A comparison of decision alaysis and expert rules for sequential diagnosis. - Jayant Kalagnanam; Max Henrion (UAI, 1988)

Learning to Diagnose by Doing. - Jayant Kalagnanam; Eswaran Subrahmanian (IJCAI, 1989)

The Mathematical Bases for Qualitative Reasoning. - Jayant Kalagnanam; Herbert A. Simon; Yumi Iwasaki (IEEE Expert, 1991)

Directions for Qualitative Reasoning. - Jayant Kalagnanam; Herbert A. Simon (Comput. Intell., 1992)

An application of qualitative analysis of ordinary differential equations to azeotropic batch distillation. - Jayant Kalagnanam; Urmila M. Diwekar (Artif. Intell. Eng., 1993)

An optimization approach to order of magnitude reasoning. - Jayant Kalagnanam; Urmila M. Diwekar (Artif. Intell. Eng. Des. Anal. Manuf., 1994)

The Scope of Dimensional Analysis in Qualitative Reasoning. - Jayant Kalagnanam; Max Henrion; Eswaran Subrahmanian (Comput. Intell., 1994)

Using Neural Networks in Agent Teams to Speed Up Solution Discovery for Hard Multi-Criteria Problems. - Shaun Gittens; Richard Goodwin; Jayant Kalagnanam; Sesh Murthy (AAAI/IAAI, 1999)

Cooperative strategies for solving the bicriteria sparse multiple knapsack problem. - F. Sibel Salman; Jayant Kalagnanam; Sesh Murthy (CEC, 1999)

The Surplus Inventory Matching Problem in the Process Industry. - Jayant R. Kalagnanam; Milind Dawande; Mark Trumbo; Ho Soo Lee (Oper. Res., 2000)

Approximation Algorithms for the Multiple Knapsack Problem with Assignment Restrictions. - Milind Dawande; Jayant Kalagnanam; Pinar Keskinocak; F. Sibel Salman; R. Ravi 001 (J. Comb. Optim., 2000)

Achieving Budget-Balance with Vickrey-Based Payment Schemes in Exchanges. - David C. Parkes; Jayant Kalagnanam; Marta Eso (IJCAI, 2001)

Computational Aspects of Clearing Continuous Call Double Auctions with Assignment Constraints and Indivisible Demand. - Jayant Kalagnanam; Andrew J. Davenport; Ho Soo Lee (Electron. Commer. Res., 2001)

Variable Sized Bin Packing With Color Constraints. - Milind Dawande; Jayant Kalagnanam; Jay Sethuraman (Electron. Notes Discret. Math., 2001)

Winner Determination Algorithms for Electronic Auctions: A Framework Design. - Martin Bichler; Jayant Kalagnanam; Ho Soo Lee; Juhnyoung Lee (EC-Web, 2002)

Cooperative Strategies for Solving the Bicriteria Sparse Multiple Knapsack Problem. - F. Sibel Salman; Jayant Kalagnanam; Sesh Murthy; Andrew J. Davenport (J. Heuristics, 2002)

Applications of flexible pricing in business-to-business electronic commerce. - Martin Bichler; Jayant Kalagnanam; Kaan Katircioglu; Alan J. King; Richard D. Lawrence; Ho Soo Lee; Grace Y. Lin; Yingdong Lu (IBM Syst. J., 2002)

A nonoparametric estimator for setting: reserve prices in procurement auctions. - Martin Bichler; Jayant Kalagnanam (EC, 2003)

Polyhedral sampling for multiattribute preference elicitation. - Soumyadip Ghosh; Jayant Kalagnanam (EC, 2003)

Reliable Execution Planning and Exception Handling for Business Process. - Liangzhao Zeng; Jun-Jang Jeng; Santhosh Kumaran; Jayant Kalagnanam (TES, 2003)

Quality driven web services composition. - Liangzhao Zeng; Boualem Benatallah; Marlon Dumas; Jayant Kalagnanam; Quan Z. Sheng (WWW, 2003)

Special Issue: 2002 Franz Edelman Award for Achievement in Operations Research and the Management Sciences: Combinatorial and Quantity-Discount Procurement Auctions Benefit Mars, Incorporated and Its Suppliers. - Gail Hohner; John Rich; Ed Ng; Grant Reid; Andrew J. Davenport; Jayant R. Kalagnanam; Ho Soo Lee; Chae An (Interfaces, 2003)

A Computational Study of the Kemeny Rule for Preference Aggregation. - Andrew J. Davenport; Jayant Kalagnanam (AAAI, 2004)

A system for automated mapping of bill-of-materials part numbers. - Jayant Kalagnanam; Moninder Singh; Sudhir Verma; Michael Patek; Yuk Wah Wong (KDD, 2004)

The Slab-Design Problem in the Steel Industry. - Milind Dawande; Jayant Kalagnanam; Ho Soo Lee; Chandra Reddy; Stuart Siegel; Mark Trumbo (Interfaces, 2004)

QoS-Aware Middleware for Web Services Composition. - Liangzhao Zeng; Boualem Benatallah; Anne H. H. Ngu; Marlon Dumas; Jayant Kalagnanam; Henry Chang (IEEE Trans. Software Eng., 2004)

Automated cleansing for spend analytics. - Moninder Singh; Jayant Kalagnanam; Sudhir Verma; Amit J. Shah; Swaroop K. Chalasani (CIKM, 2005)

Configurable offers and winner determination in multi-attribute auctions. - Martin Bichler; Jayant Kalagnanam (Eur. J. Oper. Res., 2005)

Bid Evaluation in Procurement Auctions with Piecewise Linear Supply Curves. - Marta Eso; Soumyadip Ghosh; Jayant Kalagnanam; Laszlo Ladányi (J. Heuristics, 2005)

Models for Iterative Multiattribute Procurement Auctions. - David C. Parkes; Jayant Kalagnanam (Manag. Sci., 2005)

Data Quality Management using Business Process Modeling. - Sugato Bagchi; Xue Bai; Jayant Kalagnanam (IEEE SCC, 2006)

Improved Bounds for Computing Kemeny Rankings. - Vincent Conitzer; Andrew J. Davenport; Jayant Kalagnanam (AAAI, 2006)

Software frameworks for advanced procurement auction markets. - Martin Bichler; Jayant Kalagnanam (Commun. ACM, 2006)

A Column-Generation Approach to the Multiple Knapsack Problem with Color Constraints. - John J. H. Forrest; Jayant Kalagnanam; Laszlo Ladányi (INFORMS J. Comput., 2006)

A non-parametric estimator for setting reservation prices in procurement auctions. - Martin Bichler; Jayant Kalagnanam (Inf. Technol. Manag., 2006)

An Application of Constraint Programming to Generating Detailed Operations Schedules for Steel Manufacturing. - Andrew J. Davenport; Jayant Kalagnanam; Chandra Reddy; Stuart Siegel; John Hou (CP, 2007)

Production design for plate products in the steel industry. - Sanjeeb Dash; Jayant Kalagnanam; Chandra Reddy; Sang Hwa Song (IBM J. Res. Dev., 2007)

Learning dynamic temporal graphs for oil-production equipment monitoring system. - Yan Liu 002; Jayant R. Kalagnanam; Oivind Johnsen (KDD, 2009)

Foundations for Smarter Cities. - Colin Harrison; B. Eckman; R. Hamilton; Perry Hartswick; Jayant Kalagnanam; Jurij R. Paraszczak; P. Williams (IBM J. Res. Dev., 2010)

Phase identification in smart grids. - Vijay Arya; Deva P. Seetharam; Shivkumar Kalyanaraman; Kejitan Dontas; Christopher J. Pavlovski; Steve Hoy; Jayant R. Kalagnanam (SmartGridComm, 2011)

Modeling and simulation of building energy performance for portfolios of public buildings. - Young M. Lee; Fei Liu; Lianjun An; Huijing Jiang; Chandra Reddy; Raya Horesh; Paul Nevill; Estepan Meliksetian; Pawan Chowdhary; Nat Mills; Young Tae Chae; Jane L. Snowdon; et al. (WSC, 2011)

Analytics-driven asset management. - Arun Hampapur; H. Cao; Andrew J. Davenport; W. S. Dong; Don Fenhagen; Rogério Schmidt Feris; Germán S. Goldszmidt; Z. B. Jiang; Jayant Kalagnanam; Tarun Kumar; H. Li; Xuan Liu; et al. (IBM J. Res. Dev., 2011)

Distributed methods for solving the security-constrained optimal power flow problem. - Dzung T. Phan; Jayant Kalagnanam (ISGT, 2012)

Managing Data Quality Risk in Accounting Information Systems. - Xue Bai; Manuel A. Nunez; Jayant Kalagnanam (Inf. Syst. Res., 2012)

A Comparison of Decision Analysis and Expert Rules for Sequential Diagnosis - Jayant Kalagnanam; Max Henrion (CoRR, 2013)

FoodSIS: a text mining system to improve the state of food safety in singapore. - Kiran Kate; Sneha Chaudhari; Andy Prapanca; Jayant Kalagnanam (KDD, 2014)

Monitoring Food Safety Violation Reports from Internet Forums. - Kiran Kate; Sumit Negi; Jayant Kalagnanam (MIE, 2014)

InfoSuggest: A System for Automated Information Gathering: With a Real-World Case Study. - Kiran Kate; Andy Prapanca; Jayant Kalagnanam (SRII Global Conference, 2014)

Sparse Gaussian Markov Random Field Mixtures for Anomaly Detection. - Tsuyoshi Idé; Ankush Khandelwal; Jayant Kalagnanam (ICDM, 2016)

Change Detection Using Directional Statistics. - Tsuyoshi Idé; Dzung T. Phan; Jayant Kalagnanam (IJCAI, 2016)

Optimal Generalized Decision Trees via Integer Programming. - Matt Menickelly; Oktay Günlük; Jayant Kalagnanam; Katya Scheinberg (CoRR, 2016)

Multi-task Multi-modal Models for Collective Anomaly Detection. - Tsuyoshi Idé; Dzung T. Phan; Jayant Kalagnanam (ICDM, 2017)

A Novel l0-Constrained Gaussian Graphical Model for Anomaly Localization. - Dzung T. Phan; Tsuyoshi Idé; Jayant Kalagnanam; Matt Menickelly; Katya Scheinberg (ICDM Workshops, 2017)

ChieF: A Change Pattern based Interpretable Failure Analyzer. - Dhaval Patel 002; Lam M. Nguyen; Akshay Rangamani; Shrey Shrivastava; Jayant Kalagnanam (IEEE BigData, 2018)

Development of a spectral source inverse model by using generalized polynomial chaos. - Kyongmin Yeo; Youngdeok Hwang; Xiao Liu 044; Jayant Kalagnanam (CoRR, 2018)

When Does Stochastic Gradient Algorithm Work Well? - Lam M. Nguyen; Nam H. Nguyen; Dzung T. Phan; Jayant R. Kalagnanam; Katya Scheinberg (CoRR, 2018)

DQA: Scalable, Automated and Interactive Data Quality Advisor. - Shrey Shrivastava; Dhaval Patel 002; Anuradha Bhamidipaty; Wesley M. Gifford; Stuart A. Siegel; Venkata Sitaramagiridharganesh Ganapavarapu; Jayant R. Kalagnanam (IEEE BigData, 2019)

Providing Cooperative Data Analytics for Real Applications Using Machine Learning. - Arun Iyengar; Jayant Kalagnanam; Dhaval Patel 002; Chandra Reddy; Shrey Shrivastava (ICDCS, 2019)

A Prediction-Optimization Framework for Site-Wide Process Optimization. - Dharmashankar Subramanian; Pavankumar Murali; Nianjun Zhou; Xiang Ma; Giovane Cesar Da Silva; Raju Pavuluri; Jayant Kalagnanam (ICIOT, 2019)

ThunderML: A Toolkit for Enabling AI/ML Models on Cloud for Industry 4.0. - Shrey Shrivastava; Dhaval Patel 002; Wesley M. Gifford; Stuart Siegel; Jayant Kalagnanam (ICWS, 2019)

Optimal Finite-Sum Smooth Non-Convex Optimization with SARAH. - Lam M. Nguyen; Marten van Dijk; Dzung T. Phan; Phuong Ha Nguyen; Tsui-Wei Weng; Jayant R. Kalagnanam (CoRR, 2019)

Delay-Adaptive Distributed Stochastic Optimization. - Zhaolin Ren; Zhengyuan Zhou; Linhai Qiu; Ajay Deshpande; Jayant Kalagnanam (AAAI, 2020)

Smart-ML: A System for Machine Learning Model Exploration using Pipeline Graph. - Dhaval Patel 002; Shrey Shrivastava; Wesley M. Gifford; Stuart Siegel; Jayant Kalagnanam; Chandra Reddy (IEEE BigData, 2020)

FLOps: On Learning Important Time Series Features for Real-Valued Prediction. - Dhaval Patel 002; Syed Yousaf Shah; Nianjun Zhou; Shrey Shrivastava; Arun Iyengar; Anuradha Bhamidipaty; Jayant Kalagnanam (IEEE BigData, 2020)

Doctor for Machines: A Failure Pattern Analysis Solution for Industry 4.0. - Dhaval Patel 002; Nianjun Zhou; Shrey Shrivastava; Jayant Kalagnanam (IEEE BigData, 2020)

Pruning Deep Neural Networks with $ ell_{0}$-constrained Optimization. - Dzung T. Phan; Lam M. Nguyen; Nam H. Nguyen; Jayant R. Kalagnanam (ICDM, 2020)

A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees. - Haoran Zhu; Pavankumar Murali; Dzung T. Phan; Lam M. Nguyen; Jayant Kalagnanam (NeurIPS, 2020)

Federated Learning's Blessing: FedAvg has Linear Speedup. - Zhaonan Qu; Kaixiang Lin; Jayant Kalagnanam; Zhaojian Li; Jiayu Zhou; Zhengyuan Zhou (CoRR, 2020)

Regression Optimization for System-level Production Control. - Dzung T. Phan; Lam M. Nguyen; Pavankumar Murali; Nhan H. Pham; Hongsheng Liu; Jayant R. Kalagnanam (ACC, 2021)

Scaling Anomaly Detection Service Using Serverless Technology. - Dhaval Patel 002; Shuxin Lin; Srideepika Jayaraman; Giridhar Ganapavarapu; Anuradha Bhamidipaty; Jayant Kalagnanam (IEEE BigData, 2021)

Asset Modeling using Serverless Computing. - Srideepika Jayaraman; Chandra Reddy; Elham Khabiri; Dhaval Patel 002; Anuradha Bhamidipaty; Jayant Kalagnanam (IEEE BigData, 2021)

Math Programming based Reinforcement Learning for Multi-Echelon Inventory Management. - Pavithra Harsha; Ashish Jagmohan; Jayant R. Kalagnanam; Brian Quanz; Divya Singhvi (CoRR, 2021)

Optimal decision trees for categorical data via integer programming. - Oktay Günlük; Jayant Kalagnanam; Minhan Li; Matt Menickelly; Katya Scheinberg (J. Glob. Optim., 2021)

Variational Inference Formulation for a Model-Free Simulation of a Dynamical System with Unknown Parameters by a Recurrent Neural Network. - Kyongmin Yeo; Dylan E. C. Grullon; Fan-Keng Sun; Duane S. Boning; Jayant R. Kalagnanam (SIAM J. Sci. Comput., 2021)

AnomalyKiTS: Anomaly Detection Toolkit for Time Series. - Dhaval Patel 002; Giridhar Ganapavarapu; Srideepika Jayaraman; Shuxin Lin; Anuradha Bhamidipaty; Jayant Kalagnanam (AAAI, 2022)

Interpretable Clustering via Multi-Polytope Machines. - Connor Lawless; Jayant Kalagnanam; Lam M. Nguyen; Dzung T. Phan; Chandra Reddy (AAAI, 2022)

DSServe - Data Science using Serverless. - Dhaval Patel 002; Shuxin Lin; Jayant Kalagnanam (IEEE Big Data, 2022)

Finite-sum smooth optimization with SARAH. - Lam M. Nguyen; Marten van Dijk; Dzung T. Phan; Phuong Ha Nguyen; Tsui-Wei Weng; Jayant R. Kalagnanam (Comput. Optim. Appl., 2022)

Batched Learning in Generalized Linear Contextual Bandits With General Decision Sets. - Zhimei Ren; Zhengyuan Zhou; Jayant R. Kalagnanam (IEEE Control. Syst. Lett., 2022)

AI-Based Real-Time Site-Wide Optimization for Process Manufacturing. - Jayant Kalagnanam; Dzung T. Phan; Pavankumar Murali; Lam M. Nguyen; Nianjun Zhou; Dharmashankar Subramanian; Raju Pavuluri; Xiang Ma; Crystal Lui; Giovane Cesar Da Silva (INFORMS J. Appl. Anal., 2022)

AI Model Factory: Scaling AI for Industry 4.0 Applications. - Dhaval Patel 002; Shuxin Lin; Dhruv Shah; Srideepika Jayaraman; Joern Ploennigs; Anuradha Bhamidipati; Jayant Kalagnanam (AAAI, 2023)

Optimal Control via Linearizable Deep Learning. - Vinícius Lima 002; Dzung T. Phan; Lam M. Nguyen; Jayant Kalagnanam (ACC, 2023)

A Time Series is Worth 64 Words: Long-term Forecasting with Transformers. - Yuqi Nie; Nam H. Nguyen; Phanwadee Sinthong; Jayant Kalagnanam (ICLR, 2023)

TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting. - Vijay Ekambaram; Arindam Jati; Nam Nguyen; Phanwadee Sinthong; Jayant Kalagnanam (KDD, 2023)

An End-to-End Time Series Model for Simultaneous Imputation and Forecast. - Trang H. Tran; Lam M. Nguyen; Kyongmin Yeo; Nam Nguyen; Dzung T. Phan; Roman Vaculín; Jayant Kalagnanam (CoRR, 2023)

AutoMixer for Improved Multivariate Time-Series Forecasting on BizITOps Data. - Santosh Palaskar; Vijay Ekambaram; Arindam Jati; Neelamadhav Gantayat; Avirup Saha; Seema Nagar; Nam H. Nguyen; Pankaj Dayama 001; Renuka Sindhgatta; Prateeti Mohapatra; Harshit Kumar; Jayant Kalagnanam; et al. (CoRR, 2023)

AutoMixer for Improved Multivariate Time-Series Forecasting on Business and IT Observability Data. - Santosh Palaskar; Vijay Ekambaram; Arindam Jati; Neelamadhav Gantayat; Avirup Saha; Seema Nagar; Nam H. Nguyen; Pankaj Dayama 001; Renuka Sindhgatta; Prateeti Mohapatra; Harshit Kumar; Jayant Kalagnanam; et al. (AAAI, 2024)

Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series. - Vijay Ekambaram; Arindam Jati; Pankaj Dayama 001; Sumanta Mukherjee; Nam Nguyen; Wesley M. Gifford; Chandra Reddy; Jayant Kalagnanam (NeurIPS, 2024)

Multi-polytope Machine for Classification. - Dzung T. Phan; Lam M. Nguyen; Jayant Kalagnanam; Chandra Reddy (SDM, 2024)

Identifying Homogeneous and Interpretable Groups for Conformal Prediction. - Natalia Martinez Gil; Dhaval Patel 002; Chandra Reddy; Giridhar Ganapavarapu; Roman Vaculín; Jayant Kalagnanam (UAI, 2024)

Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series. - Vijay Ekambaram; Arindam Jati; Nam H. Nguyen; Pankaj Dayama 001; Chandra Reddy; Wesley M. Gifford; Jayant Kalagnanam (CoRR, 2024)

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation. - Claudius Krause; Michele Faucci Giannelli; Gregor Kasieczka; Benjamin Nachman; Dalila Salamani; David Shih; Anna Zaborowska; Oz Amram; Kerstin Borras; Matthew R. Buckley; Erik Buhmann; Thorsten Buss; et al. (CoRR, 2024)

Convergence-Guaranteed Elastic Net Graphical Model Estimation with Applications to Anomaly Localization. - Dzung T. Phan; Matt Menickelly; Tsuyoshi Idé; Jayant Kalagnanam (SDM, 2025)

Deep Policy Iteration with Integer Programming for Inventory Management. - Pavithra Harsha; Ashish Jagmohan; Jayant Kalagnanam; Brian Quanz; Divya Singhvi (Manuf. Serv. Oper. Manag., 2025)

TSPulse: Dual Space Tiny Pre-Trained Models for Rapid Time-Series Analysis. - Vijay Ekambaram; Subodh Kumar; Arindam Jati; Sumanta Mukherjee; Tomoya Sakai; Pankaj Dayama 001; Wesley M. Gifford; Jayant Kalagnanam (CoRR, 2025)

FailureSensorIQ: A Multi-Choice QA Dataset for Understanding Sensor Relationships and Failure Modes. - Christodoulos Constantinides; Dhaval Patel 002; Shuxin Lin; Claudio Guerrero; Sunil Dagajirao Patil; Jayant Kalagnanam (CoRR, 2025)

AssetOpsBench: Benchmarking AI Agents for Task Automation in Industrial Asset Operations and Maintenance. - Dhaval Patel 002; Shuxin Lin; James T. Rayfield; Nianjun Zhou; Roman Vaculín; Natalia Martinez Gil; Fearghal O'Donncha; Jayant Kalagnanam (CoRR, 2025)

Toward a Trustworthy Optimization Modeling Agent via Verifiable Synthetic Data Generation. - Vinícius Lima 002; Dzung T. Phan; Jayant Kalagnanam; Dhaval Patel 002; Nianjun Zhou (CoRR, 2025)