About IDeAL
The Interdisciplinary Decision Sciences & Analytics Lab (IDeAL) is a Centre of Excellence at the Indian Institute of Management Visakhapatnam. This Lab is dedicated to academic research, industrial/Govt. consultancy, product development and training to support inter-disciplinary research using the innovations of artificial intelligence, machine learning, deep learning, cloud computing, graph analytics, game theory, cyber-physical systems, pervasive computing etc. while keeping Mathematical Optimization and Data Science as the core in the approach of solving the inter-disciplinary problems faced by India and other emerging economies. We invite researchers and scholars to submit their original research work to IDeAL working paper series. The papers can fall under intersection of any field of data science with areas like Health Care, Smart Cities Development, Sustainable Supply Chain Management, Behavioral Finance, Environmental Risk Assessment, Human-Computer Interaction in Decision Support Systems, Biotechnology Policy and Management, Cognitive Neuroscience in Business Strategy, Energy-Economics, Global Public Health Decision Making, Educational Data Mining and Analytics, Resource Management, etc. Researchers can visit IDeAL Working Paper Series page to submit their papers.
Thrust Areas
Health Care
With data science and optimization models, the public-health system could be transformed into a high-quality, quick-response service-delivery system. Data analytics, AI, and optimization-based solutions have great potential in bringing efficiency and effectiveness to service delivery. This approach could include analyzing past information at the primary health center (PHC) level. Machine learning models could help develop a predictive health-care system. Further, simulation and optimization models would aid in the planning and operations management of primary health-care supply chains. For example, a web-based TB registration scheme could generate massive data by enhancing outreach. Telemedicine services and mother-and-child tracking systems of voice messages to pregnant women and neo-natal mothers could be facilitated.
Natural Resource Management
IDeAL will enable researchers to apply decision science and data models against real-world challenges such as water storage, biodiversity loss, and mineral resource extraction. Managing natural resources faces the central problem of how data is exploited to build predictive and integrated models for sustainable decisions amid uncertainty. Advanced statistics and coding can reveal complex relationships between water-resource features, poverty, and energy consumption rates. Rainfall variability and droughts relate to a lack of sustainable water resources for agriculture, increased runoff and erosion, and decreases in GDP. Using natural resource data science can reveal correlations between rainfall trends and poverty rates.
Computational Public Policy
Alice Rivlin mentioned this aspect in 1970 when she published “Systemic Thinking for Social Action.” She argued for more rigor and scientific processes in government decision-making, writing: “To do better, we must have a way of distinguishing better from worse.” The data science approach is valuable for public servants and policy, pushing people to defy conjecture, consider counterfactuals, reason about complex patterns, and question missing information. It makes people skeptical of narratives that, while emotionally powerful, are not good sources for comprehensive policies. Computational public policy applies computer science and mathematics to solve public policy problems.
Cyber-Physical Systems
As computing and communication devices become smaller and cheaper, they can be embedded in objects to interact directly with the environment. Cyber-Physical Systems (CPS) are a compilation of computing and communication units connecting the cyberworld with the environment. CPS spans applications with enormous societal impact and economic benefit. They are characterized by tightly integrated components in a network that dynamically expands and contracts. CPS is already used in medical devices (pacemakers, insulin pumps), infrastructure (surveillance and control), manufacturing, and transportation (airplanes, air traffic control, rail). Advances in CPS will lead to systems that significantly surpass the capabilities of today’s simple embedded systems.
Tools We Work With
Machine Learning and Data Analytics
Most of the data oriented research is carried out with help of open-source tools which include python programming language. Researchers at IDeAL use various libraries to extract new patterns and insights from data. NumPy and Pandas libraries are used to perform data processing, data cleaning, and data reshaping. Scikit-learn library which consists of various machine learning techniques predefined is used to build a machine learning model on the data. SHAP library is used to perform explainable machine learning which is a popular technique used to explain black box machine learning models.
Mathematical Programming and Optimization
While predictive modelling and machine learning models help in understanding and exploring information required to solve a problem, the actual data problem needs to be solved using optimization techniques using integer, linear and non-linear programming techniques. R software consists of a wide range of data and statistical libraries which are useful in performing experimental analysis like data envelopment analysis, structural equation modelling, etc. A Mathematical Programming Language (AMPL) is used to perform optimization using customized mathematical programs using solvers. MATLAB is also used to perform optimization and generate visualizations on the results.
Data Visualizations and Decision Support Systems
The solutions developed at IDeAL needs to reach users and require utilization of proper visualization techniques and platform to host the applications. Matplotlib, seaborn, and plotly are three popular plotting libraries that are used in visualizing the results of data analysis. Flask is a framework in python that is used to create and deploy web applications. Researchers at IDeAL use combination of Flask framework with one of the relevant plotting libraries to build scalable decision support systems which aid decision makers with accurate findings.
Collaborate With Us
Corporations & Government Organizations
Collaborate with us on short term and long term joint research projects.
Researchers
Submit your research processes to IDeAL Working Paper Series and collaborate towards inter-disciplinary research.
Students
Explore various internship opportunities in Inter-disciplinary research areas to use your existing skills on entirely new areas.