Centre For Data Science

A Hub for Interdisciplinary Research, Advanced Analytics, and Future Technologies

About Centre for Data Science (CDS)

Centre for Data Science, JISIASR Kolkata, is dedicated to training skilled postgraduate professionals in Data Science to meet the challenges of the technological revolution. Focused on translational research-based education, we prepare students for Industry 4.0 through internships with leading industries and academic institutes across India, alongside industry-oriented projects that enhance domain knowledge and practical skills.

We strive to transform society through innovative education, interdisciplinary research, creativity, and entrepreneurship, fostering a brighter future.

Vision & Mission

Vision

To cultivate analytical minds and intellectual curiosity by delivering education centered on Data Science expertise, problem-solving, communication, and leadership skills.

Mission

We are committed to advancing knowledge by fostering a collaborative environment that encourages the free exchange of ideas, promoting research, creativity, innovation, and entrepreneurship. Our mission is to empower individuals to reach their full potential, address global challenges with a creative and scientific mindset, and uphold the highest ethical standards. The institute champions a culture that respects nature, protects the environment, and welcomes diverse creative minds from across the globe.

Salient Points

Fully-structured, job-oriented courses aligned with industry standards
Collaborations with leading industries and academic institutes globally
Scholarships for bright and meritorious students
Training from eminent professionals in emerging Data Science areas

Course Name: M.Tech in Computer Science and Engineering (Data Science)

Eligibility Criteria

Requirement	Details
Qualification	B.E./B.Tech/M.Sc. in CSE, IT, ECE, Maths, Stats/ equivalent. Final Year eligible
Min. Marks	50% (45% for reserved category)
Entrance	GATE / PGET (WB) / JISIASR Test

Course Name: PhD

Areas of Research

Areas: AI and machine learning / Medical image processing / Business analytics / Cybersecurity / Natural language processing / Blockchain / IoT / Satellite image processing / Cryospheric science

Objective & Content

Students will master Probability and Statistics, Advanced Database Management Systems, Mathematical Modeling for Data Analytics, and Visualization Techniques. They will gain expertise in Machine Learning, Artificial Intelligence, and tools to tackle Big Data challenges, with a focus on Advanced Data Analytics and Data Security. The curriculum includes theory, hands-on implementation, and annual term projects.

Objective & Content

Graduates will be equipped to address industry challenges in sectors like healthcare, transportation, finance, and business. With a strong foundation in Data Science and Machine Learning, they can manage multidisciplinary projects and pursue careers as Data Scientists, Data Analysts, Learning Scientists, Business Analysts, Data Architects, and more.

Research and Development

Requirement	Description
AYURR-AI 360 (Adaptive Yet User-Focused Remedy Recommendation System)	AI-based system for recommending Ayurvedic treatments tailored to individual needs.
Speech-to-Text Summarizer	Tool that transcribes, translates, and summarizes live speech inputs efficiently.
Data Preprocessing Tool	No-code platform for comprehensive data cleaning and preprocessing for ML workflows.

Career Opportunities

Role	Examples
Data & AI Roles	Data Scientist, ML Engineer, AI Developer
Research & Analytics	AI Analyst, R&D Scientist, Data Architect
Business & Tech	BI Expert, Cloud Data Engineer
Advanced Study	Ph.D. in AI, DS, Biomedical Computing
Entrepreneurial	Startup Founder, Tech Consultant

Research Highlights

Using Unsupervised Learning to Detect the Patterns of Symptoms of Common Homoeopathic Remedies

Sponsoring Agency: Central Council for Research in Homoeopathy (CCRH)
Duration: 1 Year

This project applies unsupervised learning techniques, including clustering, NLP, and GAN-based augmentation, to analyze clinical records and literature for identifying symptom patterns. The goal is to enhance the accuracy of homoeopathic remedy selection.

GadgetsGhatao: Developing Neurosignal Biomarkers to Combat Screen Addiction Disorder

Sponsoring Agency: Anusandhan National Research Foundation (ANRF)
Duration: 3 Years

This project focuses on identifying standardized EEG-based biomarkers to detect Screen Addiction Disorder (SAD) in children. Machine learning analysis of brainwave patterns aims to distinguish SAD from related conditions and guide effective interventions.

AI-enabled Deep Neural Predictive Model for Assisted Decision-Making in Homoeopathic Medication

Sponsoring Agency: Central Council for Research in Homoeopathy (CCRH)
Duration: 1 Year

This project develops an AI-driven predictive model integrating NLP and machine learning to analyze clinical data and homeopathic texts for accurate remedy selection. It continuously learns from patient outcomes to enhance dosage optimization and treatment precision.

Intelligent Intrusion Detection Systems

Next-gen security using AI/ML enables smarter, adaptive threat detection with reduced false positives. It protects infrastructure, cloud, and endpoint systems with automated, scalable incident management.

AI-Enabled Access Control Models

AI-driven ABAC dynamically evaluates users and context for secure, seamless access control. It enhances security in healthcare, IoT, and cloud, though privacy and explainability remain challenges.

ML-assisted Skin Disease Detection

Image-based ML models detect skin diseases early, offering fast, low-cost, non-invasive screening. The system leverages computer vision but depends on large datasets and expert validation.

Biomedical Natural Language Processing

BioNLP extracts insights from vast biomedical texts to aid drug discovery and personalized care. AI-powered tools process unstructured clinical data, improving decision-making and healthcare outcomes

End-to-End Framework for Extracting NLACPs

NLACP extraction from text helps contextualize language for smarter, rule-based NLP systems. Techniques like ML and deep learning improve interpretation, despite domain and ambiguity challenges.

ML-approach for Autism Detection in Young Children

ML applied to MEG signals reveals unique brain connectivity features linked to autism in children. Novel spectral and spatial biomarkers offer promise for early ASD diagnosis and intervention.

Corporate Sentiment Analysis

AI analyzes corporate language beyond sentiment to uncover hidden impression management tactics. Context-aware NLP and explainable models ensure trustworthy and nuanced corporate insight.