International GILT Research Symposium 2026

This talk examines how virtual reality can be meaningfully situated within specific sociocultural, infrastructural, and pedagogical contexts, rather than deployed as a universal technical solution. Drawing on Gyan Dhara, a curriculum-aligned VR experiential learning platform for Grade 8–9 NCERT Science and Mathematics developed at the Embedded Interaction Lab, IIT Guwahati, I will discuss its design and ongoing field evaluation in rural Indian schools, where sessions are led by trained student champions rather than external facilitators. The project surfaces recurring tensions between technological ambition and situated reality: intermittent connectivity, teacher and student unfamiliarity with immersive interfaces, language and literacy diversity, and the practical constraints of shared hardware in low-resource settings. I will reflect on interaction design choices, from simplified VR login flows to locally adapted content that emerged directly from these constraints, and what they suggest about designing immersive technology as something that must be locally negotiated rather than universally deployed. The talk situates HCI and VR design practice within GILT's broader interest in how technologies are adapted, translated, and localized across social and institutional contexts.

Application of culture-aware and culture-specific approaches to computational musicology and music information research (MIR) have been shown to be effective for analysis of a music culture. However, it is a considerable effort to define research tasks, collect data and develop specific methods for analysis for each music culture, often posing a significant entry barrier. Furthermore, contemporary large-scale, data-driven AI models are predominantly optimized for high-resource music cultures, which often leads to significant performance degradation and restricted utility when applied to under-represented music cultures and domains. A suitable approach is to draw parallels across musical concepts, tasks, data, methods and applications to adapt state-of-the-art models to the distinct requirements of diverse music cultures. This session illustrates such a methodology for adapting and localizing general MIR models for Indian Art Music, focusing on melodic and rhythmic dimensions, and discusses scaling it to build resilient, culture-aware music technologies for diverse musics of the world.

Cross-border AI deployment functions as a complex socio-technical translation governed by distinct geopolitical priorities. Drawing on user data from mobile-based AI applications in Canada and Bangladesh, alongside an autoethnographic perspective as a Bangla-Canadian researcher, this paper examines how AI succeeds, fails, and achieves mainstream viability across asymmetric technological landscapes. It argues that successful AI localisation must transcend mere linguistic translation to achieve ‘algorithmic translation’—the intentional adaptation of data models to fit local socioeconomic realities. By synthesising user data from the Global North and Global South, the paper proposes a hybridised GILT framework that leverages diasporic perspectives to bridge structural divides, mitigate digital hegemony, and foster more culturally equitable globalisation of AI.

The International Library of African Music (ILAM), based at Rhodes University in South Africa, celebrated its 70th anniversary in 2024. In the past decade and more, it has amplified its presence on the continent and globally while developing its role as custodian of traditional southern African music. Through research projects focused on digital return, Eastern Cape jazz heritage and regional traditional music heritage, ILAM has transformed conventional notions of the archive to develop a more inclusive model for decolonial archival practice. This presentation focuses on collaborations with the Ntinga Development Trust in Keiskammahoek, the John Kitime Music Archive in Dar es Salaam, and ‘Sounding Indigenous in South Africa: Music and Performance Heritage in Khoisan Revival’. It argues that principled engagement with research partners and digitisation technologies allow ILAM to act not merely as an archive but as an agent in producing new knowledge and relationships, offering a model for traditional music archives facing technological and human-resource constraints.

This work uses robotic musicianship as a living laboratory for understanding how humans will collaborate with artificial intelligence and embodied machines beyond text-based interfaces. Through custom-built drumming, rapping, and ensemble robots, it investigates musical interaction as a demanding test case for real-time communication, trust, fluency, agency, creativity, and group dynamics. Music compresses broader social and technical problems into observable practice: listening, turn-taking, timing, error recovery, shared attention, embodied gesture, expert judgement, and negotiation of meaning. Recent projects include emotionally expressive musical prosody for robots, real-time rap battle systems, low-cost portable robotic musicians, robot practice and skill-learning systems, and studies of ambiguous failure. Current research examines long-term interaction and group dynamics in repeated rehearsals, performances, educational settings, and public installations, aiming to develop generalisable principles for AI systems that are culturally aware, socially responsive, transparent, and useful in creative and expert practice.

This paper explores audiovisual media as both a methodological tool and an analytical lens within contemporary ethnomusicology, focusing on the documentary In Process: M.Cabral (PCC) Camp. Directed by Pedro Roxo and Dina Prant, the observational film documents an intensive music camp held in the Lisbon metropolitan area in September 2025, bringing together producers and hip-hop artists from Cape Verde, Portugal, and the Cape Verdean European diaspora to create new songs and collaborate on the new album of Cape Verdean rapper M.Cabral (PCC). The study emphasises how ethnographic filmmaking captures nuanced layers of interaction, bodily practices, sonic textures, trial-and-error, creative blocks, and spontaneous breakthroughs that conventional textual descriptions fail to transmit. It shows how geographic displacement and digital connectivity converge in the modern studio to redefine Lusophone post-colonial musical identities through shared lived creative experience. Keywords: Audiovisual Ethnomusicology; Music Camp; Cape Verdean Diaspora; Lusophone Music; Music Production.

This presentation examines the Aarsh Parampara (ancient Vedic tradition) and the Prachin Padhati (ancient methodology) practised at Gurukul Khanpur, Haryana, India. It presents the technical precision of Sanskrit linguistics, specifically analysis of Aarsh Granths such as the Ashtadhyayi and Mahabhashya, and shows how gurukul practices such as the Yajyashala (a dedicated pavilion for fire rituals) and Gaushala (a cow shelter) facilitate experiential learning. Through documentation of daily practices and testimonies of shishyas, the paper demonstrates how a guru-centred approach safeguards India’s educational heritage while addressing contemporary needs for ethical character-building. It contributes to the GILT symposium’s exploration of diverse knowledge systems by showing how ancient plural logics continue to inform interdisciplinary education and intellectual development.

The translation of Buddhist scriptures in medieval China has long been understood as a collaborative enterprise involving foreign monks, Chinese scribes, and patrons. Drawing upon prefaces, colophons, catalogues, and monastic biographies, this paper reconsiders medieval translation groups as translation organizations and explores the processes through which they gradually acquired institutional form. Using institutional logics as an analytical framework, it situates Buddhist translation at the intersection of religious authority, philological credibility, political patronage, and organizational reproduction. Translation organizations were also arenas of competition for resources, prestige, personnel, imperial recognition, and interpretive authority. Through cases including Lokakṣema, Dharmarakṣa, Dao’an, Kumārajīva, and Xuanzang, the paper traces differentiated translational roles, organizational coordination, and textual legitimation, arguing that institutionalization emerged cumulatively from sustained interaction among organizations in a shared yet competitive ecosystem.

Traditional plant-based healing practices embody a distinct institutional logic shaped by centuries of vernacular observations, community-held knowledge, and localized ecological interpretations. These systems nevertheless face marginalization through regulatory restrictions, changing lifestyles, and formal scientific skepticism. Based on genetic and ethnobotanical field research documenting traditional healers and indigenous medicinal plants within the Dhosi hills and sacred groves, this paper investigates how localized indigenous knowledge systems coexist with prevailing modern healthcare frameworks. Preserving biological and medical diversity requires mutual translation rather than complete assimilation. Harmonizing global clinical protocols with localized traditional wisdom can enable healthcare ecosystems to use valuable natural therapies while upholding cultural grounding and community integrity.

Glioblastoma multiforme (GBM) is the most aggressive primary tumor of the central nervous system, characterized by molecular and transcriptomic heterogeneity underlying therapeutic resistance and recurrence. This study presents an integrative computational framework combining Iterative Non-negative Matrix Decomposition (INMD) with a Shannon entropy-based Heterogeneity Index to quantify sample-level transcriptomic heterogeneity. Data from The Cancer Genome Atlas comprise 174 samples: 5 normal, 13 recurrent tumor, and 156 primary tumor samples. Differentially expressed genes were identified and ranked using the in-house FASE pipeline, then used with the design matrix for computational modelling and heterogeneity assessment. The integrated analyses indicated higher dominance of primary and recurrent tumors with moderate but biologically significant variability, providing a robust and interpretable approach for quantifying sample-level heterogeneity across GBM samples. Keywords: Glioblastoma Multiforme; Intratumoral Heterogeneity; Iterative Non-negative Matrix Decomposition; Shannon entropy; Heterogeneity Index.

Grounded in Job Demands–Resources theory, the study investigates the impact of abusive supervision on employees’ overall job performance within Pakistan’s management consultancy sector. Using a quantitative, three-wave time-lagged design, data were collected from 635 employees to examine the mediating role of employee cynicism and the moderating effect of perceived co-worker support. Structural equation modelling shows that abusive supervision increases cynicism, which undermines performance, while co-worker support buffers both the direct relationship and the indirect effect on performance. The findings highlight peer support’s protective capacity in high-stress environments and suggest zero-tolerance policies for abusive leadership alongside collaborative team cultures.

This paper examines how AI-generated or AI-assisted climate-risk knowledge relates to place-based social vulnerability in Hong Kong’s typhoon and Black Rainstorm preparedness. Using a qualitative case-study and document-analysis design, it analyses eight core sources, a 642-respondent worker survey, and 152 officially recorded adverse-weather-related employee-compensation cases. Evidence is coded for predictive localisation, impact localisation, vulnerability contextualisation, and formal/practical institutional mediation, with translation coding across technical, institutional, practical, and feedback settings. The analysis finds that forecasting is strongly localised meteorologically through local observations, post-processing, and forecaster judgement, while vulnerability becomes most explicit when warnings are translated into labour, transport, service, and organisational arrangements. The paper argues that localising Climate AI is not only finer prediction but whether risk knowledge can become usable protective capacity for differently situated groups.

This presentation showcases ongoing research projects and activities at the GILT Research Centre.

This paper examines the impact of artificial intelligence in Human Resource Management on employees’ psychological relationship with their organizations. It focuses on Human-Augmented HRM: the strategic use of AI to augment human abilities. Drawing on Institutional Logics Theory, it investigates how technology in HRM shapes Organizational Identification through perceptions of autonomy, influence, and control over work; the role of Perceived Human Agency; and how Algorithmic Transparency can enhance or hinder the relationship. Primary data were collected through a structured questionnaire among Gen Z employees in selected Indian organizations and analysed using Partial Least Squares Structural Equation Modelling. The study addresses how local workforce norms mediate global technological logic, balancing systemic standardization with culturally grounded autonomy, and explores implementation without sacrificing human agency.

This study explores whether different messages about the importance of education can be conveyed to India’s diverse cultural, linguistic, social, and economic groups to build educational aspirations among girls. It treats the value of education as locally constructed and potentially changeable through culturally relevant social marketing. The proposed framework moves educational communication from information provision toward messages that are personally, socially, and culturally meaningful to girls and their families. Mechanisms include language localization, cultural relevance, family and community influences, role models, perceived value, gender norms, message authenticity, and local context. A comparative mixed-method design will explore the effects of GILT-inspired messages on educational value, cultural relevance, aspirations, parental support, and intention to pursue further education, offering an evidence-based framework for corporations, foundations, NGOs, educational institutions, and social marketing agencies.

The electric-vehicle battery industry provides a paradigm of GILT tensions, with technologies emerging in one context translated and localized in other technical, economic, and policy frames. This paper examines India’s nascent industrial base from a global-to-local perspective. By 2023, the global battery market had reached $104 billion and CATL held about 37% market share, while China dominated cathode materials, anode graphite, and cell production. India remains structurally vulnerable: EV sales crossed 2 million in 2024, around 78% of battery cells are imported from China, and domestic demand is expected to grow from 4 GWh in 2023 to 139 GWh by 2035. The average indigenisation score across eleven manufacturing stages is 3.2/10, and the ₹18,100 crore ACC PLI scheme did not meet 2024 goals. Using the GILT framework, the paper conceptualises indigenisation as re-encoding global supply-chain logic into India’s institutional, regulatory, and geopolitical setting and recommends eight policy interventions.

Digital globalization—through the internet, digital platforms, ICT, payment systems, electronic banking, artificial intelligence, and digitally delivered services—is transforming production, trade, investment, and economic interaction. This study examines selected Asian economies in the Global South using secondary indicators including internet users, broadband subscriptions, ICT service exports, foreign direct investment, trade openness, GDP per capita, and economic growth. The comparative design covers India, China, Hong Kong, Singapore, Malaysia, Thailand, Indonesia, Vietnam, and the Republic of Korea, with data from the World Bank, International Telecommunication Union, Asian Development Bank, International Monetary Fund, and UNCTAD. Descriptive statistics, trend analysis, correlation, and panel regression will be used to identify links between digital globalization and productivity, exports, innovation, and wider financial and economic outcomes.