# Past EconCS Seminars Sort & Filters close ## Filters taxonomy\_calendar\_seminar expand\_more - EconCS Seminars (42) - Fall 2025 EconCS Seminars (14) - Spring EconCS 2025 Seminars (11) - Fall 2024 EconCS Seminars (13) - Spring 2024 EconCS Seminars (15) - Fall 2023 EconCS Seminars (11) - Spring 2023 EconCS Seminars (12) - Fall 2022 Econ CS Seminars (10) - Spring 2022 EconCS Seminars (10) - Fall 2021 EconCS Seminars (10) - Spring 2021 EconCS Seminars (7) - Seminar history (87) Search Within Results Search Within Results search ## 134 results Show filters filter\_alt Sort by Alphabetical A-ZChronological sort list grid\_view ## 134 results [### 1. A Simple, Statistically Robust Test of Discrimination & 2. Distortion of AI alignment: Does preference optimization optimize for preferences? ](/event/1-simple-statistically-robust-test-discrimination-2-distortion-ai-alignment-does-preference)December 12, 2025 | 1:30PM - 3:00PM EST | SEC LL2.221 In Person Speaker 1: Johann Gaebler (Harvard University) Title 1: A Simple, Statistically Robust Test of Discrimination Abstract 1: In observational studies of discrimination, the most common statistical approaches consider either the rate at which decisions are... [### Natural Centralization in Decentralized Finance (joint with Adrian Casillas and Maryam Farboodi) ](/event/natural-centralization-decentralized-finance-joint-adrian-casillas-and-maryam-farboodi)December 5, 2025 | 1:30PM - 2:30PM EST | SEC LL2.221 In Person Time & Location: Friday, December 5, 1:30pm - 2:30pm at SEC LL 2.221 Title: Natural Centralization in Decentralized Finance (joint with Adrian Casillas and Maryam Farboodi) Abstract: Can centralization arise absent barriers to entry? We confront this... [### (1) Distribution over rewards for pluralistic AI alignment & (2) Data Reliability Scoring ](/event/1-distribution-over-rewards-pluralistic-ai-alignment-2-data-reliability-scoring)November 21, 2025 | 1:30PM - 2:30PM EST | SEC LL2.221 In Person Time & Location: Friday, November 21, 1:30pm - 2:30pm at SEC LL 2.221 Speaker 1: Itai Shapira (Harvard University) Title 1: Dis tribution over rewards for pluralistic AI alignment Abstract 1: Current alignment pipelines based on human feedback, typically... [### Recommendations in high-stakes settings ](/event/recommendations-high-stakes-settings)November 14, 2025 | 1:30PM - 2:30PM EST | SEC LL2.221 In Person Nikhil Garg (Cornell Tech) Recommendations in high-stakes settings Recommendation and search systems are now used in high-stakes settings, including to help find jobs, schools, and partners. Building public interest recommender systems in such settings... [### The Trilemma of Truth in Large Language Models ](/event/trilemma-truth-large-language-models)November 7, 2025 | 1:30PM - 2:30PM EST | SEC LL2.221 In Person Tina Eliassi-Rad (Northeastern) The Trilemma of Truth in Large Language Models In our human-AI society, we often attribute human characteristics to large language models (LLMs) and claim that they "know" things. LLMs have an internal probabilistic... [### Kehang Zhu (Harvard): TBA ](/event/kehang-zhu-harvard-tba)October 31, 2025 | 1:30PM - 2:30PM EDT | SEC LL2.221 In Person Kehang Zhu (Harvard): TBA [### Cardinal-Utility Matching Markets: Pricing is Intractability, but Nash Bargaining Works! ](/event/cardinal-utility-matching-markets-pricing-intractability-nash-bargaining-works)October 24, 2025 | 1:30PM - 2:30PM EDT | SEC LL2.221 In Person Vijay Vazirani (UC Irvine) Cardinal-Utility Matching Markets: Pricing is Intractability, but Nash Bargaining Works! For a mechanism to be truly impactful, it must combine strong game-theoretic properties with computational efficiency -- a classic example... [### When Experimental Economics Meets Large Language Models: Evidence-based Tactics ](/event/when-experimental-economics-meets-large-language-models-evidence-based-tactics)October 17, 2025 | 1:30PM - 2:30PM EDT | SEC LL2.221 In Person Tracy Liu (Tsinghua University) When Experimental Economics Meets Large Language Models: Evidence-based Tactics Advancements in large language models (LLMs) have sparked a growing interest in measuring and understanding their behavior through experimental... [### The Impossibility of Transparent and Decentralized DeFi Trading & Assortment Optimization for Patient-Provider Matching ](/event/impossibility-transparent-and-decentralized-defi-trading-assortment-optimization-patient)October 10, 2025 | 1:30PM - 3:00PM EDT | SEC LL2.221 In Person Hanna Halaburda (NYU) - 60 min The Impossibility of Transparent and Decentralized DeFi Trading Decentralized finance (DeFi) aspires to replace traditional intermediaries with transparent, decentralized markets. Yet we show that transparency itself creates... [### Calibrated Coarsening: Designing Information for AI-Assisted Decisions ](/event/calibrated-coarsening-designing-information-ai-assisted-decisions)October 3, 2025 | 1:30PM - 2:30PM EDT | SEC LL2.221 In Person Ruru Hoong (Harvard) Artificial intelligence (AI) signals are increasingly deployed as human decision-making aids across many critical applications, but human cognitive biases can prevent them from improving outcomes. We propose calibrated coarsening... [### Metritocracy: Representative Metrics for Lite Benchmarks & Learning to Coordinate Bidders in Non-Truthful Auctions ](/event/metritocracy-representative-metrics-lite-benchmarks-learning-coordinate-bidders-non-truthful)September 26, 2025 | 1:30PM - 2:30PM EDT | SEC LL2.221 In Person Speaker 1: Shirley Zhang (Harvard University) Title: Metritocracy: Representative Metrics for Lite Benchmarks Abstract: A common problem in LLM evaluation is how to choose a subset of metrics from a full suite of possible metrics. Subset selection is... [### Gerdus Benade (BU, Harvard): Towards Rawlsian Justice in Food Rescue ](/event/gerdus-benade-bu-harvard-towards-rawlsian-justice-food-rescue)September 19, 2025 | 1:30PM - 2:30PM EDT | SEC LL2.221 In Person Towards Rawlsian Justice in Food Rescue We study a problem faced by a national food rescue platform that matches each donation to the first recipient who claims it. Recipients have very different response rates, leading to a few highly responsive... - Previous page chevron\_left - [1](?page=0 "Current page") - [2](?page=1 "Go to page 2") - [3](?page=2 "Go to page 3") - [ Last page 12 ](?page=11 "Go to last page") - [ Next page chevron\_right ](?page=1 "Go to next page")