Research Experience
Ecological Modelling • Machine Learning • Conservation Biology
Bridging theoretical ecology with practical conservation applications
Research Overview
My research journey spans multiple prestigious institutions, integrating process-based ecological modelling, machine learning algorithms, and biodiversity assessments to better understand freshwater ecosystems, food web dynamics, and species conservation. Each research experience has contributed unique methodological and theoretical perspectives to my comprehensive understanding of ecological systems.
Machine Learning in Ecology
Developing novel unsupervised algorithms like Self-Organizing Maps (SOM) for ecological predictions and community characterization
Ecological Networks & Metawebs
Pioneering research in metaweb construction and ecological interaction predictions using minimal data requirements
Process-Based Modelling
Investigating ecosystem dynamics through mathematical models, focusing on nutrient cycling and species interactions
Conservation Applications
Applying theoretical research to practical conservation challenges, including wildlife management and biodiversity assessments
Postdoctoral Research at IISER Kolkata
Fish Ecology and Behavior Laboratory
Indian Institute of Science Education and Research Kolkata
Duration: January 2024 – June 2024
Position: DST Research Associate-II (CEFIPRA project)
Project title: Using machine learning to understand impacts of water quality and habitat disturbances on fish community structures and patterns in lower eastern Himalayan streams of India and in La Moselle stream in France
Supervisor: Prof. Anuradha Bhat
Research Focus: Machine Learning Applications in Fish Community Analysis
At IISER Kolkata, I applied the unsupervised machine learning algorithm Self-Organising Map (SOM), an artificial neural network-based method, to characterise fish communities into distinct functional groups based on morphometric features and feeding habits.
Key Methodological Contributions:
- Applied SOM algorithms for community characterization based on morphometric features and trophic level
- Integrated feeding habits and functional traits into machine learning frameworks
- Conducted statistical analyses to examine environmental preferences of functional groups
- Developed novel approaches for understanding fish community structures in Himalayan streams
I further applied statistical analyses to examine whether these functional groups exhibited specific environmental preferences, contributing to our understanding of how water quality and habitat disturbances affect fish community structures in lower eastern Himalayan streams.
Postdoctoral Research at Kyung Hee University
Ecology and Ecological Informatics Laboratory
Kyung Hee University, Seoul, South Korea
Duration: October 2022 – December 2023
Funding: National Research Foundation of Korea
Supervisor: Young-Seuk Park
Research Focus: Metawebs and Ecological Interaction Predictions
My research at Kyung Hee University focused on metawebs and ecological interaction predictions, resulting in several groundbreaking contributions to the field of ecological informatics.
🔬 Pioneering Review Publication
Authored a pioneering review article on recent progress in metaweb research, published in Ecological Informatics
🤖 Novel ML Algorithm
Developed a novel unsupervised machine learning approach to predict ecological interactions using minimal data requirements
📊 Database Curation
Curated two comprehensive ecological databases for South Korean ecosystems
🏆 High-Impact Publication
Published methodology in Methods in Ecology and Evolution showing superior performance
Key Research Innovations:
- Minimal Data Requirements: Developed methods relying primarily on interaction matrices
- High Predictive Accuracy: Demonstrated superior performance with minimal noise
- Multiple Validation Techniques: Proposed and applied comprehensive evaluation methods
- Comparative Analysis: Showed superior performance compared to existing methods
Database Contributions:
Functional Groups Database
A comprehensive database on functional groups of benthic macroinvertebrates in South Korean stream ecosystems
Metaweb Database
A metaweb database of South Korean freshwater ecosystems with detailed interaction networks
I also conducted research on characterising functional groups using SOM and predicted the metaweb of South Korea, comparing observed and predicted structures as well as regional variations. These comprehensive studies demonstrate the power of combining machine learning with ecological theory.
Doctoral Research at Visva-Bharati University
Systems Ecology and Ecological Modelling Laboratory
Department of Zoology, Visva-Bharati University
Duration: 2016-2022
Supervisor: Prof. Santanu Ray
Thesis: "Guanotrophication by aquatic avifauna on the dynamics of freshwater ecosystem of Ballavpur, India: a modelling approach"
Research Focus: Waterbird Impact on Freshwater Ecosystem Dynamics
During my PhD, I investigated how waterbirds influence phosphorus cycling in freshwater wetlands through feeding and defecation. While it was known that birds contribute to nutrient enrichment, especially nitrogen and phosphorus, their role in ecosystem dynamics was not well studied.
Research Methodology & Findings:
- Pioneering research: Pioneering research to understand how waterbirds can impact wetland dynamics with the help of Process-based Modelling
- Birds can be a major nutrient contributer: Revealed that birds can be a major nutrient source in these systems
- Temporal Dynamics: Found gradual rather than immediate effects, aligning with previous studies
- Internal Regulation: Discovered that tropical freshwater lake dynamics are primarily regulated by internal nutrient cycling
🔍 Key Scientific Discoveries:
Nutrient Source Identification
Birds serve as major nutrient contributors in oligotrophic wetlands
Temporal Patterns
Nutrient inputs show gradual, long-term effects rather than immediate impacts
System Regulation
Internal cycling dominates over external fluxes in tropical freshwater systems
Collaborative Research During Doctoral Tenure
Alongside my doctoral research, I engaged in several collaborative studies that expanded my expertise in process-based modelling and applied ecology.
🦠 Plant Disease Dynamics
Collaborator: Dr. Fahad Al Basir
Publications: Bulletin of Mathematical Biology, Computational and Applied Mathematics
- Examined effects of time delays on disease spread
- Developed strategies for stage-specific pest control
- Applied mathematical modelling to plant-pathogen interactions
🌊 Benthic-Pelagic Coupling
Collaborator: Dr. Swagata Sinha
Location: Kakinada Bay
- Investigated ecosystem connectivity between benthic and pelagic zones
- Applied systems ecology approaches to marine environments
- Contributed to understanding of coastal ecosystem dynamics
🦐 Biocontrol Applications
Collaborator: Dr. Netri Datta
Focus: Macrobrachium lamarrei as biocontrol agent
- Explored use of prawns against fish louse Argulus
- Applied PBM approaches to biocontrol strategies
- Contributed to sustainable aquaculture practices
Research and Conservation Activities with WINGS
Beyond formal research, I remain actively engaged with the Wildlife Information and Nature Guides Society (WINGS). Driven by personal interest in wildlife conservation, I have developed a comprehensive research program focused on biodiversity assessment and conservation planning.
🐺 Indian Grey Wolf Conservation Projects
WWF-India Conservation Catalyst Grant
Amount: ₹6 Lakh | Role: Principal Investigator
Duration: May 2024 - October 2025
The Habitat Trust Action Grant
Amount: ₹25 Lakh | Role: Co-Principal Investigator
Duration: March 2025 - February 2027
📊 Biodiversity Research & Management
Avian Diversity Publications
Published several research articles on regional avian diversity patterns and conservation status
Wildlife Management Planning
Conducting biodiversity studies and developing wildlife management plans for various corporate organizations
Biodiversity of West Bengal Database
Leading the development of a comprehensive state-level biodiversity database
Research Impact & Future Directions
Future Research Directions
My research continues to evolve at the intersection of machine learning, ecological modelling, and conservation biology. Future work will focus on developing more sophisticated predictive models for ecosystem management, expanding the application of AI in conservation, and bridging the gap between theoretical ecology and practical conservation outcomes.