Faculty & Research

Production and Quantitative Methods

About Production & Quantitative Methods (P&QM) Area

The Production & Quantitative Methods (P&QM) area engages in interdisciplinary research, teaching and consulting relating to scientific methodologies in Operations Management, Operations Research and Statistics. The goal is to design, influence and enable good management practices and strengthen policies by providing the necessary strategic thinking, tools and techniques for evidence-based decision-making towards improving organizational performance in an increasingly data intensive world.

Research

Faculty research interests in operations management are on strategic or operational issues related to manufacturing and service planning, supply chain coordination, shop floor scheduling and improving productivity of plant operations, design of operations, technological change and innovation, R&D capabilities, economics of flexible operations and process planning and in the area of Public sector and socially responsible operations.

In operations research, faculty members have expertise in linear and integer programming, large scale optimization, combinatorial optimization, revenue management and network optimization. Interest in this area is both in modeling as well as in development of algorithms and heuristics for such problems. Typical application areas for research include finance, logistics, and the process industry.

Faculty research interests in statistics include modeling discrete and financial data, survey sampling, finite population inference, biostatistics, longitudinal and survival analysis, Bayesian inference, reliability analysis, time series analysis, statistical genetics, directional statistics, functional data analysis and stochastic processes.

Teaching

The area offers several courses in Operations management, Operations research, and Statistics across all the programmes of the institute. In addition, faculty members offer a wide array of Executive Education Programmes, both on-campus and online, that cater to a large number of working professionals from diverse backgrounds. The complete list of courses on offer with a brief summary of each is provided here

Recruitment

The area welcomes applications from candidates who have demonstrated strong research capabilities in carrying out interdisciplinary work, especially those that can influence management, theory, practice and policy, as well as methodological developments in any of the core fields, namely operations management, operations research or statistics. The following areas will be of special interest: Machine learning and Artificial Intelligence, Causal Inference, logistics and transportation, sustainable operations, empirical operations management, big data analytics, high dimensional data analysis, managing platforms and sharing economy, Industry 4.0, smart mobility.

Message from the Area Chairperson

The Production & Quantitative Methods (P&QM) area engages in interdisciplinary research, teaching, and consulting relating to scientific methodologies in Operations Management, Operations Research, and Statistics. The goal is to design, influence, and enable good management practices and strengthen policies by providing the necessary strategic thinking, tools, and techniques for evidence-based decision-making toward improving organizational performance in an increasingly data-intensive world.

Karthik Sriram
Associate Professor

Doctoral Students

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Ph.D. at IIMA

The Ph.D. Programme in Management seeks candidates with outstanding academic credentials, intellectual curiosity and discipline needed to make scholarly contribution to society. It provides a diverse set of opportunities for interdisciplinary learning and research The student becomes part of one of the eleven functional/sectoral areas and acquires the super specialized theoretical knowledge and practical aspects of the area.

List of Courses

  • Working with Networks
  • Why Projects Fail? Uncertainty, Complexity and Risk in Projects
  • The Art and Craft of Decision Making
  • Supply Chain Thinking
  • Supply Chain Management
  • Statistical Methods in Data Analysis
  • Revenue Management and Dynamic Pricing
  • Operations Strategy
  • Managerial Applications of OR
  • Forecasting Techniques for a Practitioner
  • Elephants and Cheetahs: Systems, Strategy and Bottlenecks
  • Coordinating the Crowd
  • Business Analytics
  • Bayesian Method of Data Analysis
  • Advanced Methods of Data Analysis
  • Advanced Mathematical Modeling for Managerial Decisions
  • Flexicore – Service Operations Management
  • Flexicore – Manufacturing Operations Management
  • Quantitative Methods 2
  • Operations Management II
  • Operations Management I
  • Quantitative Methods -1b
  • Quantitative Methods -1a
  • Project Management
  • Operations Management
  • Logistics & Supply Chain Management
  • Decision Modelling
  • Business Statistics and Research Methods
  • Special topics introducing contemporary practices or research areas in operations
  • Statistical Data Analysis
  • Operations Management
  • Food Supply Chain Management
  • Understanding and Assessing Risk
  • Supply Chain Management
  • Quality Management
  • Perspectives on Operations Management
  • Logistics Management
  • Elephants and Cheetahs: Systems, Strategy and Bottlenecks
  • Data Science for Business
  • Business Analytics
  • Setting and Delivering Service Levels
  • Modeling for Decisions
  • Designing Operations to Meet Demand
  • Analysis of Data
  • Business Analytics
  • Quantitative Techniques – (Decision Making)
  • Probability Statistics II
  • Probability Statistics I
  • Operations Management II
  • Operations Management I

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