// team-data.jsx — Real Digital AI Finance content
// Bilingual (de/en) data module. Loaded as a Babel script — no ES imports;
// everything is attached to window for cross-script access.

const HERO = {
  label: { de: "Digital AI Finance · FHGR", en: "Digital AI Finance · FHGR" },
  title: { de: "Digital AI Finance · FHGR", en: "Digital AI Finance · FHGR" },
  subtitle: {
    de: "Forschende und Dozierende an der Schnittstelle von künstlicher Intelligenz, quantitativer Finanzwirtschaft und digitaler Innovation — gefördert durch Innosuisse, SNF und die Europäische Kommission.",
    en: "Researchers and lecturers at the intersection of artificial intelligence, quantitative finance, and digital innovation — funded by Innosuisse, SNF, and the European Commission.",
  },
};

const TEAM = [
  {
    id: "joerg",
    photo: "photos/joerg.jpg",
    name: "Prof. Dr. Jörg Osterrieder",
    initials: "JO",
    title: {
      de: "Professor · FHGR",
      en: "Professor · FHGR",
    },
    institution: {
      de: "Schweizerisches Institut für Informationswissenschaft",
      en: "Swiss Institute for Information Science",
    },
    focus: {
      de: "KI, ML & quantitative Finanzwirtschaft",
      en: "AI, ML & quantitative finance",
    },
    bio: {
      de: "Jörg Osterrieder beschäftigt sich seit vielen Jahren in Forschung und Lehre mit Themen an der Schnittstelle von Künstlicher Intelligenz, Digital Finance, Fintech, Computational and Data Science, Digital Innovation und IT. Sein Forschungsinteresse gilt dem Einsatz datengetriebener Methoden und maschinellen Lernens, um komplexe Systeme zu verstehen, Entscheidungsprozesse zu verbessern und innovative Lösungen in Wirtschaft, Technologie und Gesellschaft zu entwickeln. Er hat einen PhD in Mathematik (ETH Zürich), einen MSc in Mathematik (Syracuse University, USA) sowie einen Master in Wirtschaftsmathematik (Universität Ulm). Seine berufliche Laufbahn begann im Investment Banking und Asset Management, wo er in quantitativen Funktionen bei Man Investments, Credit Suisse, Goldman Sachs und Bank of America Merrill Lynch tätig war.  Seine Lehrtätigkeit umfasst neben klassischen Vorlesungen auch Praxisprojekte in Kooperation mit Unternehmen und internationalen Organisationen, wodurch Studierende frühzeitig Einblicke in reale Anwendungsfelder erhalten. Darüber hinaus betreut er Bachelor-, Master- und Doktorarbeiten und engagiert sich in der Entwicklung neuer Curricula zu Themen wie KI in Finanzmärkten, digitaler Transformation und Digitalisierung.",
      en: "Jörg Osterrieder has been engaged for many years in research and teaching on topics at the intersection of Artificial Intelligence, Digital Finance, Fintech, Computational and Data Science, Digital Innovation, and IT. His research interests focus on the use of data-driven methods and machine learning to understand complex systems, improve decision-making processes, and develop innovative solutions in business, technology, and society. He holds a PhD in Mathematics (ETH Zurich), an MSc in Mathematics (Syracuse University, USA), and a Master's in Business Mathematics (University of Ulm). His professional career began in investment banking and asset management, where he held quantitative roles at Man Investments, Credit Suisse, Goldman Sachs, and Bank of America Merrill Lynch. His teaching activities include not only traditional lectures but also practical projects in cooperation with companies and international organisations, giving students early insights into real-world applications. In addition, he supervises Bachelor's, Master's, and doctoral theses and is actively involved in developing new curricula on topics such as AI in financial markets, digital transformation, and digitalisation.",
    },
    tags: [
      { de: "AI / ML", en: "AI / ML" },
      { de: "Quantitative Finance", en: "Quantitative Finance" },
      { de: "NLP", en: "NLP" },
      { de: "Digital Finance", en: "Digital Finance" },
      { de: "Sustainable Finance", en: "Sustainable Finance" },
    ],
    links: [
      { label: "FHGR", url: "https://www.fhgr.ch/personen/person/osterrieder/", primary: true },
      { label: "Website", url: "https://www.joergosterrieder.com/", primary: false },
      { label: "LinkedIn", url: "https://www.linkedin.com/in/joergosterrieder/", primary: false },
    ],
  },
  {
    id: "lennart",
    photo: "photos/lennart.jpg",
    name: "Lennart John Baals",
    initials: "LB",
    title: { de: "Doktorand · FHGR", en: "Doctoral Researcher · FHGR" },
    institution: {
      de: "FHGR",
      en: "FHGR",
    },
    focus: {
      de: "Krypto, DeFi & Risikomanagement",
      en: "Crypto, DeFi & risk management",
    },
    bio: {
      de: "Lennart John Baals ist Ph.D.-Kandidat im Bereich Quantitative Finance und Risikomanagement an der Universität Twente und wurde durch das Projekt des Schweizerischen Nationalfonds „Network-Based Credit Risk Models in P2P Lending Markets“ gefördert. Seine Forschung konzentriert sich auf die Messung und Preisbildung von Risiken in der digitalen Finanzwelt und umfasst sowohl spekulative Dynamiken in digitalen Vermögensmärkten als auch netzwerkbasierte Kreditrisikomodellierung und Machine-Learning-Methoden für Peer-to-Peer-Kredite. Er hat in Expert Systems With Applications und Finance Research Letters (2024) sowie Financial Innovation (2026) publiziert. Im Jahr 2025 war er als Visiting Ph.D. Researcher am Department of Industrial Engineering and Operations Research der Columbia University tätig und absolvierte ein Forschungspraktikum bei Ask2.Ai in New York. Er ist Gutachter für Expert Systems With Applications, Finance Research Letters, Financial Innovation, Global Finance Journal, das International Journal of Forecasting sowie das Journal of Economics and Business und hatte Lehrunterstützungsrollen am Trinity College Dublin und an der Columbia University.",
      en: "Lennart John Baals is a Ph.D. candidate in Quantitative Finance and Risk Management at the University of Twente, supported by the Swiss National Science Foundation project Network-Based Credit Risk Models in P2P Lending Markets. His research focuses on measuring and pricing risks in digital finance, encompassing speculative dynamics in digital asset markets, network-based credit risk modelling, and machine learning methods for peer-to-peer lending. He has published in Expert Systems With Applications and Finance Research Letters (2024) as well as Financial Innovation (2026). In 2025, he was a Visiting Ph.D. Researcher at the Department of Industrial Engineering and Operations Research at Columbia University and completed a research internship at Ask2.Ai in New York. He serves as a reviewer for Expert Systems With Applications, Finance Research Letters, Financial Innovation, Global Finance Journal, the International Journal of Forecasting, and the Journal of Economics and Business, and has held teaching support roles at Trinity College Dublin and Columbia University.",
    },
    tags: [
      { de: "Blockchain", en: "Blockchain" },
      { de: "DeFi / NFTs", en: "DeFi / NFTs" },
      { de: "Risikomanagement", en: "Risk Management" },
      { de: "Econometrics", en: "Econometrics" },
    ],
    links: [
      { label: "FHGR", url: "https://www.fhgr.ch/personen/person/baals/", primary: true },
      { label: "LinkedIn", url: "https://www.linkedin.com/in/lennart-john-baals-a621aa193/", primary: false },
    ],
  },
  {
    id: "illia",
    photo: "photos/illia.jpg",
    name: "Illia Kosterin",
    initials: "IK",
    title: { de: "Forschungsassistent · FHGR", en: "Research Assistant · FHGR" },
    institution: { de: "Digital AI Finance", en: "Digital AI Finance" },
    focus: {
      de: "Lehrentwicklung & KI-Infrastruktur",
      en: "Teaching development & AI infrastructure",
    },
    bio: {
      de: "Illia Kosterin ist Forschungsassistent im Bereich Digital AI Finance an der FHGR. Er verfügt über einen Master-Abschluss in Informatik mit Spezialisierung auf Künstliche Intelligenz der Charkiwer Nationalen Universität für Radioelektronik. Sein beruflicher Werdegang umfasst Business-Analyse, Marketing-Analytics (SQL, Power BI), Systemadministration sowie Front-End-Entwicklung in ukrainischen Technologieunternehmen. An der FHGR wirkt er in der Forschungsgruppe von Prof. Osterrieder mit und unterstützt die Projekte «Implied Risk Premia» und «Compliance Copilot». Er bringt eine praxisorientierte, funktionsübergreifende Perspektive ein – als Bindeglied zwischen Dokumentation, Anforderungsmanagement und technischer Umsetzung – in die angewandte KI-Finanzforschung.",
      en: "Illia Kosterin is a research assistant in Digital AI Finance at FHGR. Business analyst and computer scientist, holding a Master's in Computer Science with an AI specialisation from Kharkiv  National University of Radio Electronics. Professional background spans business analysis, marketing analytics (SQL, Power BI), system administration, and front-end development across Ukrainian tech companies. At FHGR contributes to Prof. Osterrieder's research group, supporting the Implied Risk Premia and Compliance Copilot projects. Brings a practical cross-functional perspective — bridging documentation, requirements engineering, and technical implementation — to applied AI finance research.",
    },
    tags: [
      { de: "AI / ML", en: "AI / ML" },
      { de: "Digital Finance", en: "Digital Finance" },
      { de: "Lehrentwicklung", en: "Teaching Development" },
    ],
    links: [
      { label: "LinkedIn", url: "https://www.linkedin.com/in/illia-kosterin/", primary: false },
    ],
  },
];

const PROJECTS = [
  {
    id: "compliance-copilot",
    name: { de: "Compliance Copilot", en: "Compliance Copilot" },
    logo: "logos/compliance-copilot.svg",
    poster: "Compliance_Copilot_poster.png",
    status: { de: "Aktiv", en: "Active" },
    funder: { de: "Innosuisse Innovationsprojekt", en: "Innosuisse Innovation Project" },
    description: {
      de: "Spezialisierter, sicherer KI-Orchestrator für die Dokumentenverarbeitung in regulierten Umgebungen. Mehrere KI-Agenten bearbeiten autonom komplexe dokumentenbasierte Aufgaben im Compliance- und Finanzbereich.",
      en: "A specialised, secure AI orchestrator for document processing in regulated environments. Multiple AI agents autonomously handle complex document-based tasks in compliance and finance.",
    },
    details: {
      de: "Compliance Copilot ist ein von Innosuisse gefördertes Innovationsprojekt zur Entwicklung eines sicheren, mehragentenbasierten KI-Orchestrators für die Dokumentenverarbeitung in regulierten Umgebungen. Das System koordiniert mehrere spezialisierte KI-Agenten — Extraktoren, Validatoren, Zusammenfasser und Prüfer —, die komplexe Dokumentenabläufe wie KYC-Prüfungen, regulatorische Meldungen, Due-Diligence-Berichte und Vertragsanalysen bearbeiten. Der Industriepartner Wecan Group liefert produktionsreife Compliance-Infrastruktur, die von Schweizer Banken genutzt wird, sodass die Implementierung an realen betrieblichen Anforderungen ausgerichtet ist. Das Projekt untersucht, wie Mehragenten-Architekturen den manuellen Prüfaufwand reduzieren können, während Auditierbarkeit und menschliche Aufsicht erhalten bleiben.",
      en: "Compliance Copilot is an Innosuisse-funded innovation project building a secure, multi-agent AI orchestrator for document processing in regulated environments. The system coordinates several specialised AI agents — extractors, validators, summarisers, and reviewers — that handle complex document workflows such as KYC reviews, regulatory filings, due diligence reports, and contract analysis. Industry partner Wecan Group provides production-grade compliance infrastructure used by Swiss banks, ensuring deployment is grounded in real operational requirements. The project explores how multi-agent architectures can reduce manual review effort while preserving auditability and human-in-the-loop oversight.",
    },
    link: "https://digital-ai-finance.github.io/AI-Orchestrator/",
  },
  {
    id: "implied-risk-premia",
    name: { de: "Implied Risk Premia", en: "Implied Risk Premia" },
    logo: "logos/implied-risk-premia.svg",
    poster: "ImpliedRiskPremia_poster.png",
    status: { de: "Aktiv", en: "Active" },
    funder: { de: "SNF — Narrative Digital Finance", en: "SNF — Narrative Digital Finance" },
    description: {
      de: "Modellierung impliziter Risikoprämien über mehrere Anlageklassen mit GARCH, EWMA-Kovarianzschätzung und Hauptkomponentenanalyse — welche Faktoren treiben Renditen, und wie werden Investoren entschädigt?",
      en: "Modelling implied risk premia across asset classes using GARCH, EWMA covariance estimation, and PCA — which factors drive returns, and how are investors compensated?",
    },
    details: {
      de: "Implied Risk Premia modelliert faktorgetriebene Renditen über mehrere Anlageklassen hinweg — Aktien, festverzinsliche Wertpapiere, Devisen, Rohstoffe und Kryptowährungen — durch die Kombination von GARCH-basierter Volatilitätsschätzung, exponentiell gewichteter Kovarianzdynamik und Hauptkomponentenanalyse zur Extraktion latenter Risikofaktoren. Das Projekt adressiert zwei zentrale Fragen: Welche Faktoren entschädigen Investoren tatsächlich für das Tragen von Risiken, und wie verändern sich diese Entschädigungen über verschiedene Marktphasen hinweg? Gefördert vom Schweizerischen Nationalfonds im Rahmen des Programms „Narrative Digital Finance“ verbindet die Arbeit narrative Signale aus Textdaten mit klassischen quantitativen Faktoren. Ergebnisse umfassen zeitvariable Risikoprämien-Schätzungen, Regime-Erkennungsdiagnostik und ein Open-Source-Toolkit, das die publizierte Forschung begleitet.",
      en: "Implied Risk Premia models factor-driven returns across asset classes — equities, fixed income, foreign exchange, commodities, and crypto — by combining GARCH-family volatility estimation, exponentially-weighted moving-average covariance dynamics, and principal component analysis to extract latent risk factors. The project addresses two core questions: which factors actually compensate investors for bearing risk, and how do those compensations evolve through market regimes? Funded by the Swiss National Science Foundation under the Narrative Digital Finance programme, the work integrates narrative signals from text data with traditional quantitative factors. Outputs include time-varying premia estimates, regime-detection diagnostics, and an open-source toolkit accompanying the published research.",
    },
    link: "https://digital-ai-finance.github.io/Implied_Risk_premia/",
  },
  {
    id: "ai-digital-finance",
    name: { de: "AI for Digital Finance — Swiss-MENA", en: "AI for Digital Finance — Swiss-MENA" },
    logo: "logos/ai-digital-finance.svg",
    poster: "AIforDigitalFinance_poster.png",
    status: { de: "Aktiv", en: "Active" },
    funder: { de: "FHGR × American University of Sharjah", en: "FHGR × American University of Sharjah" },
    description: {
      de: "Internationales Forschungsnetzwerk zu KI im digitalen Finanzwesen mit Schweiz/MENA-Fokus. Februar 2027 an der American University of Sharjah, 80–100 Teilnehmende.",
      en: "International research network on AI in digital finance with Swiss/MENA focus. February 2027 at the American University of Sharjah, 80–100 participants.",
    },
    details: {
      de: "Das Swiss-MENA AI for Digital Finance Network ist eine internationale Forschungskollaboration zwischen der FHGR und der American University of Sharjah und konzentriert sich darauf, Forschungsgemeinschaften zusammenzuführen, die zu Künstlicher Intelligenz auf Finanzmärkten arbeiten. Das zentrale Ereignis ist eine Konferenz im Februar 2027 an der American University of Sharjah in Sharjah, die voraussichtlich 80–100 Teilnehmende aus Wissenschaft, Industrie und Politik versammelt. Konferenzthemen umfassen KI-Ethik im Finanzwesen, digitale Vermögensmärkte, grenzüberschreitende Regulierung und maschinelles Lernen für Emerging Markets. Über die Veranstaltung hinaus zielen die Ergebnisse auf gemeinsame Forschungsarbeiten, ein PhD-Austauschprogramm zwischen Schweizer und MENA-Institutionen sowie eine Reihe von Folgeworkshops zur Aufrechterhaltung des Netzwerks ab.",
      en: "The Swiss-MENA AI for Digital Finance Network is an international research collaboration between FHGR and the American University of Sharjah, focused on bridging research communities working on artificial intelligence in financial markets. The flagship event is a February 2027 conference at the American University of Sharjah, expected to host 80–100 participants drawn from academia, industry, and policy. Conference themes include AI ethics in financial services, digital asset markets, cross-border regulation, and machine learning for emerging markets. Beyond the event, outcomes target joint research papers, a PhD exchange programme between Swiss and MENA institutions, and a series of follow-on workshops to sustain the network.",
    },
    link: "https://digital-ai-finance.github.io/digital-ai-in-finance/",
  },
];

const TEACHING = [
  { id: "digital-finance", title: { de: "Digital Finance", en: "Digital Finance" },
    meta: { de: "BSc + PhD · 80 Lektionen · 3 Editionen", en: "BSc + PhD · 80 lessons · 3 editions" },
    url: "https://digital-ai-finance.github.io/digital-finance/" },
  { id: "data-science", title: { de: "Data Science mit Python", en: "Data Science with Python" },
    meta: { de: "BSc · 48 Lektionen · 18+ Notebooks", en: "BSc · 48 lessons · 18+ notebooks" },
    url: "https://digital-ai-finance.github.io/data-science/" },
  { id: "crypto", title: { de: "Cryptoeconomics & Blockchain", en: "Cryptoeconomics & Blockchain" },
    meta: { de: "BSc · 52 Lektionen · 12 Wochen", en: "BSc · 52 lessons · 12 weeks" },
    url: "https://digital-ai-finance.github.io/Cryptoeconomics-Blockchain/" },
  { id: "methods", title: { de: "Methods & Algorithms", en: "Methods & Algorithms" },
    meta: { de: "MSc · 6 Vorlesungen · 265 Fragen", en: "MSc · 6 lectures · 265 questions" },
    url: "https://digital-ai-finance.github.io/methods-algorithms/" },
];

const PARTNERS = [
  {
    id: "wecan",
    name: "Wecan Group",
    logo: "logos/wecan.svg",
    description: {
      de: "Schweizer Technologieunternehmen für sichere Multi-Bank-Compliance-Plattformen — Industriepartner im Compliance-Copilot-Projekt.",
      en: "Swiss technology company building secure multi-bank compliance platforms — industry partner on the Compliance Copilot project.",
    },
    url: "https://wecangroup.ch/",
  },
  {
    id: "bantleon",
    name: "Bantleon",
    logo: "logos/bantleon.svg",
    description: {
      de: "Unabhängiger Asset Manager mit Sitz in Deutschland und der Schweiz — Industriepartner in den Forschungsprojekten der Gruppe.",
      en: "Independent asset manager based in Germany and Switzerland — industry partner across the group's research projects.",
    },
    url: "https://www.bantleon.com/",
  },
];

const ACKNOWLEDGEMENTS = [
  {
    id: "ack-ai-1",
    project: { de: "AI for Digital Finance", en: "AI for Digital Finance" },
    title: { de: "SNF Leading House MENA — LinkedIn", en: "SNF Leading House MENA — LinkedIn" },
    source: "LinkedIn",
    url: "https://www.linkedin.com/posts/joergosterrieder_snf-leading-house-mena-activity-7433062102514446337-NTqq?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC2KWFIBEtXz3kICcnziG0giZbvr17irtGI",
  },
  {
    id: "ack-ai-2",
    project: { de: "AI for Digital Finance", en: "AI for Digital Finance" },
    title: { de: "AI for Digital Finance Workshop 2026 — LinkedIn", en: "AI for Digital Finance Workshop 2026 — LinkedIn" },
    source: "LinkedIn",
    url: "https://www.linkedin.com/posts/joergosterrieder_ai-for-digital-finance-workshop-2026-activity-7431697487888904193-bUh3?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC2KWFIBEtXz3kICcnziG0giZbvr17irtGI",
  },
  {
    id: "ack-cc-1",
    project: { de: "Compliance Copilot", en: "Compliance Copilot" },
    title: { de: "Wecan Group — Building Compliance AI — LinkedIn", en: "Wecan Group — Building Compliance AI — LinkedIn" },
    source: "LinkedIn",
    url: "https://www.linkedin.com/posts/wecangroup_at-wecan-group-we-believe-that-building-activity-7453425490658455552-zNac?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC2KWFIBEtXz3kICcnziG0giZbvr17irtGI",
  },
  {
    id: "ack-cc-2",
    project: { de: "Compliance Copilot", en: "Compliance Copilot" },
    title: { de: "Wecan Group — Dedicated Copilot — LinkedIn", en: "Wecan Group — Dedicated Copilot — LinkedIn" },
    source: "LinkedIn",
    url: "https://www.linkedin.com/posts/wecangroup_we-are-building-a-dedicated-copilot-to-radically-activity-7425546928660127744-XzDy?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC2KWFIBEtXz3kICcnziG0giZbvr17irtGI",
  },
  {
    id: "ack-cc-3",
    project: { de: "Compliance Copilot", en: "Compliance Copilot" },
    title: { de: "FHGR News — Compliance Copilot", en: "FHGR News — Compliance Copilot" },
    source: "FHGR",
    url: "https://my.fhgr.ch/index.php?id=home&tx_fhgrnews_news%5BidNews%5D=6555&tx_fhgrnews_news%5Baction%5D=show&tx_fhgrnews_news%5Bcontroller%5D=News&cHash=4bb9b1f4a154bbe4cd4a33f6c1e9d1c3",
  },
  {
    id: "ack-cc-4",
    project: { de: "Compliance Copilot", en: "Compliance Copilot" },
    title: { de: "A Specialized Secure AI Orchestrator — ARAMIS", en: "A Specialized Secure AI Orchestrator — ARAMIS" },
    source: "ARAMIS",
    url: "https://www.aramis.admin.ch/Grunddaten/?ProjectID=60005",
  },
  {
    id: "ack-irp-1",
    project: { de: "Implied Risk Premia", en: "Implied Risk Premia" },
    title: { de: "AI-Enhanced Implied Risk Premia Calculation — ARAMIS", en: "AI-Enhanced Implied Risk Premia Calculation — ARAMIS" },
    source: "ARAMIS",
    url: "https://www.aramis.admin.ch/Grunddaten/?ProjectID=58517",
  },
  {
    id: "ack-other-1",
    project: { de: "Andere Projekte", en: "Other Projects" },
    title: { de: "ESG Scoring Engine — Green Finance — ARAMIS", en: "ESG Scoring Engine — Green Finance — ARAMIS" },
    source: "ARAMIS",
    url: "https://www.aramis.admin.ch/Grunddaten/?ProjectID=51451",
  },
  {
    id: "ack-snf-1",
    project: { de: "Swiss National Science Foundation (SNF)", en: "Swiss National Science Foundation (SNF)" },
    title: { de: "Narrative Digital Finance — SNF Grant 213370", en: "Narrative Digital Finance — SNF Grant 213370" },
    source: "SNF",
    url: "https://data.snf.ch/grants/grant/213370",
  },
  {
    id: "ack-snf-2",
    project: { de: "Swiss National Science Foundation (SNF)", en: "Swiss National Science Foundation (SNF)" },
    title: { de: "Anomaly & Fraud Detection in Blockchain — SNF Grant 211195", en: "Anomaly & Fraud Detection in Blockchain — SNF Grant 211195" },
    source: "SNF",
    url: "https://data.snf.ch/grants/grant/211195",
  },
  {
    id: "ack-snf-3",
    project: { de: "Swiss National Science Foundation (SNF)", en: "Swiss National Science Foundation (SNF)" },
    title: { de: "Network-Based Credit Risk in P2P Lending — SNF Grant 205487", en: "Network-Based Credit Risk in P2P Lending — SNF Grant 205487" },
    source: "SNF",
    url: "https://data.snf.ch/grants/grant/205487",
  },
  {
    id: "ack-snf-4",
    project: { de: "Swiss National Science Foundation (SNF)", en: "Swiss National Science Foundation (SNF)" },
    title: { de: "SPARK — Hybrid Sustainable Investment — SNF Grant 190703", en: "SPARK — Hybrid Sustainable Investment — SNF Grant 190703" },
    source: "SNF",
    url: "https://data.snf.ch/grants/grant/190703",
  },
  {
    id: "ack-snf-5",
    project: { de: "Swiss National Science Foundation (SNF)", en: "Swiss National Science Foundation (SNF)" },
    title: { de: "Mathematics and FinTech — Digital Transformation — SNF Grant 174853", en: "Mathematics and FinTech — Digital Transformation — SNF Grant 174853" },
    source: "SNF",
    url: "https://data.snf.ch/grants/grant/174853",
  },
  {
    id: "ack-snf-6",
    project: { de: "Swiss National Science Foundation (SNF)", en: "Swiss National Science Foundation (SNF)" },
    title: { de: "SNF Leading House Asia — Digital AI Finance", en: "SNF Leading House Asia — Digital AI Finance" },
    source: "SNF",
    url: "https://digital-ai-finance.github.io/SNFS-Leading-House-Asia/",
  },
  {
    id: "ack-snf-profile",
    project: { de: "Swiss National Science Foundation (SNF)", en: "Swiss National Science Foundation (SNF)" },
    title: { de: "Prof. Osterrieder — SNF Researcher Profile", en: "Prof. Osterrieder — SNF Researcher Profile" },
    source: "SNF",
    url: "https://data.snf.ch/grants/person/701038",
  },
  {
    id: "ack-ubb-1",
    project: { de: "Babes-Bolyai University (UBB)", en: "Babes-Bolyai University (UBB)" },
    title: { de: "International Advanced Fellowship-UBB", en: "International Advanced Fellowship-UBB" },
    source: "UBB",
    url: "https://www.ubbcluj.ro/",
  },
];

const RESEARCH_CONTEXT = [
  { id: "snf", title: "SNF Narrative Digital Finance",
    description: { de: "SNF-Projekt: Marktnarrative, Strukturbrüche und Blasen in digitalen Finanzmärkten.",
                   en: "SNF project: market narratives, structural breaks, and bubbles in digital financial markets." },
    link: "https://www.snf.ch" },
  { id: "innosuisse", title: "Innosuisse",
    description: { de: "Mehrere Innosuisse-Innovationsprojekte zur praktischen Implementierung von KI in Schweizer Unternehmen.",
                   en: "Multiple Innosuisse innovation projects on practical AI implementation in Swiss companies." },
    link: "https://www.innosuisse.admin.ch" },
  { id: "fhgr", title: "FHGR Applied Future Technologies",
    description: { de: "Forschungsabteilung der FHGR mit Fokus auf Big Data, KI und digitale Innovation.",
                   en: "FHGR research department focused on Big Data, AI, and digital innovation." },
    link: "https://www.fhgr.ch/fhgr/applied-future-technologies/" },
];

const COPY = {
  en: {
    eyebrow: "Digital AI Finance · FHGR",
    section_team: "Team", section_projects: "Projects",
    section_partners: "Partners",
    section_teaching: "Teaching", section_context: "Funding Institutions",
    section_acknowledgements: "Acknowledgements",
    role: "Role", focus: "Focus", expertise: "Expertise",
    institution: "Institution", links: "Links", bio: "Bio",
    name: "Name", index: "Index", status: "Status", funder: "Funder",
    visit: "Visit ↗", read: "Read more ↗",
    hover_hint: "Hover a row →",
  },
  de: {
    eyebrow: "Digital AI Finance · FHGR",
    section_team: "Team", section_projects: "Projekte",
    section_partners: "Partner",
    section_teaching: "Lehre", section_context: "Förderinstitutionen",
    section_acknowledgements: "Danksagungen",
    role: "Rolle", focus: "Schwerpunkt", expertise: "Expertise",
    institution: "Institution", links: "Links", bio: "Biografie",
    name: "Name", index: "Index", status: "Status", funder: "Förderung",
    visit: "Besuchen ↗", read: "Mehr lesen ↗",
    hover_hint: "Zeile hovern →",
  },
};

function useReveal(deps = []) {
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      });
    }, { threshold: 0.08, rootMargin: '0px 0px -6% 0px' });
    els.forEach((el) => io.observe(el));
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}

Object.assign(window, { HERO, TEAM, PROJECTS, PARTNERS, TEACHING, RESEARCH_CONTEXT, ACKNOWLEDGEMENTS, COPY, useReveal });