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The AI@Ashoka initiative represents a significant step in Ashoka University’s commitment to cutting-edge research and interdisciplinary innovation. Led by Prof. Partha P. Chakrabarti (Advisor to Computer Science, Ashoka University, and Professor of Computer Science and Engineering at IIT Kharagpur), this initiative is driving advancements in Artificial Intelligence (AI) and Machine Learning (ML) across diverse fields, from environmental studies and psychology to biology, chemistry, and computer science.
The eleven ongoing projects demonstrate AI’s transformative potential—enhancing fire detection accuracy, biodiversity monitoring, and cognitive assessments in infants, while also advancing cancer research, antiviral drug discovery, and carbon capture solutions. Researchers are leveraging ML-driven computational models to refine diagnostics, optimise therapeutic strategies, and develop scalable solutions to pressing scientific challenges.
By integrating AI into interdisciplinary research, AI@Ashoka is not only expanding the frontiers of knowledge but also addressing critical questions about AI’s ethical, legal, and societal impact—equipping students and researchers to navigate the future of this rapidly evolving field.
Led by Dr. Balaji Chattopadhyay ( Trivedi School of Biosciences) and Dr. Kritika M. Garg (Ramalingaswami Fellow, Department of Biology), this project aims to address critical challenges in biodiversity conservation.
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Led by Dr. Meghna Agarwala (Department of Environmental Studies), this project is working to improve the accuracy of satellite-based fire detection, which currently identifies less than 30% of fire events. Global fire databases, such as MODIS fire products, report even lower accuracy—under 20%—for detecting small-scale fires, leading to significant omissions.
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Under the guidance of Dr. Madhavilatha Maganti, this project is developing objective measures to assess infants’ neural functioning and cognitive development, aiming to create tools for the early identification of cognitive deficits in high-risk infants.
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Under the supervision of Dr. Debayan Gupta (Department of Computer Science), researchers are exploring the role of tumour-resident stem cells, or cancer stem cells (CSCs), in driving treatment resistance and tumour recurrence. These cells, a highly adaptable subgroup within tumours, pose significant challenges for conventional therapies, making their identification a critical area of study.
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Under the leadership of Dr. Rama Akondy (Department of Biology) and Dr. Debayan Gupta (Department of Computer Science), researchers are developing an AI-based approach for analysing flow cytometry data.
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Under the direction of Dr. Imroze Khan (Department of Biology), this project addresses the growing challenge of antimicrobial resistance (AMR)—a major global health threat caused by microbes developing resistance to widely used antibiotics.
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Supervised by Dr. Kasturi Mitra (Department of Biology), this project focuses on developing computational approaches to identify mitochondria-related quantitative biomarkers for cancer energy metabolism.
The research aims to create AI-ML models capable of predicting mitochondrial function based on mitochondrial structure, leveraging data from the quantitative mito-SiM method developed in the lab. Preliminary models have already been tested for prediction accuracy, and further refinements are underway.
Under the leadership of Dr. Bittu Kaveri Rajaraman (Department of Biology and Psychology), researchers are advancing a non-invasive, long-term biodiversity monitoring system using automatic acoustic sampling methods. This approach aims to track the impact of climate change on ecosystems while also testing conservation interventions.
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Under the direction of Dr. Vidya Avasare (Department of Chemistry), researchers are exploring the potential of covalent organic frameworks (COFs) as efficient materials for capturing atmospheric CO₂ and reducing carbon footprints.
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Dr. Sourav Chatterjee (Department of Chemistry) and Dr. Rintu Kutum (Faculty Fellow, Department of Computer Science, Ashoka University) are leading a research initiative to develop computationally driven antiviral therapeutics against mosquito-borne flaviviruses such as Zika, Dengue, Yellow Fever, and West Nile viruses.
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The advent of AI language tools like Chat-GPT has drastically altered various writing tasks, including ideation, refinement, creativity, and synthesis. However, quantifying and benchmarking the extent to which Chat-GPT (and other such tools) satisfactorily execute these tasks, and how they accommodate discourse patterns and implement discipline-specific academic styles in the social sciences and humanities, remains a challenge.
This study aims to design a comprehensive research framework to address these objectives, ultimately providing insights into the effective integration of AI in academic writing across disciplines in the social sciences and humanities.
