Software

AI Fairness & Bias Mitigation

• Jurity: Fairness and bias mitigation, and recommender system evaluation techniques. LION’23, CIKM’22, ICMLA’21

Personalization & Recommender Systems

• Mab2Rec End-to-end framework for building bandits-based recommenders from raw interaction data to feature generation, model evaluation and deployment. AAAI’24, ODSC’23, Presentation@AAAI’24, Presentation@ATO’21, ATO Blogpost
• MABWiser Parallelizable, contextual multi-armed bandits library with simulation capabilities. Bridge@AAAI’24, TMLR’22, IJAIT’21, ICTAI’19

Natural Language Processing

• Ner4Opt Given an optimization problem in natural language, extract optimization related entities from free-form text. CPAIOR’23, NeurIPS’22
• TextWiser Text featurization NLP library that unifies several text embedding techniques. AAAI’21

Pattern Mining

• Seq2Pat Sequence-to-Pattern generation library to find frequent patterns from large sequence databases. Joint work with CMU. AI Magazine’23, AAAI’22, Bridge@AAAI’23, Frontiers’22, KDF@AAAI’22, CMU Blog Post

Feature Selection

• Selective A white-box feature selection library that supports unsupervised and supervised selection methods for classification and regression tasks. CPAIOR’21, DSO@IJCAI’21

• FSiHD Feature Selection in High-Dimensional Classification. The bronze winner at the Interspeech Speaker Trait Challenge in 2012. Computer Speech & Language’15, Interspeech’12

Combinatorial Optimization

• Pathfinder: CP Decomposition for Capacitated Vehicle Routing with Time-Windows (CVRP-TW) This solver was a finalist of the 2018 AIMMS/MOPTA Modelling Competition Constraint programming based decomposition approach to solve a realistic variant of the vehicle routing problem. AIMMS’18, Brown News

• Hegel: Dialectic Search Solver for Set Cover Problem Dialectic search based local search approach for solving Set Covering Problems. CP’09

Constraint Satisfaction

• 3S: Satisfiability Solver Selector. This solver won 2 gold and 7 medals in total at the International SAT Solver Competition in 2011. CP’11, SAT’11

Algorithm Configuration & Hyperparameter Tuning

• ISAC: Instance-Specific Algorithm Configuration. Algorithm Portfolio based on the Instance-Specific Algorithm Configuration (ISAC) approach. ECAI’10

• GGA: Gender-based Genetic Algorithm for Parameter Tuning. A state-of-the-art parameter tuning and algorithm configuration tool based on genetic algorithms. It is the backbone of many competition-winning constraint solvers and algorithm portfolios. Re-implemented and now maintained by Optano GmbH. CP’09

• DASH: Dynamic Adaptive Search Heuristics & Non-Model Based Search Guidance Set Partitioning Problem (SPP) Benchmark Instance Generator. EJOR’16, AAAI’12

• ASLib: Algorithm Selection Library. This library consists of scenarios and instances for benchmarking from different domains, such as SAT, CSP, and ASP.