About Me

Hello! I'm Anjali. Welcome to my corner of the web. I am a PhD student at the Department of Computational and Data Sciences at the Indian Institute of Science (IISc). Having recently submitted my thesis, I am wrapping up my time at the QUEST lab and preparing for the next chapter in my research career. I have always been fascinated by how complex the natural world is. I find immense joy in using algorithms and modeling to decode and understand the underlying patterns and processes that shape it.

Education

PhD in Computational and Data Science | IISc Bangalore | CGPA: 9.2 (2020 – 2025)

M.Tech in Civil Engineering | IISc Bangalore | CGPA: 8.7 (2018 – 2020)

B.Tech in Civil Engineering | Government College of Engineering, Kannur | 79.27% (2013 – 2017)

Research Interests

Multi-Agent Systems

AI for Social Good

Machine Learning and Deep Learning

Game Theory and Reinforcement Learning

Technical Skills

Modeling & Simulation — Agent-Based Modeling, Reinforcement Learning, Game Theory, Ecological Modelling, Population Modelling.

Data Science & Machine Learning — Deep Learning, Species Distribution Modelling, Numerical Optimization.

Geospatial Analysis — Environmental Data Analytics, GIS, Remote Sensing Applications.

Scientific Programming — Proficiency in C, C++, Python, and R; TensorFlow and PyTorch for Deep Learning; NetLogo, mesa, and geo-mesa for Agent-Based Modeling.

Awards and Achievements

Best Young Researcher Award — International Society for Ecological Modelling (2025) [link]

Featured Research — Website and Social Media handles of the Indian Institute of Science (2025) [link]

Best Student Presentation Award — Dynamic Data Driven Application Systems Conference (2024)

Best Student Presentation Award — IEEE India Geoscience and Remote Sensing Symposium (2021)

Best Student Presentation Award — Conference on Non-Destructive Evaluation (2019)

Scientific Officer (Declined) — Nuclear Power Corporation of India (2019)

All India Rank – 435 — Graduate Aptitude Test in Engineering (GATE 2018)

University Level Second Rank Holder — Bachelor of Technology, Kannur University (2017)

School Level First Rank Holder — ISC Higher Secondary Board Examination (2013)

Projects

Spatially Explicit Agent-Based Modeling for Studying Human-Elephant Conflicts (HECs)

Traditional models oversimplify conflict drivers, failing to capture micro-scale behavioral nuances like thermoregulation, crop habituation, and risk-taking that lead to crop-raiding.
Developed a decision-support system integrating GPS telemetry data and environmental drivers to simulate emergent macro-scale movement patterns of Asian elephants (Elephas maximus).
Successfully identified HEC hotspots and demonstrated that water availability and thermal stress significantly dictate seasonal movement and conflict intensity.

Adaptive Guard Policies for Human-Elephant Conflict Mitigation via Green Security Games

Limited patrol resources are often ineffective against intelligent wildlife due to static allocation and partial observability limitations.
Formulated HEC mitigation as Green Security Game and developed the HERDS algorithm, an online learning framework using Follow-the-Perturbed-Leader with Uniform Exploration (FPL-UE).
Validated the algorithm against a calibrated prototype ABM, achieving convergence against multiple adversarial models and developing the first of its kind game-theoretic solution for adaptive wildlife conflict.

Computational Demographic Forecasting for Saltwater Crocodiles using Population Matrix Models and Agent-Based Models

Territorial populations of Crocodylus porosus are highly sensitive to climate-driven sex-ratio shifts, which traditional matrix models fail to capture due to stochasticity.
Engineered a territory-dynamics ABM integrating dominance hierarchies and Temperature-Dependent Sex Determination to simulate climate scenarios through 2100.
Predicted a critical male-biased sex ratio shift and identified nesting site bottlenecks, providing a data-driven roadmap for proactive conservation management.

Machine Learning for Habitat Suitability Analysis

Fragmenting Asian elephant habitats lacks quantitative metrics to correlate historical habitat deterioration with modern migration shifts and movement patterns.
Developed a Random Forest model using satellite-derived metrics (NDVI, LAI, NPP) and topographic data, performing rigorous hyper-parameter tuning and validation.
Quantified the correlation between seasonal habitat reduction and migration patterns, establishing a predictive basis for strategic conservation actions.

Publications

A Dynamic Data Driven Agent Based Model for Characterizing the Space Utilization of Asian Elephants in Response to Water Availability Anjali Purathekandy, Deepak N Subramani.
Dynamic Data Driven Applications Systems — DDDAS (Infosymbiotics for Reliable AI). Lecture Notes in Computer Science, Vol 15514 (2025).

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An Agent-Based Model of Elephant Crop Raid Dynamics in the Periyar-Agasthyamalai Complex, India Anjali Purathekandy, Meera Anna Oommen, Martin Wikelski, Deepak N Subramani.
Ecological Modelling, Volume 496, 110843 (2024).

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Inter and Intra-Annual Spatio-Temporal Variability of Habitat Suitability for Asian Elephants in India: A Random Forest Model-based Analysis Anjali Purathekandy, Deepak N Subramani.
Proceedings of the IEEE International India Geoscience and Remote Sensing Symposium — InGARSS (2021).

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Characteristics of Acoustic Emissions Generated During the Electrochemical Corrosion Process of Steel Reinforcement in Reinforced Concrete Beams R Vidya Sagar, Anjali Purathekandy.
Indian Journal of Engineering and Materials Sciences — IJEMS, Volume 32 (2025).

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Characteristics of Acoustic Emissions Generated During Steel Rebar Corrosion in Reinforced Concrete Anjali Purathekandy, R Vidya Sagar.
Advances in Non-destructive Evaluation. Lecture Notes in Mechanical Engineering. Springer (2021).

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Research Experiences

Dakshin Foundation Oct 2025 - Present | Bangalore, India

Consultant

Dakshin Foundation Oct 2024 - Sep 2025 | Bangalore, India

Research Affiliate

QUEST Lab, Dept. of Computational and Data Sciences, IISc Oct 2020 - Sep 2025 | Bangalore, India

Graduate Research Assistant

Teaching Experiences

DS 225-0: Deep Learning (Jan – Jul 2025)
DS 211: Numerical Optimization (Aug – Dec 2023)
DA 204-O: Data Science in Practice (Aug – Dec 2023)
DA 224-O: Practical Machine Learning (Aug – Dec 2022)
DA 225-O: Deep Learning (Aug – Dec 2022)
DA 202-O: Introduction to Data Science (Aug – Dec 2021)

Other Professional Activities & Engagement

Poster Presentation in International Society for Ecological Modelling Global Conference (2025)
Participant in Winter School on Biodiversity Digital Twins, BioDT School & Hackathon (2025)
Paper Presentation in EECS Research Students Symposium at IISc (2025 & 2022)
Poster Presentation in Indo-German Workshop on Hardware-aware Scientific Computing (2024)