Prof. Akanksha Rathore

Assistant Professor,
Dept. of Computer Science and Information Systems

Birla Institute of Technology & Science, Pilani
Hyderabad Campus
Jawahar Nagar, Kapra Mandal
Dist.-Medchal-500 078
Telangana, India

Web: https://www.akanksharathore.in/

rathore.akanksha@hyderabad.bits-pilani.ac.in

04066303798

https://www.linkedin.com/in/akanksha-rathore-76a7818b/

Education

2015 – 2021: PhD, Indian Institute of Science, Bangalore.
2008 – 2012: B.Tech. in Information Technology, Dept. Of Computer Engineering, Malaviya National Institute of Technology, Jaipur.

Experience

Apr 2024 – Present: Assistant Professor, Department of CSIS, BITS-Pilani, Hyderabad campus, India.
Oct 2021 – Mar 2024: Postdoctoral Researcher, Max Planck Institute of Animal Behavior, Konstanz, Germany.
2014 – 2015: Project Associate, Nature Conservation Foundation, Mysuru, India.
2012 – 2014: Software Developer, SAP Labs Pvt Ltd, India.
May - July 2013: Intern, Center for Development of Telematics, New Delhi, India.

Data Science & Computational Ecology Research

Welcome to the DSCOvER Lab! I am passionate about exploring the intersection of Data and Computational Sciences with Ecological Research, where my work leverages computational methods and data-driven approaches to enhance our understanding of natural systems. My research investigates how collective animal behavior, ecological data science, and applied artificial intelligence can provide transformative insights into ecosystem dynamics and address critical challenges posed by environmental change.

By integrating expertise in ecology, behavioral science, artificial intelligence, and data analytics, DSCOvER Lab seeks to unravel the complexities of animal movement, social interactions, and ecosystem processes. We apply cutting-edge technologies to bridge computational theory with ecological applications, delivering innovative solutions for biodiversity conservation, climate resilience, and habitat monitoring.

Research Areas:

Collective Intelligence:
- I study how animals coordinate and make decisions in groups, examining patterns like collective movement, escape dynamics, and synchrony in species such as fireflies and birds.
- My research delves into computational and theoretical models that drive swarm intelligence, investigating how animal behavior can inspire solutions to complex environmental and societal challenges.
- I use multi-modal data collection (UAVs, sensors, GPS) and network analysis to uncover the principles behind collective decision-making in natural systems.
Eco-Informatics:
- - I apply AI, machine learning, and data science to study animal populations, habitat quality, and community ecology. My work involves automating wildlife monitoring with advanced tools like drones, remote sensing, and deep learning.
  - I focus on building models that use animal behavior as early warning indicators for environmental stress, such as habitat degradation or the impacts of climate change.

By integrating ecological theory with computational methods, I strive to develop scalable, data-driven solutions for wildlife conservation and ecosystem management.

Through this interdisciplinary approach, my research not only pushes the boundaries of collective behavior and computational ecology but also contributes to real-world applications that address biodiversity and environmental sustainability challenges.

Below are some of the research themes I am currently working on:

Swarm Intelligence in Natural Systems

Key areas: Information transfer, Decision making, Self-organisation, Herding dynamics, Mathematical modelling, Collective motion, Emergent behaviours

Mathematical modelling

Agent-based modelling: Swarm behaviour & Ecological processes

Data Science & Eco-informatics

Key areas: Visual animal tracking, Computer Vision, Deep-learning, Tech deployment for wildlife studies, Drone-based imagery

Deep learning applied to satellite and aerial imagery

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