, S He, et al. arXiv:2404.01268.
• Measuring Sustainability with AI. W Jiang, M Wang, B Yang. Artificial Intelligence, Finance, and Sustainability: Economic, Ecological.
• Measuring Sustainability with AI. M Wang, B Yang, W Jiang. Available at SSRN 5364388.
• Microsecagg: Streamlined single-server secure aggregation. Y Guo, A Polychroniadou, E Shi, D Byrd, T Balch. Proceedings on Privacy Enhancing Technologies.
• Monitoring AI-modified content at scale: A case study on the impact of ChatGPT on AI conference peer reviews. W Liang, Z Izzo, Y Zhang, H Lepp, H Cao, X Zhao, L Chen, et al. Proceedings of the 41st International Conference on Machine Learning.
• Moving beyond ChatGPT: Applying large language models in marketing contexts. DA Schweidel, M Reisenbichler, T Reutterer. NIM Marketing Intelligence Review 16(1), 24–29.
• Realtime, multimodal invasive ventilation risk monitoring using language models and BoXHED. A Pakbin, A Su, DKK Lee, BJ Mortazavi. arXiv:2410.03725.
• Segmenting Bitcoin Transactions for Price Movement Prediction. Y Zhang, R Garg, LL Golden, PL Brockett, A Sharma. Journal of Risk and Financial Management 17(3), 128.
• Shining a Light on Hurricane Damage Estimation via Nighttime Light Data: Pre-Processing Matters. N Thomas, S Rahimi, A Vapsi, C Ansell, E Christie, D Borrajo, T Balch, et al. IGARSS 2024–2024 IEEE International Geoscience and Remote Sensing Symposium.
• Six levels of privacy: A framework for financial synthetic data. T Balch, V Potluru, D Paramanand, M Veloso. arXiv:2403.14724.
• Soft Governance Across Digital Platforms Using Transparency. AR Doshi, W Schmidt. Strategy Science 9(2), 185–204.
• Tadacap: Time-series adaptive domain-aware captioning. E Fons, R Kaur, Z Zeng, S Palande, T Balch, S Vyetrenko, M Veloso. Proceedings of the 5th ACM International Conference on AI in Finance, 54–62.
• The Impact of Generative Artificial Intelligence on Higher Education: Disruption or Seamless Integration? R Garg. Available at SSRN 4762814.
• Tm-okc: An unsupervised topic model for text in online knowledge communities. D Zhang, K Zhang, Y Yang, DA Schweidel. MIS Quarterly 48(3), 931–978.
• Variational neural stochastic differential equations with change points. Y El-Laham, Z Sun, H Zhu, T Balch, S Vyetrenko. arXiv:2411.00635.

2023

• A Model-Based Synthetic Stock Price Time Series Generation Framework. H Zhu, S Vyetrenko, T Balch. arXiv:2311.02209.
• ATMS: Algorithmic Trading-Guided Market Simulation. S Wei, A Coletta, S Vyetrenko, T Balch. arXiv:2309.01784.
• Automated alignment: Guiding visual generative AI for brand building and customer engagement. T Jansen, M Heitmann, M Reisenbichler, DA Schweidel. Available at SSRN 4656622.
• Breaking out of the ivory tower: A large-scale analysis of patent citations to HCI research. H Cao, Y Lu, Y Deng, D McFarland, M Bernstein. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. (Best Paper Award)
• Comparing scalable strategies for generating numerical perspectives. H Cao, S Spatharioti, D Goldstein, J Hofman. arXiv:2308.01535.
• Differentially private synthetic data using kd-trees. E Kreacic, N Nouri, V Potluru, T Balch, M Veloso. Uncertainty in Artificial Intelligence, 1143–1153.
• Efficient event series data modeling via first-order constrained optimization. N Dalmasso, R Zhao, M Ghassemi, V Potluru, T Balch, M Veloso. Proceedings of the 4th ACM International Conference on AI in Finance, 463–471.
• Exploring the Effectiveness of GPT Models in Test-Taking: A Case Study of the Driver's License Knowledge Test. S Rahimi, T Balch, M Veloso. arXiv:2308.11827.
• Financial time series forecasting using CNN and transformer. Z Zeng, R Kaur, S Siddagangappa, S Rahimi, T Balch, M Veloso. arXiv:2304.04912.
• Flowmind: automatic workflow generation with LLMs. Z Zeng, W Watson, N Cho, S Rahimi, S Reynolds, T Balch, M Veloso. Proceedings of the 4th ACM International Conference on AI in Finance, 73–81.
• From pixels to predictions: Spectrogram and vision transformer for better time series forecasting. Z Zeng, R Kaur, S Siddagangappa, T Balch, M Veloso. Proceedings of the 4th ACM International Conference on AI in Finance, 82–90.
• Generative AI and artists: Consumer preferences for style and fair compensation. W Wang, JJ Bell, JP Dotson, DA Schweidel. Available at SSRN 4428509.
• Generative AI has an intellectual property problem. G Appel, J Neelbauer, DA Schweidel. Harvard Business Review 7, 10–16.
• HiddenTables and PyQTax: A cooperative game and dataset for TableQA to ensure scale and data privacy across a myriad of taxonomies. W Watson, N Cho, T Balch, M Veloso. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing.
• How new ideas diffuse in science. M Cheng, D Smith, X Ren, H Cao, S Smith, D McFarland. American Sociological Review 88(3), 522–561.
• How to talk when a machine is listening: Corporate disclosure in the age of AI. S Cao, W Jiang, B Yang, AL Zhang. The Review of Financial Studies 36(9), 3603–3642.
• Intags: Interactive agent-guided simulation. S Wei, A Coletta, S Vyetrenko, T Balch. arXiv:2309.01784.
• K-SHAP: Policy clustering algorithm for anonymous multi-agent state-action pairs. A Coletta, S Vyetrenko, T Balch. arXiv:2302.11996.
• Leveraging AI for content generation: A customer equity perspective. DA Schweidel, M Reisenbichler, T Reutterer, K Zhang.
• Multi-modal financial time-series retrieval through latent space projections. T Bamford, A Coletta, E Fons, S Gopalakrishnan, S Vyetrenko, T Balch, et al. Proceedings of the 4th ACM International Conference on AI in Finance, 498–506.
• On ChatGPT and beyond: How generative artificial intelligence may affect research, teaching, and practice. R Peres, M Schreier, D Schweidel, A Sorescu. International Journal of Research in Marketing 40(2), 269–275.
• Once burned, twice shy? The effect of stock market bubbles on traders that learn by experience. H Zhu, S Vyetrenko, K Dwarakanath, T Balch, S Grundl, D Byrd. 2023 Winter Simulation Conference (WSC), 291–302.
• Predicting real-time, recurrent adverse invasive ventilation from clinical data streams. A Pakbin, Z Nowroozilarki, DKK Lee, BJ Mortazavi. 2023 IEEE 19th International Conference on Body Sensor Networks (BSN), 1–4.
• Privacy-preserving energy-based generative models for marginal distribution protection. R Tillman, T Balch, M Veloso. Transactions on Machine Learning Research.
• Synthetic data applications in finance. V Potluru, D Borrajo, A Coletta, N Dalmasso, Y El-Laham, E Fons, et al. arXiv:2401.00081.
• The rise of open science: Tracking the evolution and perceived value of data and methods link-sharing practices. H Cao, J Dodge, K Lo, D McFarland, L Wang. arXiv:2310.03193.
• Transparency as delayed observability in multi-agent systems. K Dwarakanath, S Vyetrenko, T Balch, T Oyebode. 2023 Winter Simulation Conference (WSC), 279–290.
• User Experience Design Professionals' Perceptions of Generative Artificial Intelligence. J Li, H Cao, L Lin, Y Hou, R Zhu. arXiv:2309.15237.
• What's in a Name? The Impact of Artist Names in Image Generative AI Prompts. W Wang, JJ Bell, JP Dotson, DA Schweidel. SSRN.

2022

• Addressing Extreme Market Responses Using Secure Aggregation. S Mazloom, A Polychroniadou, T Balch. Proceedings of the Third ACM International Conference on AI in Finance, 192–198.
• AI and procurement. R Cui, M Li, S Zhang. Manufacturing & Service Operations Management 24(2), 691–706.
• Beyond virtual bazaar: How social commerce promotes inclusivity for the traditionally underserved community in Chinese developing regions. Z Chen, H Cao, X Lan, Z Lu, Y Li. Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems.
• Collusion resistant federated learning with oblivious distributed differential privacy. D Byrd, V Mugunthan, A Polychroniadou, T Balch. Proceedings of the Third ACM International Conference on AI in Finance, 114–122.
• CTMSTOU driven markets: simulated environment for regime-awareness in trading policies. S Amrouni, A Moulin, T Balch. arXiv:2202.00941.
• Differentially Private Learning of Hawkes Processes. M Ghassemi, E Kreacic, N Dalmasso, V Potluru, T Balch, M Veloso. arXiv:2207.13741.
• Efficient calibration of multi-agent simulation models from output series with bayesian optimization. Y Bai, H Lam, T Balch, S Vyetrenko. Proceedings of the Third ACM International Conference on AI in Finance, 437–445.
• Equitable marketplace mechanism design. K Dwarakanath, S Vyetrenko, T Balch. Proceedings of the Third ACM International Conference on AI in Finance, 232–239.
• Evaluating human-language model interaction. M Lee, M Srivastava, A Hardy, J Thickstun, E Durmus, A Paranjape, et al. arXiv:2212.09746.
• Fast learning of multidimensional hawkes processes via frank-wolfe. R Zhao, N Dalmasso, M Ghassemi, V Potluru, T Balch, M Veloso. arXiv:2212.06081.
• Frontiers: Supporting content marketing with natural language generation. M Reisenbichler, T Reutterer, DA Schweidel, D Dan. Marketing Science 41(3), 441–452.
• Learning to simulate realistic limit order book markets from data as a world agent. A Coletta, A Moulin, S Vyetrenko, T Balch. Proceedings of the Third ACM International Conference on AI in Finance, 428–436.
• MicroFedML: Privacy Preserving Federated Learning for Small Weights. Y Guo, A Polychroniadou, E Shi, D Byrd, T Balch. IACR Cryptology ePrint Archive 2022, 714.
• Online learning for mixture of multivariate hawkes processes. M Ghassemi, N Dalmasso, S Lamba, V Potluru, T Balch, S Shah, et al. Proceedings of the Third ACM International Conference on AI in Finance, 506–513.
• Optimal stopping with Gaussian processes. K Dwarakanath, D Dervovic, P Tavallali, S Vyetrenko, T Balch. Proceedings of the Third ACM International Conference on AI in Finance, 497–505.
• Practitioners versus users: A value-sensitive evaluation of current industrial recommender system design. Z Chen, J Piao, X Lan, H Cao, C Gao, Z Lu, Y Li. Proceedings of the ACM on Human-Computer Interaction 6(CSCW2), 1–32.
• Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulations. N Vadori, L Ardon, S Ganesh, T Spooner, S Amrouni, J Vann, M Xu, et al. Mathematical Finance.
• Using continuous 3D tracking and remote video to enhance management of social groups of rhesus monkeys. R Roberts, T Balch, D Byrd, S Gilliland, B Hrolenok, J Rehg, K Wallen. American Journal of Primatology 84.
• Using Topic Modeling to Examine Consumer Mobility Patterns: An Application to the COVID-19 Pandemic. N Zhong, KKB Kim, DA Schweidel. Available at SSRN 4487086.

2021

• ABIDES-gym: gym environments for multi-agent discrete event simulation and application to financial markets. S Amrouni, A Moulin, J Vann, S Vyetrenko, T Balch, M Veloso. Proceedings of the Second ACM International Conference on AI in Finance, 1–9.
• Artificial intelligence research in finance: discussion and examples. M Veloso, T Balch, D Borrajo, P Reddy, S Shah. Oxford Review of Economic Policy 37(3), 564–584.
• Boosted nonparametric hazards with time-dependent covariates. DKK Lee, N Chen, H Ishwaran. The Annals of Statistics 49(4), 2101.
• BoXHED2.0: Scalable boosting of dynamic survival analysis. A Pakbin, X Wang, BJ Mortazavi, DKK Lee. arXiv:2103.12591.
• Calibrating over-parametrized simulation models: A framework via eligibility set. Y Bai, T Balch, H Chen, D Dervovic, H Lam, S Vyetrenko. arXiv:2105.12893.
• Community value prediction in social E-commerce. G Zhang, Y Li, Y Yuan, F Xu, H Cao, Y Xu, D Jin. Proceedings of the Web Conference 2021, 2958–2967.
• Context-aware semantic annotation of mobility records. H Wang, Y Li, J Lin, H Cao, D Jin. ACM Transactions on Knowledge Discovery from Data 16(3), 1–20.
• Deep video prediction for time series forecasting. Z Zeng, T Balch, M Veloso. Proceedings of the Second ACM International Conference on AI in Finance, 1–7.
• Demographics of mobile app usage: Long-term analysis of mobile app usage. Z Tu, H Cao, E Lagerspetz, Y Fan, H Flores, S Tarkoma, P Nurmi, Y Li. CCF Transactions on Pervasive Computing and Interaction 3(3), 235–252.
• Efficient Calibration of Multi-Agent Market Simulators from Time Series with Bayesian Optimization. Y Bai, H Lam, S Vyetrenko, T Balch. CoRR.
• From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses. S Cao, W Jiang, J Wang, B Yang. NBER working paper 28800.
• From Man vs. Machine to Man+ Machine: The Art and AI of Stock Analyses. J Wang, S Cao, B Yang, W Jiang.
• How to Talk When a Machine is Listening?: Corporate Disclosure in the Age of AI. S Cao, W Jiang, B Yang, AL Zhang. Cambridge Centre for Alternative Finance.
• Large scale analysis of multitasking behavior during remote meetings. H Cao, C Lee, S Iqbal, M Czerwinski, P Wong, S Rintel, B Hecht, et al. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. (Honorable Mention)
• Learning from home: A mixed-methods analysis of live streaming based remote education experience in Chinese colleges during the COVID-19 pandemic. Z Chen, H Cao, Y Deng, X Gao, J Piao, F Xu, Y Zhang, Y Li. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems.
• Learning to classify and imitate trading agents in continuous double auction markets. M Mahfouz, T Balch, M Veloso, D Mandic. Proceedings of the Second ACM International Conference on AI in Finance, 1–8.
• Learning who is in the market from time series: market participant discovery through adversarial calibration of multi-agent simulators. V Storchan, S Vyetrenko, T Balch. arXiv:2108.00664.
• My team will go on: Differentiating high and low viability teams through team interaction. H Cao, V Yang, V Chen, Y Lee, L Stone, N Diarrassouba, M Whiting, et al. Proceedings of the ACM on Human-Computer Interaction 4(CSCW3), 1–27. (Best Paper Award)
• Persuade to click: Context-aware persuasion model for online textual advertisement. Y Yuan, F Xu, H Cao, G Zhang, P Hui, Y Li, D Jin. IEEE Transactions on Knowledge and Data Engineering 35(2), 1938–1951.
• Profit equitably: an investigation of market maker's impact on equitable outcomes. K Dwarakanath, S Vyetrenko, T Balch. Proceedings of the Second ACM International Conference on AI in Finance, 1–8.
• Real-time mortality prediction using MIMIC-IV ICU data via boosted nonparametric hazards. Z Nowroozilarki, A Pakbin, J Royalty, DKK Lee, BJ Mortazavi. 2021 IEEE EMBS International Conference on Biomedical and Health Informatics.
• Stability effects of arbitrage in exchange traded funds: An agent-based model. M Shearer, D Byrd, T Balch, M Wellman. Proceedings of the Second ACM International Conference on AI in Finance, 1–9.
• Supporting content marketing with natural language generation. M Reisenbichler, T Reutterer, D Schweidel, D Dan. Marketing Science Institute Working Paper.
• Theory and software for boosted nonparametric hazard estimation. DKK Lee, N Chen, H Ishwaran, X Wang, A Pakbin, B Mortazavi, H Zhao. Survival Prediction — Algorithms, Challenges and Applications, 149–158.
• Towards realistic market simulations: a generative adversarial networks approach. A Coletta, M Prata, M Conti, E Mercanti, N Bartolini, A Moulin, S Vyetrenko, et al. Proceedings of the Second ACM International Conference on AI in Finance, 1–9.
• Understanding the long-term dynamics of mobile app usage context via graph embedding. Y Fan, Z Tu, T Li, H Cao, T Xia, Y Li, X Chen, L Zhang. IEEE Transactions on Knowledge and Data Engineering 35(3), 3180–3194.
• Visual time series forecasting: an image-driven approach. S Sood, Z Zeng, N Cohen, T Balch, M Veloso. Proceedings of the Second ACM International Conference on AI in Finance, 1–9.
• ViziTex: Interactive visual sense-making of text corpora. N Raman, S Shah, T Balch, M Veloso. Proceedings of the Second Workshop on Data Science with Human in the Loop.
• You recommend, I buy: How and why people engage in instant messaging based social commerce. H Cao, Z Chen, M Cheng, S Zhao, T Wang, Y Li. Proceedings of the ACM on Human-Computer Interaction 5(CSCW1), 1–25.

2020

• "What Apps Did You Use?": Understanding the Long-term Evolution of Mobile App Usage. T Li, M Zhang, H Cao, Y Li, S Tarkoma, P Hui. Proceedings of The Web Conference 2020.
• ABIDES: Towards high-fidelity multi-agent market simulation. D Byrd, M Hybinette, T Balch. Proceedings of the 2020 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation.
• BoXHED: Boosted eXact hazard estimator with dynamic covariates. X Wang, A Pakbin, B Mortazavi, H Zhao, DKK Lee. International Conference on Machine Learning, 9973–9982.
• Capturing changes in social media content: A multiple latent changepoint topic model. N Zhong, DA Schweidel. Marketing Science 39(4), 827–846.
• Generating synthetic data in finance: opportunities, challenges and pitfalls. S Assefa, D Dervovic, M Mahfouz, R Tillman, T Balch, P Reddy, et al. Proceedings of the First ACM International Conference on AI in Finance, 1–8.
• Get real: Realism metrics for robust limit order book market simulations. S Vyetrenko, D Byrd, N Petosa, M Mahfouz, D Dervovic, M Veloso, et al. Proceedings of the First ACM International Conference on AI in Finance, 1–8.
• HealthWalks: Sensing fine-grained individual health condition via mobility data. Z Lin, S Lyu, H Cao, F Xu, Y Wei, H Samet, Y Li. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.
• MAS-GAN: Adversarial Calibration of Multi-Agent Market Simulators. V Storchan, S Vyetrenko, T Balch.
• Real-Time Prediction of Online False Information Purveyors and their Characteristics. A Doshi, S Raghavan, W Schmidt. Available at SSRN 3725919.
• Some people aren't worth listening to: periodically retraining classifiers with feedback from a team of end users. J Lockhart, S Assefa, T Balch, M Veloso. arXiv:2004.13152.
• SURF: Improving classifiers in production by learning from busy and noisy end users. J Lockhart, S Assefa, A Alajdad, A Alexander, T Balch, M Veloso. Proceedings of the First ACM International Conference on AI in Finance, 1–8.
• Trading via image classification. N Cohen, T Balch, M Veloso. Proceedings of the First ACM International Conference on AI in Finance, 1–6.
• Understanding the role of intermediaries in online social e-commerce: an exploratory study of Beidian. Z Chen, H Cao, F Xu, M Cheng, T Wang, Y Li. Proceedings of the ACM on Human-Computer Interaction 4(CSCW2), 1–24.
• Uniting the tribes: Using text for marketing insight. J Berger, A Humphreys, S Ludwig, WW Moe, O Netzer, DA Schweidel. Journal of Marketing 84(1), 1–25.
• Visual forecasting of time series with image-to-image regression. N Cohen, S Sood, Z Zeng, T Balch, M Veloso. arXiv:2011.09052.
• When your friends become sellers: An empirical study of social commerce site Beidian. H Cao, Z Chen, F Xu, T Wang, Y Xu, L Zhang, Y Li. Proceedings of the International AAAI Conference on Web and Social Media 14.
• Will This Idea Spread Beyond Academia? Understanding Knowledge Transfer of Scientific Concepts across Text Corpora. H Cao, M Cheng, Z Cen, D McFarland. Proceedings of EMNLP 2020.
• Will you come back/check-in again? Understanding characteristics leading to urban revisitation and re-check-in. Z Chen, H Cao, H Wang, F Xu, V Kostakos, Y Li. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.

2019

• Fund asset inference using machine learning methods: what's in that portfolio? D Byrd, S Bajaj, T Balch. The Journal of Financial Data Science.
• Habit2vec: Trajectory semantic embedding for living pattern recognition in population. H Cao, F Xu, J Sankaranarayanan, Y Li, H Samet. IEEE Transactions on Mobile Computing 19(5), 1096–1108.
• How to evaluate trading strategies: Single agent market replay or multiple agent interactive simulation? T Balch, M Mahfouz, J Lockhart, M Hybinette, D Byrd. arXiv:1906.12010.
• Intra-day equity price prediction using deep learning as a measure of market efficiency. D Byrd, T Balch. arXiv:1908.08168.
• Machine Learning, Geospatial Information, and Social Media Text. R Garg, P Brockett, LL Golden, Y Zhang. Finding New Ways to Engage and Satisfy Global Customers: Proceedings.
• Multiplayer alphazero. N Petosa, T Balch. arXiv:1910.13012.
• On the importance of opponent modeling in auction markets. M Mahfouz, A Filos, C Chtourou, J Lockhart, S Assefa, M Veloso, et al. arXiv:1911.12816.
• Semantics-aware hidden Markov model for human mobility. H Shi, Y Li, H Cao, X Zhou, C Zhang, V Kostakos. IEEE Transactions on Knowledge and Data Engineering.
• Semantics-aware hidden Markov model for human mobility. H Shi, H Cao, X Zhou, Y Li, C Zhang, V Kostakos, F Sun, F Meng. SIAM International Conference on Data Mining 2019, 774–782.
• Smpai: Secure multi-party computation for federated learning. V Mugunthan, A Polychroniadou, D Byrd, T Balch. Proceedings of the NeurIPS 2019 Workshop on Robust AI in Financial Services.
• The effect of visual design in image classification. N Cohen, T Balch, M Veloso. arXiv:1907.09567.
• Towards Explaining Exchange Traded Funds' Impact on Market Volatility Using an Agent-based Model. M Shearer, D Byrd, T Balch. Neural Information Processing Systems, 1–10.
• Understanding metropolitan crowd mobility via mobile cellular accessing data. H Cao, J Sankaranarayanan, J Feng, Y Li, H Samet. ACM Transactions on Spatial Algorithms and Systems 5(2), 1–18.
• User behaviour modeling, recommendations, and purchase prediction during shopping festivals. M Zeng, H Cao, M Chen, Y Li. Electronic Markets 29(2), 263–274.

2018

• Detecting popular temporal modes in population-scale unlabelled trajectory data. F Xu, T Xia, H Cao, Y Li, F Sun, F Meng. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.
• Rapid assessment of customer marketplace in disaster settings through machine learning, geospatial information, and social media text mining: an abstract. R Garg, P Brockett, LL Golden, Y Zhang. Academy of Marketing Science World Marketing Congress, 479–480.
• Rapid Damage Estimation with Iterative Improvements for Relief Resource Planning Post-Disasters. R Garg, Y Zhang, L Golden, P Brockett. Available at SSRN 3254748.
• Revisitation in urban space vs. online: A comparison across POIs, websites, and smartphone apps. H Cao, Z Chen, F Xu, Y Li, V Kostakos. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.
• Uniqueness in the city: Urban morphology and location privacy. H Cao, J Feng, Y Li, V Kostakos. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.
• Use of position tracking to infer social structure in rhesus macaques. B Hrolenok, T Balch, D Byrd, R Roberts, C Kim, J Rehg, S Gilliland, et al. Proceedings of the Fifth International Conference on Animal-Computer Interaction.

2017

• Sampling beats fixed estimate predictors for cloning stochastic behavior in multiagent systems. B Hrolenok, B Boots, T Balch. Proceedings of the AAAI Conference on Artificial Intelligence 31(1).