Other links:
Other links:
Projects
Faculty: Sudipta Tung, Fellow, Department of Biology, Ashoka University
Co-supervisor name: NONE
Department/Research Centre: Biology
Project Description: This project explores how mismatched diets between development and adulthood shape evolution across biological scales—from individual performance to molecular change. Using fruit fly populations that have evolved for many generations on different combinations of protein-rich and carbohydrate-rich diets, we will ask how early-life and adult nutrition interact to influence growth, reproduction, and resilience. By transferring flies between their native and non-native diets, we can see whether evolution under one condition limits or enhances their ability to cope with another. Students will measure visible traits like development time, egg size, and activity, alongside molecular readouts of key metabolic and reproductive pathways. Together, these experiments reveal how nutrition not only alters short-term physiology but also drives long-term adaptation—linking diet, development, and evolution in a unified framework that connects everyday biology to foundational evolutionary questions.
Duration (in weeks): 8 weeks (between May – August)
Start date: 5/15/2026
End date: 8/15/2025
Level of Interns: Senior Undergraduates OR Master’s Students
Max Number of interns accepted on this project: 3
Project type: Lab project
Technical skill/knowledge requisites: Nil
Faculty: Anup Padmanabhan, Assistant Professor of Biology, Co-ordinator (Ph.D. program in Biology) Ashoka University
Co-supervisor name:Tanushree Sinha
Department/Research Centre: Biology
Project Description: Pseudomonas infects a wide variety of hosts , ranging from plants to humans. How is a single pathogen able to infect wide variety of hosts ? Does it involve a shared mechanism or does the pathogen employ distinct methods to different hosts ? We will investigate these questions using the soil nematode, C. elegans as a model host. We will employ a wide variety genetics, biochemistry and cell biology techniques in this project.
Duration (in weeks): 10 weeks (15 June – 24 August)
Start date: 5/18/2026
End date: 7/31/2026
Level of Interns: Senior Undergraduates or Master’s Students
Max Number of interns accepted on this project: 2
Project type: Lab project
Technical skill/knowledge requisites: Commitment, hard working and Basic Lab etiquette
Faculty: Bittu K R, Associate Professor of Biology and Psychology
Co-supervisor name: NONE
Department/Research Centre: Biology and Psychology
Project Description: Our lab works on various puzzles in animal communication, sensation and cognition, and the evolution and ecology of neural systems.
We work on 3 main projects in the lab:
We look at the structural and neurophysiological adaptations that enable cricket/bushcricket song: on the systems involved in song production and song perception, acoustic niche partitioning and masking, song localization, predator avoidance and eavesdropping.
Quantitative and mathematical cognition in zebrafish and dogs: How do our brains produce math? We investigate this question at a behavioural level in both zebrafish and dogs, with an aim to establish zebrafish as an attractive neural model system for this behaviour.
Neuroeconomics in zebrafish: We are interested in quantitative decision making between various “goods” of interest to zebrafish, as part of a collaborative project to set up a zebrafish model system for economic decision making. We can then work with collaborators to examine the neural basis of these behaviours using calcium imaging of the whole brain in awake, behaving fish.
Duration (in weeks): 6 weeks (July – August)
Start date: 07/01/2026
End date: 8/15/2026
Level of Interns: Senior Undergraduates or Master’s Students
Max Number of interns accepted on this project: 3
Project type: Combination of field & lab project
Technical skill/knowledge requisites: No, just enthusiasm for the field
Faculty: Aalok Thakkar, Associate Professor of Computer Science.
Co-supervisor name: NONE
Department/Research Centre: Computer Science
Project Description: Several concerns about large language models (LLMs) persist, particularly regarding their robustness against adversarial inputs, data privacy, and structured reasoning capabilities. This project aims to address these challenges through a comprehensive compositional verification framework. The primary objective is to decompose the correctness specification into distinct correctness criteria for each layer of the LLM architecture. By developing verification methods tailored to these individual layers, we can establish an assume-guarantee style verification process that ensures each component meets its specified requirements. This modular approach not only facilitates easier debugging and maintenance but also strengthens the overall security posture of LLMs by enabling targeted interventions in identified vulnerable areas. In particular, the project will focus on verifying the robustness of LLMs against adversarial attacks, ensuring that they can withstand unexpected inputs without compromising their functionality or integrity. Additionally, we will explore methods to safeguard data privacy, employing formal techniques to prevent leakage of sensitive information during model training and inference. The project offers opportunities for senior undergraduates and master’s students from diverse backgrounds to engage in literature reviews, algorithm development, implementation, and research. By participating in this initiative, students will gain practical skills in compositional verification and AI while contributing to the advancement of robust and privacy-preserving technologies.
Duration (in weeks): 10 weeks (between June – August)
Start date:5/15/2025
End date: 8/24/2025
Level of Interns: Senior Undergraduates or Master’s Students
Max Number of interns accepted on this project: 3
Project type: Online
Technical skill/knowledge requisites: Familiarity with LLM architecture and fundamentals of verification, strong programming skills
Faculty: Aparajita Dasgupta, Associate Professor of Economics
Co-supervisor name: NONE
Department/Research Centre: Economics
Project Description: In this project we aim to investigate how access to health insurance bears upon health investments in both curative as well as preventive healthcare and child health outcomes in the developing country setting.
Duration (in weeks): 10 weeks (between June – August)
Start date: 5/21/2025
End date: 8/21/2025
Level of Interns: Senior Undergraduates or Master’s Students
Max Number of interns accepted on this project: 3
Project type: Online
Technical skill/knowledge requisites: Knowledge pf Stata, Python, GIS Skills would be a bonus. Data analysis using stata/R and helping with manuscript preparation including reviewing literature, adding collated results on Latex, Copy editing of draft, finding new datasets relevant for the project Students should be proficient in data handling using stata or R and should have a working knowledge of latex. GIS skills would be greatly appreciated. Interested applicants should send their CV and a writing sample that has used data analysis. Applicants will be shortlisted based on a stata-based test. Experience with large scale household surveys will be good.
Faculty: Aalok Thakkar, Assistant Professor of Computer Science, Ashoka University.
Co-supervisor name: None
Department/Research Centre: Department of Computer Science
Project Description: Parliamentary debates are among the most consequential forms of political discourse in a democracy, shaping policy, ideology, and public reasoning. Yet, despite their historical and analytical value, the proceedings of the Indian Parliament largely remain as vast archives of unstructured text—difficult to search, analyse, or interpret systematically. This project aims to design a computational system that structures and analyses this discourse through multi-layered semantic modelling and logical provenance tracking. By integrating methods from Natural Language Processing (NLP), knowledge representation, and automated reasoning, the project will transform parliamentary text into a structured, explainable, and queryable resource for political and linguistic analysis.
The core methodology involves a multi-layered semantic categorisation of debate transcripts. Using transformer-based language models fine-tuned for Indian political language, the system will automatically tag speech segments. The categorisation schema includes: Policy Domain (e.g., economy, defence, agriculture); Stance Polarity (support, opposition, neutral); Speech Act (e.g., assertion, rebuttal, question); and Rhetorical Device, with a specific focus on identifying the use of poetry, literary allusions, and cultural metaphors. A further layer of analysis will classify the Content of Debate, distinguishing between procedural motions, legislative details, constituency concerns, and ideological rhetoric. This tagged data will populate a provenance knowledge graph, linking claims and tracking their evolution. The final deliverable is an interactive tool for researchers to query this structured corpus, enabling systematic analysis of how specific topics, rhetorical strategies, and arguments develop over time.
Duration (in weeks): 10 weeks (15 June – 24 August)
Start date: 5/01/2026
End date: 8/31/2026
Level of Interns: Senior Undergraduates or Master’s Students
Max Number of interns accepted on this project: 3
Project type: Lab Project
Technical skill/knowledge requisites: Python Programming, Basic ML
Faculty: Meghna Agarwala, Assistant Professor, Environmental Studies,
Co-supervisor name: Shikhar Srivastava
Department/Research Centre: Environmental Studies
Project Description: Human-elephant conflict (HEC) is a leading source of elephant mortality across the world and managers are increasingly focused on mitigating HEC. Because a large number of deaths are caused by sudden encounters between humans and elephants, the Forest Department is interested in working with us to develop an early warning signal to prevent sudden encounters. For this, we expect to collect acoustic recordings of elephant vocalizations at different elephant densities and in different habitats to develop a Convolution Neural Network (CNN) to detect elephant presence at a distance of ~3 km. Further, in order to deploy an early warning system that is effective in mitigating HEC, we need to understand how local residents negotiate HEC. We will conduct social surveys in villages adjoining our study areas to understand perceptions towards HEC and identify villages where conflict is only due to damages, as opposed to those where conflict is due to other under-lying and deep-rooted causes. We will work with villages to devise a deployment strategy for the early warning system. For villages where conflict has other deep-rooted causes, our surveys will inform us on best strategies to supplement our early warning system in mitigating HEC.
Duration (in weeks): 8 weeks (May – August)
Start date:07/01/2025
End date:8/31/2025
Level of Interns: Senior Undergraduates or Master’s Students
Max Number of interns accepted on this project: 2
Project type: Combination of field & lab project
Technical skill/knowledge requisites: Analyse data in lab.
Faculty: Meghna Agarwala, Assistant Professor, Environmental Studies,
Co-supervisor name: Jishnu Borgohain
Department/Research Centre: Environmental Studies
Project Description: Natural systems are dynamic and not static and are influenced by historical legacies. Our work in Central India finds that forests have long been burned, and forests may have been co-created by humans. We would like a David Attenborough-style documentary made on the work, its findings and implications for understanding human-nature relations. Students can take fresh footage at our field station in Pachmarhi and interview traditional forest burners as well.
Duration (in weeks): 8 weeks (May – August)
Start date: 5/15/2025
End date: 7/15/2025
Level of Interns: Senior Undergraduates or Master’s Students
Max Number of interns accepted on this project: 2
Project type: Combination of field & lab project
Technical skill/knowledge requisites: Media, documentary film-making/long-form journalism.
Faculty: Simantani Ghosh, Assistant Professor of Psychology
Department/Research Centre: Psychology
Project Description: Violence against women, particularly in the form of Intimate Partner Violence (IPV), remains a grave concern worldwide. IPV not only inflicts physical harm but also leaves enduring psychological repercussions. The World Health Organization reported that, as of 2018, approximately one in three women globally experienced physical and/or sexual violence from an intimate or non-intimate partner. In India, Intimate Partner Violence takes on a broader dimension and has to be defined in terms of domestic violence (DV). DV in the South Asian context is deeply entrenched in cultural norms that subordinate women to men, reflecting prevalence rates similar to global figures. However, the nature of abuse extends beyond the conventional understanding of IPV, as Indian women often cohabit with not just their spouses but also marital relatives who can be perpetrators. Emergent data suggests that domestic violence among married women reportedly doubled between 2014-15 and 2019, despite NFHS surveys more or less replicating the WHO statistics (1 in 3 women, approximately) with respect to DV exposure. Episodic framing of issues pertaining to domestic violence, as is common in the literature, fails to capture the nuanced psychological consequences of sustained, and repetitive domestic violence. Researchers argue for a continuous trauma framework to better map the pervasive and chronic nature of domestic violence in India. The complex trauma theory, initially developed for childhood sexual abuse survivors, emerges as a relevant lens for understanding the multilayered trauma experienced by Indian women. Complex trauma theory posits that prolonged, inescapable trauma results in psychological disturbances beyond those defined by the clinical construct of PTSD. For Indian women, the pervasive environment of control, oppression, and abuse throughout childhood, adolescence, and adulthood aligns with the criteria of complex trauma. Our preliminary data (unpublished) also suggests that ever partnered Indian women trapped in abusive relationships often display psychological disturbances that are well aligned with the disorders of self-organisation (DSO) cluster of symptoms that complex trauma theory accommodates, which include interpersonal disturbances, negative self-concept and extensive somatic symptoms. In this study, we ask the overarching question whether Complex Trauma theory can be utilised to investigate the consequences of domestic violence in ever-partnered adult Indian women.
Duration (in weeks): 10 weeks
Start date: 6/15/2025
End date: 8/24/2025
Level of Interns: Senior Undergraduates or Master’s Students
Max Number of interns accepted on this project: 3
Project type: Online
Technical skill/knowledge requisites: Psychometric theory, null hypothesis testing, multiple regression, mediation and moderation
Faculty: Meghna Agarwala, Associate Professor of Environmental Studies, Ashoka University
Co-supervisor name: Shikhar Srivastava
Department/Research Centre: Environmental Studies
Project Description: AI/ML allows faster processing of data, imagery, acoustics from various sources, thus expediting our ability to identify, quantify, differentiate and understand. In this project, students with pre-existing skills in data analysis–whether statistics or ML–will use these skills to answer important questions related with environmental history, forest use and well-being, and develop products for aiding conservation such as early warning systems and other detectors. Please look at my website for more details.
Duration (in weeks): 10 weeks (June – August)
Start date: 5/15/2026
End date: 7/14/2026
Level of Interns: Senior Undergraduates or Master’s Students
Max Number of interns accepted on this project: 3
Project type: Lab project
Technical skill/knowledge requisites: AI/ML, statistics
Faculty: Rama Akondy, Assistant Professor of Biology
Co-supervisor name: NONE
Department/Research Centre: Trivedi School of Biosciences
Project Description: CD8+ T cells are crucial for detecting and eliminating infected or abnormal cells by recognizing viral epitopes presented on MHC class I molecules. The diversity of Human Leukocyte Antigen (HLA) alleles across populations significantly shapes the range of viral epitopes recognized by CD8+ T cells. India, with its considerable genetic diversity, has a unique distribution of HLA alleles that may influence immune responses to various viral infections. This project aims to identify widely expressed HLA alleles in Indian populations and map the diversity of viral epitopes recognized by CD8+ T cells. The study will involve mining immunological databases such as the Immune Epitope Database (IEDB) to extract viral epitopes that bind to the most prevalent HLA alleles in India. Special focus will be given to understanding how these differences in HLA alleles influence immune responses to viral infections. Viruses such as Respiratory Syncytial Virus (RSV), Influenza, SARS-CoV-2, and Dengue are of particular interest, but the student may choose to explore others that are relevant to the Indian context. The project will begin by identifying the most widely expressed HLA alleles in Indian populations through analysis of genetic studies and databases. Following this, viral epitopes from the selected viruses will be retrieved, and their binding affinities to the identified HLA alleles will be analyzed using computational tools. This will help determine which viral peptides are likely recognized by CD8+ T cells in India and highlight differences in immune recognition based on HLA diversity. The study will also differentiate between conserved epitopes, which are recognized across various populations, and those that vary based on HLA allele types, providing insights into population-specific immune responses.
Duration (in weeks): 6 weeks (15 June – 24 August)
Start date:07/01/2025
End date: 8/23/2025
Level of Interns: Senior Undergraduates or Master’s Students
Max Number of interns accepted on this project: 1
Project type: Online
Technical skill/knowledge requisites: Basic understanding of the immune system, MHC and ability to use computational tools such as IEDB is preferred.
Faculty: Sandeep Ameta, Assistant Professor of Biology
Co-supervisor name: NONE
Department/Research Centre: Biology
Project Description: Liquid-liquid phase separation (LLPS) is a notable feature of biological systems and plays a crucial role in spatiotemporal regulation. Furthermore, by acting as reaction crucibles, phase-separated droplets have also been assumed to play a major role in the emergence of life on early Earth. LLPS involves various non-covalent interactions, such as π- π, dipole-dipole, and hydrogen bonding, between biomolecules, resulting in a condensed internal microenvironment inside these phase-separated droplets. In vitro, such a complex environment can be mimicked by the phase separation of different polymers, including RNA and peptides, resulting in ‘liquid-like’ droplets. Even though these droplets support various biomolecular functions, we lack a comprehensive and quantitative understanding of how the internal heterogeneous and crowded environment influences the dynamics of biomolecules.
Employing various biochemical and biophysical approaches, our lab is interested in a quantitative understanding of parameters governing the dynamics of structured and functional RNAs in the complex environment of liquid-liquid phase separation. Furthermore, we also exploit these phase-separated droplets as a protocell model to address some pertaining questions regarding the emergence of evolvable systems in the context of the origins of life.
Duration (in weeks): 8-10 weeks (June -August with flexible dates)
Start date: 6/1/2025
End date: 8/16/2025
Level of Interns: Senior Undergraduates or Master’s Students
Max Number of interns accepted on this project: 1
Project type: Lab project
Technical skill/knowledge requisites: Biochemistry or Molecular Biology or Biophysics
Faculty: Saikat Majumdar, Assistant Professor of Biology
Co-supervisor name: NONE
Department/Research Centre: English & Creative Writing
Project Description: I’m looking to appoint an editorial/research assistant for my forthcoming book, “The Critic as Artist: An Autoethnography of World Literature” (New York: Bloomsbury, forthcoming 2027). BRIEF DESCRIPTION OF THE BOOK: “The Critic as Artist: An Autoethnography of World Literature” looks at the natural entanglements of intellectual analysis and imaginative creation through the fused sensibility of what is sometimes called creative criticism. While acknowledging canonical western practices in this field, such as by the English and the German Romantic poets and philosophers, and practitioners such Matthew Arnold and T.S. Eliot, it seeks to shift the primary focus of this entanglement to questions of embattled and marginal identities, which also shapes its activist form. Key here are the radically imaginative criticisms of Kamau Braithwaite on language, nation and poetic voice in the Caribbean, language and power in sub-Saharan Africa by Ngũgĩ wa Thiong’o, experimentation, autoethnography, teaching, and activism in the works of Alice Walker and Trinh T. Minh-Ha, ancient performative and communal traditions in the critical essays and A.K. Ramanujan, and marginal aesthetic and literary traditions in the work of Zadie Smith, Amit Chaudhuri and Hoshang Merchant. These thinkers are preoccupied with themes that cannot be neither exclusively theorized, nor exclusively embodied: tradition, materiality, voice, form and performance, teaching and community, culture, literacy and orality, place and home – realities where the transparency of the referential argument conflicts with the unexpected polemics of sensory life.
Duration (in weeks): 8-10 weeks (June -August with flexible dates)
Start date: 6/6/2026
End date: 8/6/2026
Level of Interns: Senior Undergraduates or Master’s Students
Max Number of interns accepted on this project: 2
Project type: Online
Technical skill/knowledge requisites: Should be an advanced student of literature, senior undergraduate, Masters, or Ph.D. Background in creative writing welcome but not essential.
Faculty: Aalok Thakkar, Assistant Professor of Computer Science, Ashoka University.
Co-supervisor name: None
Department/Research Centre: Department of Computer Science
Project Description: This project develops a computational and statistical framework to rigorously quantify the carbon sequestration potential of Enhanced Rock Weathering (ERW). ERW is a negative-emissions technology that involves applying crushed silicate minerals to soils, but its efficacy is highly dependent on spatially variable factors like soil chemistry, hydrology, and mineralogy. The core challenge is to move from point-based field measurements to robust, landscape-scale predictions with mathematically sound uncertainty quantification. Our approach centres on constructing spatially explicit models that provide formal guarantees on prediction confidence and derive lower bounds on carbon removal estimates, which are critical for the credibility of carbon markets.
The methodological foundation employs hierarchical Bayesian models, primarily Gaussian Process (GP) regression, to create probabilistic surfaces of key ERW variables. This provides a formal guarantee: for any given region, we can compute a high-probability confidence interval for the carbon drawdown rate, enabling stakeholders to make decisions based on worst-case scenarios (lower bounds) rather than optimistic averages. A critical component of ensuring these guarantees is optimal spatial sampling. Data collection for ERW is expensive, making the efficiency of measurement campaigns paramount. We frame this as an optimal experimental design problem.
The final deliverable is a decision-support system that outputs maps of predicted carbon sequestration with statistical certainty. This framework provides the necessary computational rigour to underpin verification in carbon markets, offering defensible, conservative estimates of ERW efficacy that are essential for risk assessment, policy-making, and scalable deployment.
Duration (in weeks): 10 weeks (15 June – 24 August)
Start date: 5/01/2026
End date: 8/31/2026
Level of Interns: Senior Undergraduates or Master’s Students
Max Number of interns accepted on this project: 3
Project type: Lab Project
Technical skill/knowledge requisites: Statistics, Programming
Faculty: Sandeep Ameta, Assistant Professor of Biology
Co-supervisor name: NONE
Department/Research Centre: Biology
Project Description: Liquid-liquid phase separation (LLPS) is a fundamental process integral to biological systems. Owing to their spontaneous formation, LLPS droplets have also been envisioned as model protocells that drive pre-cellular evolution by supporting several biomolecular functions crucial to the emergence of life on the early Earth. Despite these crucial roles, the internal dynamics of the microenvironment of LLPS droplets remain poorly understood, and we lack mechanistic details on how the internal packing of these phase-separated droplets drives the dynamics of the encapsulated molecules. The LLPS droplets, in addition to being densely packed, are very heterogeneous inside. There is evidence of the formation of a dynamic polymer meshwork or percolated network, resulting in different behaviours of interacting and encapsulated biomolecules compared with a well-mixed, diluted solution due to diffusion-limited and volume-exclusion effects. One way to elucidate dynamics is to apply FCS- and FCCS-based methods to measure the dynamics of the encapsulated macromolecule within these droplets at unprecedented resolution. Employing biochemical and biophysical approaches, our lab aims to develop a quantitative understanding of the parameters governing the dynamics of functional RNAs in the complex environment of LLPS at high spatiotemporal resolution.
Interested students will select one of the protein condensate systems in the lab and elucidate the dynamics of RNA-protein interactions within the LLPS environment.
Duration (in weeks): 8-10 weeks (June -August with flexible dates)
Start date: 7/1/2026
End date: 8/31/2026
Level of Interns: Senior Undergraduates or Master’s Students
Max Number of interns accepted on this project: 1
Project type: Lab project
Technical skill/knowledge requisites: Interest in Biophysics
Faculty: Priyam Verma, Assistant Professor of Economics
Co-supervisor name: Abhishek Rai
Department/Research Centre: Department of Economics
Project Description: As India continues to urbanize, an increasing share of national economic growth will be generated by its cities. The pace at which individual cities grow depends critically on their ability to produce goods and services for markets beyond the local economy. Cities with strong tradable sectors can tap into external demand, allowing firms to scale up and benefit from economies of scale, learning-by-doing, and agglomeration effects. Following the emerging urban economics literature, we refer to such cities as production cities. In contrast, consumption cities are dominated by non-tradable activities—such as retail, healthcare, education, and construction—and are therefore constrained by local purchasing power, limiting their long-run growth potential.
In India, tradable activity remains highly concentrated in a small number of large metropolitan areas, while most tier-2 and tier-3 cities continue to rely heavily on locally oriented consumption sectors. Understanding why only a subset of Indian cities has evolved into production cities requires examining two interrelated mechanisms. First, the internal spatial organization of economic activity within cities—including commuting infrastructure, land-use regulations, and the spatial proximity and interaction between formal and informal firms—shapes productivity and labor market access. Second, transport connectivity across cities determines access to external markets and intermediate inputs, influencing firms’ incentives to specialize in tradable production. The interaction between these intra-city frictions and inter-city market access ultimately determines whether a city becomes a production hub or remains a consumption center.
This project seeks to explain the uneven emergence of tradable specialization across Indian cities by jointly quantifying the roles of internal urban frictions and external connectivity. The analysis is organized around three core questions. First, how do within-city spatial patterns of firms and residents differ between production and consumption cities? Second, are differences in tradable specialization driven more by internal constraints—such as commuting costs and land-use restrictions—or by external factors related to market access and trade costs? Third, how does a city’s internal geography shape access to economic opportunities, particularly for women seeking formal-sector employment?
Duration (in weeks): 8-10 weeks (June -August with flexible dates)
Start date: 5/1/2026
End date: 6/30/2026
Level of Interns: Master’s Students
Max Number of interns accepted on this project: 2
Project type: Lab project
Technical skill/knowledge requisites: QGIS, MATLAB or Python
If you have questions about the Ashoka International Summer Research Programme (AISRP), please contact:
Email: globaleducation@ashoka.edu.in
LinkedIn: LinkedIn
Instagram: Instagram
