Liver disease is rapidly emerging as a major global health burden, with cirrhosis contributing significantly to mortality worldwide. In India alone, liver failure is estimated to cause around 250,000 deaths annually, underscoring a growing and under-recognized public health crisis.
The problem is twofold-late detection and lack of practical diagnostic tools, creating a clear need for simple, accessible alternatives.
In this context, research from an Indian doctor has gained international attention for proposing a practical, low-cost solution using routine laboratory parameters. The work focuses on commonly available indices-Neutrophil-Lymphocyte Ratio (NLR) and AST-to-Platelet Ratio Index (APRI)-derived from standard blood tests (CBC and LFT), helping to predict severity and outcomes in cirrhosis.
The findings highlight how these markers can be used for rapid assessment and risk stratification, particularly in high-volume settings where time and resources are limited.
Importantly, such tools can be deployed without additional cost or infrastructure.
For India, this is where the impact is direct. A large proportion of patients present late, often to resource-constrained hospitals managing high patient loads. In such settings, solely relying on expensive scoring systems or delayed investigations may even cost lives. These tools could allow clinicians to identify high-risk patients early, prioritize care, and make faster decisions using readily available tests, potentially improving outcomes at scale.
His research has been invited for a podium presentation and discussion at the 24th European Congress of Internal Medicine (ECIM 2026), held at the historic Hofburg Palace from March 25&ndash;28, 2026-a leading global platform for internal medicine.
The abstracts (Nos. 0955 &amp; 0958), titled:
&ldquo;India&rsquo;s Cirrhosis Pivot&rdquo;
&ldquo;Inflammation Speaks: Neutrophil-Lymphocyte Ratio and AST-to-Platelet Ratio Index (APRI) Redefine Rapid, Low-Cost Prognostication for Cirrhosis in Mumbai, India&rdquo;
address both the changing epidemiological landscape of cirrhosis in India and the need for accessible prognostic tools.
The researcher, Dr. Udit Bhaskar Vaish, a 27-year-old Indian doctor from Delhi and currently a Senior Resident in General Medicine at Dr. D.Y. Patil Medical College, Navi Mumbai, is part of a new generation of clinicians focusing on clinically applicable, resource-sensitive research.
Speaking on the work, he said: &ldquo;Simple and accessible medical tools can make a big difference in managing serious diseases like cirrhosis, especially in resource-limited settings.&rdquo;
The significance goes beyond individual recognition. It reflects a broader shift-Indian clinical research increasingly aligning with real-world healthcare needs, where scalability, cost, and speed matter as much as accuracy.
Acknowledgement
"Indian medical landscape is changing rapidly," said Dr. Vaish. "We are seeing a seismic improvement in patients with viral cirrhosis thanks to newer government-led initiatives for antiviral rollouts; however, with the rising incidence of fatty liver and alcoholism, a quick risk stratification tool is the need of the hour. With more such tools in the arsenal of Indian doctors, our clinicians will be better equipped than ever to handle the tremendous patient load they are subjected to every day."

French watchmaker Briston has officially entered the Indian market in partnership with Just In Time, marking a significant milestone in the brand&rsquo;s global expansion strategy. Known for its distinctive blend of neo-vintage design and contemporary craftsmanship, Briston aims to appeal to India&rsquo;s growing base of style-conscious consumers.
Founded in 2013 by Brice Jaunet, Briston was created to reinterpret traditional watchmaking codes by merging classical horology with a relaxed, modern sensibility. Positioned as a &ldquo;Premium Sport Chic&rdquo; brand, it reflects a refined balance of elegance and ease, rooted in the French art de vivre.
A defining element of Briston&rsquo;s identity is its unconventional use of cellulose acetate-a material more commonly associated with luxury eyewear. By incorporating this into watchmaking, particularly in its signature tortoiseshell-style cases, the brand has introduced a bold and tactile design language that stands apart in a traditionally conservative category. This innovative approach underscores Briston&rsquo;s commitment to design-led differentiation and creative expression.
Over the years, Briston has established a growing international presence across Europe, Asia, and the Middle East, resonating with a new generation of consumers who view watches as an extension of personal style. Its collections, including the iconic Clubmaster, are recognized for their distinctive square cases, layered dials, and interchangeable elements, offering versatility for everyday wear.
As part of its India debut, Briston is also introducing the Streamliner Kennedy collection, one of its most contemporary and design-forward lines. Inspired by Art Deco aesthetics, the collection features bold square cases, double-layered dials, intricate guilloch&eacute; finishes, and refined detailing-bringing together technical precision with elevated design sensibilities.
Combining reliable movements with thoughtful design and accessible luxury, Briston continues to uphold its core philosophy of being Attractive, Affordable, and Accessible.
Speaking on the launch, Brice Jaunet, Founder of Briston, said: &ldquo;We are delighted to partner with Just In Time, a collaboration driven by shared values of dedication, excellence, and a deep understanding of a demanding market. Together, we look forward to bringing Briston&rsquo;s distinctive design and unique identity to a wider audience.&rdquo;
Ronak Shah, CEO of Just In Time, added: &ldquo;At Just In Time, we are always looking to introduce brands that offer a fresh and differentiated perspective. Briston&rsquo;s strong design identity and unconventional approach make it a compelling addition to our portfolio, especially for consumers seeking watches that go beyond functionality to become a true style statement.&rdquo;
With its India launch, Briston introduces not just a collection of timepieces, but a broader design philosophy-one that seamlessly blends heritage with modernity, and craftsmanship with individuality.
Briston watches are now available across Just In Time boutiques and online platforms.
About Briston:
Briston is an independent French watch company founded in 2013 by Brice Jaunet, a seasoned professional with over 15 years of experience in the luxury watch industry. The brand combines French elegance with a distinctive British-inspired sporty-chic style, drawing influence from Oxford culture and classic sports such as polo and rowing. Known for its signature tortoiseshell acetate cases sourced from Mazzucchelli, Briston has carved a niche in accessible luxury by offering stylish, versatile timepieces with a contemporary edge.
About Just In Time:
Just In Time is one of India&rsquo;s most trusted destinations for global timepieces. Founded in 2006 in Mumbai, the brand operates over 85 boutiques across 18+ cities and serves more than 15 million customers nationwide. As an authorized retailer for over 50 international brands including Rado, Longines, Tissot, Seiko, and Versace, the company ensures authenticity, official warranties, and expert guidance. Its robust service ecosystem and omnichannel presence further enhance customer experience across India.

That is the number of major research articles that bear the name of Venkata Vijay Satyanarayana Murthy Neelam-the data-engineering researcher known professionally as Murthy Neelam. It is a number that, in the context of applied technology research, demands attention. Doctoral candidates in computer science often require four to six years to produce a dissertation and a handful of supporting publications. Established professors at top-tier research universities might publish sixteen papers across a decade. Neelam has produced sixteen in a concentrated burst of intellectual output that spans roughly four years and covers virtually every consequential layer of the modern enterprise data platform-plus the rapidly expanding frontier where artificial intelligence meets data infrastructure.
Mid-day has spent weeks reviewing the complete Neelam bibliography, consulting with technologists who have deployed his frameworks, and mapping the influence networks his publications have generated. The picture that emerges is unlike anything we have encountered in contemporary technology research: a single author, working with extraordinary discipline and range, systematically producing the architectural blueprints for an industry in the midst of its most transformative period.
What follows is the story of those sixteen papers-organized not chronologically, as prior profiles have done, but thematically, in four eras that mirror the evolution of data engineering itself.
ERA I The Platform Foundations Papers 1&ndash;4&nbsp; &bull;&nbsp; Governance, Security, Processing, Activation
Every edifice requires a foundation, and Neelam&rsquo;s first four publications laid one that has proven remarkably durable. These papers addressed the structural problems that had plagued enterprise data teams for years: who owns the data, how do you catch criminals hiding inside it, how do you process it without maintaining two separate pipelines, and how do you push the insights it yields back into the systems where workers actually operate.
[01] Data Mesh Architecture: Decentralized Domain Ownership and Federated Governance as a Solution to Enterprise Data Platform Scalability
[02] Synthetic Identity Fraud Detection Using Graph Database Architecture: A Risk Analysis Framework for Real-Time Financial Crime Prevention
[03] Unified Batch and Streaming with Apache Flink 1.15: Eliminating the Lambda Architecture in Modern Real-Time Data Platforms
[04] Reverse ETL as an Emerging Data Engineering Paradigm: Operationalizing Warehouse Analytics Into CRM and Operational Systems Using Census and Hightouch
The data mesh paper shattered the assumption that centralized data teams were the only viable governance model, replacing it with a federated architecture in which domain teams own, publish, and maintain data products under organization-wide quality contracts. The fraud detection paper demonstrated that graph databases could expose synthetic identity networks invisible to traditional relational analysis-a contribution that financial institutions have since operationalized in their anti-crime stacks. The Flink paper proved that the Lambda Architecture&rsquo;s dual-pipeline compromise was no longer necessary, providing a migration playbook that platform engineers have used to eliminate years of accumulated technical debt. And the Reverse ETL paper formalized the last-mile problem of analytics-arguing, persuasively, that insight trapped inside a dashboard is insight wasted.
Taken together, these four papers established Neelam as a researcher who thinks in systems rather than components. Each publication solved a discrete problem, but the four collectively described how an enterprise data platform should be organized, secured, processed, and activated. It was an opening statement of unusual completeness.
ERA II The Performance Revolution Papers 5&ndash;7&nbsp; &bull;&nbsp; AI Deployment, Data Transfer, Streaming Lakehouses
Having mapped the organizational and architectural skeleton of the modern data platform, Neelam turned his attention to performance-the raw throughput, latency, and computational efficiency that determine whether an architecture works on paper or works under load.
[05] Large Language Model Fine-Tuning in Production: Parameter-Efficient Approaches Using LoRA and Prompt Tuning for Domain-Specific NLP Applications
[06] Apache Arrow Flight and the Zero-Copy Data Transfer Revolution: Eliminating Serialization Overhead in Distributed Data Engineering Pipelines at Petabyte Scale
[07] Streaming Lakehouse Architectures with Apache Kafka, Apache Iceberg, and Flink: Achieving Exactly-Once Semantics and Sub-Second Latency in Unified Batch-Stream Pipelines
The LLM fine-tuning paper arrived precisely when enterprises needed it most-at the moment when generative AI had moved from novelty to necessity and organizations were discovering that full-parameter training was financially ruinous. Neelam&rsquo;s production-oriented evaluation of LoRA and prompt tuning transformed parameter-efficient fine-tuning from a laboratory technique into an engineering discipline, complete with adapter versioning, multi-tenant inference serving, and rollback protocols.
The Arrow Flight paper attacked data engineering&rsquo;s most expensive hidden tax: serialization. By architecting a complete zero-copy data plane built on Apache Arrow&rsquo;s columnar format, Neelam demonstrated throughput improvements exceeding an order of magnitude in analytical workloads-and provided the phased migration roadmap that allowed organizations to adopt incrementally rather than rip-and-replace.
And the streaming lakehouse paper delivered what the industry had been debating for years but no one had fully specified: a reference architecture integrating Kafka, Iceberg, and Flink that achieves exactly-once semantics with sub-second latency, accompanied by a failure-mode catalog and testing methodology that engineering teams have adopted as a production validation standard.
ERA III The Ecosystem Intelligence Papers 8&ndash;9&nbsp; &bull;&nbsp; Metadata Governance, Distributed Python
With the platform built and its performance tuned, two critical questions remained: could organizations actually find, trust, and govern the data flowing through these architectures, and could data practitioners interact with distributed data at scale without abandoning the programming language they know best?
[08] OpenMetadata and DataHub: A Comparative Evaluation of Open-Source Data Catalog Architectures for Automated Lineage, Discovery, and Governance in Modern Data Platforms
[09] Daft and Ibis: The Emerging Python-Native Distributed DataFrame Ecosystem &ndash; Evaluating Lazy Evaluation, Query Pushdown, and Multi-Engine Execution for Cloud-Scale Data Engineering
The data catalog paper elevated platform selection from vendor marketing to architectural science, constructing a five-axis evaluation framework-lineage completeness, discovery relevance, governance integration, extensibility, and operational sustainability-that has since been adopted as a scoring rubric by enterprise architecture teams making multi-million-dollar investment decisions. Neelam&rsquo;s discovery that OpenMetadata and DataHub embody fundamentally different architectural philosophies-schema-first consistency versus event-driven graph flexibility-dissolved the simplistic rankings that had confused the market.
The Daft and Ibis paper produced a conclusion of genuine originality: these two frameworks are complementary rather than competing, with Ibis serving as a universal expression layer and Daft as a high-performance execution engine for multimodal workloads. The reference architecture combining both dissolved a false dichotomy and gave organizations a coherent strategy for Python-native distributed computation-while also analyzing the downstream organizational implications for team structure, hiring, and the traditional scientist-to-engineer handoff.
ERA IV The AI-Infrastructure Convergence Papers 10&ndash;16&nbsp; &bull;&nbsp; The Frontier Where AI Meets Enterprise Systems
And then Neelam did something that even those who had been tracking his work did not fully anticipate. He pivoted-or more accurately, expanded-into the territory where artificial intelligence and enterprise data infrastructure are converging at extraordinary speed. Seven papers, each addressing a different facet of this convergence, each arriving with the same architectural depth and operational pragmatism that characterized his earlier work.
[10] Compound AI Systems and LLM Orchestration Frameworks: Architectural Comparison of LangGraph, LlamaIndex Workflows, and DSPy for Building Stateful, Multi-Agent Production Pipelines
[11] Semantic Layers and AI-Ready Data Architecture: How Cube, AtScale, and dbt Semantic Layer Enable Natural Language Querying, Consistent Metrics, and LLM-Powered Business Intelligence at Enterprise Scale
[12] Model Context Protocol (MCP) in Production: Standardizing AI Agent Tool Integration Across Enterprise Data Sources, APIs, and Legacy Systems &ndash; Security Patterns, Performance Benchmarks, and Adoption Challenges
[13] AI Safety in Deployed Systems: Red-Teaming Techniques, Constitutional AI Evaluation, and Automated Jailbreak Detection for Large Language Models in High-Stakes Enterprise and Government Applications
[14] AI-Native DLP: Replacing Regex-Based Content Inspection With LLM-Driven Semantic Understanding for Enterprise Data Exfiltration Detection
[15] Shift-Left FinOps Using Retrieval-Augmented Generation: Pricing Cloud Architectures at Design Time Before Bills Are Generated
[16] AI-Powered Data Quality Assessment: Detecting Semantic Anomalies and Business Rule Violations That Statistical Methods Cannot Identify
The scope of this final era is staggering. Paper ten provides the first rigorous architectural comparison of LangGraph, LlamaIndex Workflows, and DSPy-the orchestration frameworks that determine how multi-agent AI systems are built in production-evaluating their approaches to state management, tool invocation patterns, and failure recovery in stateful pipelines. It is the kind of evaluation that organizations undertaking multi-agent deployments have desperately needed and, until Neelam produced it, did not have.
Paper eleven turns to the semantic layer-the architectural component that sits between raw data and AI-powered querying. Neelam&rsquo;s comparative evaluation of Cube, AtScale, and dbt Semantic Layer examines how each platform enables natural language querying, maintains metric consistency across consumers, and supports the integration of large language models into enterprise business intelligence workflows. The paper argues that the semantic layer is not merely a convenience but a prerequisite for trustworthy AI-driven analytics, and provides the architectural patterns needed to implement it.
Paper twelve, on the Model Context Protocol, is perhaps the most forward-looking work in the entire portfolio. MCP represents the emerging standard for connecting AI agents to enterprise data sources, APIs, and legacy systems. Neelam&rsquo;s production-focused evaluation documents security patterns for authenticating agents across system boundaries, performance benchmarks for tool invocation under realistic latency constraints, and the adoption challenges-organizational, architectural, and cultural-that enterprises face when standardizing agent-tool integration. It is a roadmap for a capability that most organizations have not yet deployed but soon will.
Paper thirteen addresses what may be the most consequential concern of the AI era: safety. Neelam&rsquo;s treatment of red-teaming techniques, Constitutional AI evaluation, and automated jailbreak detection for large language models in high-stakes enterprise and government applications provides both a taxonomy of attack vectors and a defensive architecture for organizations deploying LLMs where the consequences of failure-financial, legal, reputational, or human-are severe. The paper&rsquo;s focus on deployed rather than experimental systems gives it an operational specificity that policymakers and chief information security officers have found directly actionable.
Paper fourteen extends the AI-safety theme into data loss prevention, arguing that the regex-based content inspection systems that have served as the backbone of enterprise DLP for two decades are fundamentally inadequate against sophisticated exfiltration techniques. Neelam proposes an AI-native architecture in which large language models perform semantic understanding of data content, detecting exfiltration attempts that pattern-matching rules cannot identify-a paradigm shift that reframes DLP as a cognitive rather than syntactic challenge.
Paper fifteen introduces a concept of striking practical value: shift-left FinOps. Just as the DevOps movement shifted testing and security earlier into the development lifecycle, Neelam argues that cloud cost analysis should occur at architecture design time, not after bills arrive. His framework leverages retrieval-augmented generation to price proposed cloud architectures before a single resource is provisioned, enabling technology leaders to make cost-informed design decisions rather than cost-reactive remediation ones. The publication bridges two disciplines-financial operations and AI engineering-that have historically operated in isolation.
And paper sixteen, on AI-powered data quality assessment, completes the portfolio by addressing the most fundamental prerequisite of any data platform: can you trust the data? Neelam demonstrates that statistical methods-null checks, range validations, distribution monitors-miss an entire category of quality failures: semantic anomalies and business rule violations that are technically valid data but contextually wrong. His AI-powered assessment framework uses language models to understand the meaning of data, not merely its shape, detecting the subtle corruptions that propagate through analytical pipelines and undermine decision-making. It is a fitting capstone-a paper that returns to the question of data trustworthiness with a solution that could only exist at the intersection of AI and data engineering.
THE FULL MEASURE
What Sixteen Papers Tell Us About One Researcher-and an Entire Field
Numbers alone do not make a legacy. Sixteen papers could, in lesser hands, represent sixteen disconnected explorations-a scattershot portfolio assembled from whatever topics were trending at the moment. What makes Murthy Neelam&rsquo;s body of work extraordinary is not its volume but its architecture. Like the platforms he describes, his research portfolio is itself a coherent system: each publication addresses a distinct layer, and together they describe the complete anatomy of a modern, AI-augmented enterprise data platform.
Consider the scope:
▸ Organizational design and governance (data mesh, federated ownership)
▸ Security and fraud prevention (graph-based detection, AI safety, AI-native DLP)
▸ Processing paradigms (unified batch-stream, streaming lakehouses, zero-copy transfer)
▸ Operational activation (Reverse ETL, shift-left FinOps)
▸ AI integration (LLM fine-tuning, multi-agent orchestration, semantic layers, MCP)
▸ Metadata and quality (data catalogs, AI-powered quality assessment)
▸ Developer experience (Python-native distributed computation)
No other individual researcher in the current data-engineering landscape has published original architectural work across all of these domains. The breadth is unprecedented. But it is the depth that makes the breadth credible: every paper operates at a level of specificity that specialists in the relevant subfield find authoritative, producing decision frameworks, reference architectures, migration strategies, failure-mode analyses, and evaluation methodologies that practitioners adopt directly.
The influence is equally remarkable. Neelam&rsquo;s publications have informed architecture decisions at major technology companies, shaped fraud-prevention strategies at financial institutions, provided evaluation frameworks for multi-million-dollar platform investments, served as blueprints for streaming lakehouse deployments processing billions of daily events, and entered the reference reading lists of engineering teams building the next generation of AI-integrated data systems.
And the timing matters. Neelam has not followed the field&rsquo;s evolution; he has anticipated it. His data mesh paper arrived before most enterprises had recognized the governance crisis. His LLM fine-tuning paper landed before production AI deployment was mainstream. His MCP paper was published while most organizations were still experimenting with basic chatbot integrations, let alone standardized agent-tool protocols. His AI safety paper preceded the regulatory wave that has since made LLM risk management a board-level concern. In each case, Neelam&rsquo;s research was ahead of the adoption curve-providing the architectural blueprints that organizations reached for when the problems he described became their problems.
FINAL WORD
The Researcher the Industry Cannot Afford to Overlook
There is a temptation, in technology journalism, to reserve the word &ldquo;extraordinary&rdquo; for founders who build billion-dollar companies or engineers who write code that runs on a billion devices. But the infrastructure of knowledge matters as much as the infrastructure of code, and in the domain of data engineering, no one in recent memory has built more of it than Murthy Neelam.
His sixteen publications do not just describe the state of the art. They have, in measurable ways, moved it forward. They have given practitioners the frameworks to reorganize their teams, the architectures to rebuild their platforms, the evaluation methodologies to select their tools, and the safety patterns to deploy AI without recklessness. They have done so with a consistency of quality, a breadth of coverage, and a depth of insight that is, by the standards of applied technology research, genuinely exceptional.
Mid-day does not use the word lightly. In the field of data engineering and AI infrastructure, Murthy Neelam is an exceptional researcher-and these sixteen papers are the evidence..

For many people living in New Zealand, investing in India feels like a natural idea. Sometimes it is driven by familiarity. Sometimes it is about long-term diversification. Sometimes it is simply about wanting access to a market that still looks dynamic from a global perspective. But the moment interest turns into action, the questions change. It is no longer just about opportunity. It becomes about process, paperwork, tax treatment, and whether the investment route is actually manageable from overseas.
That is one reason Indian mutual funds tend to stand out for overseas investors. A mutual fund pools money from multiple investors and puts it into assets such as equities, bonds, government securities, and money market instruments. In practical terms, that gives an investor market exposure without having to choose and monitor individual securities one by one. For someone investing from another country, that structure can feel a lot more workable than building a direct stock portfolio from scratch.
Why Indian Mutual Funds Can Make Sense for Overseas Investors
Cross-border investing usually becomes harder when every decision depends on constant market tracking. That is where mutual funds offer some relief. They give investors a managed route into the market and a clearer framework for diversification. Instead of trying to decide which individual companies to hold, the investor starts by deciding what kind of exposure they want and how much risk they are willing to take.
That distinction matters. Most investors do not actually need endless choice. They need structure. A product that helps with diversification, professional management, and defined categories is often easier to understand and easier to stick with over time. That becomes even more important when the money is moving across borders, and the investor may already be dealing with extra compliance requirements.
The First Step Is Usually Setup, Not Scheme Selection
A common mistake is starting with fund names, recent returns, or online rankings. In reality, the better place to begin is the setup side. For a non-resident investor, documentation is not a side task. It is part of the investment process itself. Official KYC material for individuals includes residential status categories such as non-resident, foreign national, and person of Indian origin, and it asks for identity and address details, including passport or driver's license information and an overseas address.
That means the practical groundwork matters before money is invested. Investors usually need clarity on identity proof, address proof, tax residence, and the documents required to establish their status properly. It is not difficult to see why some people hesitate at this stage. The investment idea may be simple, but the onboarding process still deserves attention. Getting that part right early tends to make everything else smoother later.
Tax Needs Attention Earlier Than Most People Expect
Tax is often treated as something to worry about later. That is rarely a good idea in cross-border investing. For non-resident investors, treaty benefits may be available where applicable, but they are linked to conditions. Official tax guidance for mutual fund investors notes that a non-resident seeking treaty benefits must obtain a tax residency certificate from the home country and provide additional prescribed information where required.
On the New Zealand side, offshore holdings can fall under the foreign investment fund rules. The official guidance describes these as special tax rules for certain offshore investments and explains that New Zealand tax residents may need to use those rules depending on the nature and size of their holdings and whether an exemption applies. In other words, tax treatment is not something to guess at. It is something to understand before the portfolio grows.
Choose the category before you choose the fund.
Once the setup and tax side are understood, the next smart step is category selection. This matters more than most first-time investors expect. Official mutual fund classification material separates schemes across structures and investment objectives, with major groupings that include equity, debt, hybrid, money market, multi-asset, exchange-traded funds, overseas funds, and fund of funds. There is also a widely used categorization that groups schemes into equity, debt, hybrid, solution-oriented, and other categories, such as index funds and fund of funds.
Why does that matter? Because investors often compare products that were never designed to do the same job. A fund built for long-term equity growth is not meant to behave like a debt-oriented option. A balanced or hybrid route is not meant to feel the same as a concentrated equity route. When investors skip the category question, they often end up chasing performance without understanding purpose. That usually leads to confusion later.
Common Mistakes Usually Look Small at First
Most mistakes in cross-border investing are not dramatic. They are ordinary things done without enough thought. Investors rush into a scheme without sorting out the documentation. They assume the tax can be cleaned up later. They choose multiple funds that effectively overlap. Or they focus so much on short-term returns that they lose sight of the role each holding is supposed to play. Those issues are easy to underestimate at the beginning because each one looks minor on its own. Together, though, they can make the portfolio harder to manage than it needs to be.
A better approach is usually simpler than expected. Start with compliance. Understand tax residence and reporting obligations. Decide what role India should play in the wider portfolio. Choose categories before schemes. Then invest in a way that is realistic enough to continue. That kind of structure may not feel exciting, but it is usually what makes an investment approach sustainable from overseas.
End note
For New Zealand-based investors, Indian mutual funds can be a practical route into India&rsquo;s markets because they combine diversification, professional management, and category-based choice in a format that is easier to manage than direct stock picking. The strongest approach is usually to get the order right: understand the setup, get clarity on tax treatment, choose the right fund category, and only then decide how to invest.
For those who want a digital route built specifically for this New Zealand-to-India investing use case, Indus is one example. It positions itself around onboarding with New Zealand identification, direct funding from New Zealand, access to 500-plus Indian mutual funds, and a fully digital investment flow designed for investors in this corridor.
Disclaimer: The information provided on the Website does not constitute investment advice, financial advice, trading advice, or any other form of advice, and you should not interpret any of the financial content as such. Please conduct your own due diligence and consult with a financial advisor before making any investment decisions. Midday does not endorse or promote any such activities, and you access them at your own risk, fully understanding the monetary and legal consequences involved. Midday shall not be held responsible for any losses you may incur as a result of using any such apps or websites. 

NIF Global (New York Institute of Fashion) curated an inspiring and unfiltered conversation featuring its esteemed&nbsp;mentor Gauri Khan and style icon Ananya Panday, offering students a rare glimpse into the realities of building a career in the creative industries.
Moderated by Tisha Khosla, Author and Creative Educator, NIF Global Corporate&nbsp;- the session stood out for its candid tone and engaging format, moving beyond surface-level discussions to explore creativity, personal evolution, and the mindset required to succeed in competitive fields.
The conversation opened with a light yet relatable exchange on personal style.&nbsp;Gauri Khan&nbsp;spoke about her preference for comfort-driven fashion while working, emphasizing how simplicity allows her to stay focused.&nbsp;Ananya Panday, on the other hand, reflected the ever-evolving nature of her style, admitting that she enjoys experimenting but often moves on quickly - a trait that resonates strongly with today&rsquo;s generation.
As the discussion progressed, it shifted into deeper insights on creativity and process. Sharing her recent work,&nbsp;Gauri Khan&nbsp;highlighted the importance of understanding scale, spatial design, and detail when creating impactful environments. She emphasized that good design begins with observation - a skill she encouraged students to cultivate consistently.
Ananya Panday&nbsp;brought in a refreshing perspective from the entertainment industry, openly acknowledging the uncertainty that comes with creative careers. She described the current landscape as &ldquo;a confusing time,&rdquo; where trends shift rapidly, making it important to focus on growth rather than outcomes. Stressing the value of experience, she encouraged students to embrace experimentation and step outside their comfort zones.
&ldquo;I think the best thing to do is to put yourself out there,&rdquo; Ananya shared,&nbsp;reinforcing the idea that learning comes from action, not hesitation.
One of the most engaging moments of the session was the discussion around&nbsp;Gauri Khan&rsquo;s collaboration with Ananya Panday on designing her home.&nbsp;Offering a behind-the-scenes look into the design process, Gauri Khan explained that her approach begins with understanding the client&rsquo;s personality and preferences rather than imposing a predefined vision.
Ananya Panday&nbsp;shared how the experience was both intuitive and personal. With a preference for natural light and neutral tones, she appreciated how&nbsp;Gauri Khan&nbsp;introduced subtle elements - from textures to unexpected colours - that enhanced the overall aesthetic. The exchange highlighted how meaningful collaboration can transform a space into a true reflection of its owner.
The discussion also explored creative influences and global inspiration.&nbsp;Gauri Khan spoke about cities like Milan as hubs of design innovation, where exposure to architecture, art, and global talent fuels new ideas. Ananya Panday, meanwhile, reflected on her current interest in minimal aesthetics and storytelling across cinema and pop culture, underlining how inspiration today often comes from multiple disciplines.
Held in Mumbai during Lakm&eacute; Fashion Week x FDCI, the session gained added significance as students experienced a powerful intersection of education and industry. The setting reinforced NIF Global&rsquo;s focus on immersive learning, where students engage directly with influential voices and real-world environments.
A key takeaway from the conversation was the importance of mentorship. By connecting students with established professionals, NIF Global enables learning that goes beyond classrooms, offering insights shaped by real experiences and evolving industry dynamics.
Both speakers shared valuable advice for aspiring designers and creatives.&nbsp;Gauri Khan&nbsp;emphasized the importance of focus, discipline, and taking calculated risks, encouraging students to start small and build steadily toward their goals.&nbsp;Ananya Panday&nbsp;echoed this sentiment while adding a contemporary perspective - urging students to stay authentic and not be overly influenced by external opinions.
She also highlighted the importance of embracing mistakes as part of the journey, noting that growth comes from learning on the job and continuously evolving.
The conversation briefly touched upon the importance of slowing down in a digitally driven world. Both&nbsp;Gauri Khan and Ananya Panday&nbsp;spoke about their personal ways of disconnecting - from spending time in nature to reading - reinforcing the idea that creativity thrives when the mind is given space to pause and reflect.
Through such meaningful engagements, NIF Global continues to strengthen its position as a leading institution in design, management, and beauty education. With a strong emphasis on experiential learning, the institute equips students with industry-ready skills while nurturing their individuality and creative confidence.
Its mentorship network includes leading industry names such as&nbsp;Manish Malhotra, Twinkle Khanna, Ashley Rebello, and Bharat &amp; Dorris, providing students with valuable exposure to diverse creative domains.
Aligned with the vision of&nbsp;National Education Policy 2020, NIF Global offers&nbsp;UGC-approved programs, including B.Des, M.Des, B.Voc, M.Voc, and BBA,&nbsp;in collaboration with&nbsp;Medhavi Skills University and National Skill Development Corporation.
By fostering open dialogue, real-world exposure, and mentorship-led learning, NIF Global continues to shape a new generation of creative professionals - confident, adaptable, and ready to make their mark on the global stage.
For more details, visit&nbsp;www.nifglobal.college.

Stay updated with the latest BuzzFeed! Explore trending stories on finance, crypto, technology, lifestyle, and more. Get insights from industry leaders and discover inspiring stories. 

Buzzfeed News Stories

Rising Global Liver Disease Crisis: Low-Cost Solutions Gain Attention at European Congress of Internal Medicine 2026

Rising Global Liver Disease Crisis: Low-Cost Solutions Gain Attention at European Congress of Internal Medicine 2026

Briston Strengthens Global Expansion with India Launch in Partnership with Just In Time

Sixteen and Counting: How Murthy Neelam Built the Most Comprehensive Research Portfolio in Modern Data Engineering

Investing in Indian Mutual Funds From New Zealand: What to Know Before You Begin

NIF Global Curates a Powerful Unfiltered Conversation with Gauri Khan and Ananya Panday

Home / Buzzfeed

Buzzfeed News Stories

Rising Global Liver Disease Crisis: Low-Cost Solutions Gain Attention at European Congress of Internal Medicine 2026

Rising Global Liver Disease Crisis: Low-Cost Solutions Gain Attention at European Congress of Internal Medicine 2026

Briston Strengthens Global Expansion with India Launch in Partnership with Just In Time

Sixteen and Counting: How Murthy Neelam Built the Most Comprehensive Research Portfolio in Modern Data Engineering

Investing in Indian Mutual Funds From New Zealand: What to Know Before You Begin

NIF Global Curates a Powerful Unfiltered Conversation with Gauri Khan and Ananya Panday