Divya Mishra | Crisis Management | Young Scientist Award

Published on by Cognitive Scientist Awards

Dr. Divya Mishra | Crisis Management | Young Scientist Award

Delhi Technological University | India

Dr. Divya Mishra is an accomplished academician and researcher in the field of Human Resource Management and Organizational Behavior. Currently serving as Assistant Professor at Delhi Technological University, she holds a Ph.D. in HRM and OB from the same university. Her scholarly journey is distinguished by her UGC-NET JRF qualification in Commerce and Management and a consistent record of academic excellence, including gold medals from the University of Allahabad. She has published extensively in ABDC-ranked and Scopus-indexed journals, focusing on digital transformation, crowdsourcing, governance, and innovation. With professional experience in research and academia, she integrates theoretical insights with practical applications in her teaching. Dr. Mishra is also a certified HR analyst and an active contributor to workshops, conferences, and international journals. As a dynamic mentor, case study author, and book editor, she brings a holistic and impactful perspective to management research, particularly emphasizing value co-creation and technology-enabled governance systems.

Profile

Googlescholar

Education

Dr. Divya Mishra earned her Ph.D. in Human Resource Management and Organizational Behavior from Delhi Technological University, where she excelled with distinction. She holds postgraduate and undergraduate degrees in commerce, specializing in HR and Marketing, from the University of Allahabad, achieving top academic honors. Her early academic foundation was laid at Bethany Convent School, affiliated with CBSE, where she performed consistently well. She qualified for the UGC NET-JRF in Commerce and NET in Management, establishing her academic credentials further. Her academic trajectory reflects a consistent commitment to excellence, critical inquiry, and intellectual rigor. Her exposure to advanced quantitative research methods, structural equation modeling, and mixed-method approaches has enhanced her capacity to address contemporary challenges in management science. Additionally, her participation in numerous workshops and FDPs on research methodology, data analytics, AI, and publication ethics highlights her drive for continuous learning and academic engagement in evolving interdisciplinary domains.

Experience

Dr. Divya Mishra’s professional journey reflects a diverse blend of teaching, research, and industry experience. As an Assistant Professor at Delhi Technological University and previously at Vivekananda Institute of Professional Studies, she has taught management, business analytics, psychology, and development studies. Her academic roles include mentoring, research supervision, and curriculum design. She served as a Senior Research Fellow and Teaching Assistant at DTU during her Ph.D., contributing to research, teaching, and academic advising. Before transitioning into academia, she worked as a Research Associate at Boodle Web Mart, Noida, where she specialized in market research and data-driven strategic planning. Dr. Mishra also played pivotal roles in organizing NEP workshops, training programs, and interdisciplinary projects. Her experience spans both undergraduate and postgraduate teaching and encompasses administrative responsibilities, editorial work, and interdisciplinary collaboration. This multi-dimensional exposure has empowered her to integrate theory with practice and approach academia with real-world problem-solving insights.

Awards and Honors

Dr. Divya Mishra has received numerous academic distinctions throughout her career. She was awarded the prestigious HARI KESHAB GHOSH GOLD MEDAL, SRI BANARSILAL MEMORIAL GOLD MEDAL, and SRIBASANT BEHARI JAIRANI GOLD MEDAL for being the overall topper in both graduation and postgraduation from the University of Allahabad. She was honored with the Best Reviewer Award at the Academy of Management (AOM) Conference and serves as a peer reviewer for international journals like Springer Nature, IEEE, and others. She has completed multiple prestigious faculty development programs and earned certification in HR Analytics from the University of California, Irvine. Her role as organizer and coordinator in national-level NEP sensitization workshops highlights her leadership and academic outreach. Additionally, she has held key student leadership positions, including House Captain and Club Member, which nurtured her early organizational and leadership skills. These accolades demonstrate her excellence across academic, administrative, and scholarly domains

Research Focus

Dr. Divya Mishra’s research concentrates on Human Resource Management, Organizational Behavior, technological innovation, and digital governance, with a specific emphasis on crowdsourcing, open innovation, and digital transformation. Her interdisciplinary research explores the intersection of organizational learning, social capital, and strategic innovation. She employs quantitative and mixed-methods approaches, including Structural Equation Modeling and bibliometric analysis, to study knowledge transfer, governance models, influencer engagement, and entrepreneurial pathways. Her recent works address contemporary themes like crisis communication, participatory governance, influencer alignment, and metaverse adoption in banking. Her book on crowdsourcing and her editorial contribution to an upcoming Scopus-indexed volume showcase her depth in value co-creation and HR innovation. With several publications in SSCI/SCOPUS-indexed journals and over a dozen case studies published by SAGE, her research bridges academic theory and practical relevance. Dr. Mishra’s scholarship aligns with advancing organizational adaptability in the face of rapid digital change and stakeholder engagement in innovation ecosystems.

 

Publications

 

Effective governance through crowdsourcing: A strategic framework for empowered participation
Year: 2023
Citation: 8

Crowdsourcing-based social linkage and organizational innovation competence: knowledge transfer effectiveness and absorptive capacity as serial mediators
Year: 2024
Citation: 5

Crowdsourcing a wellspring of value co-creation: an integration of social capital and organisational learning mechanisms
Year: 2024
Citation: 4

Elucidating the determinants of crowdsourcing adoption for organisation value creation
Year: 2025
Citation: 3

 

Conclusion

Dr. Divya Mishra is a dynamic academician whose dedication to research, teaching, and innovation in Human Resource Management and Organizational Behavior significantly contributes to the evolving landscape of governance, technology, and organizational learning.

Meryem Yankol-Schalck | Insurance and Machine Learning | Best Researcher Award

Published on by Cognitive Scientist Awards

Assist. Prof. Dr. Meryem Yankol-Schalck | Insurance and Machine Learning | Best Researcher Award

 

Profile

Education

She holds a Ph.D. in Econometrics and Machine Learning from the University of Orleans (2018–2022), where she investigated new machine learning approaches for financial fraud detection and survival analysis in the insurance industry under the supervision of S. Tokpavi. In addition, she earned a Data Science Certificate (Executive) from the Institute of Risk Management (IRM) in 2016–2017. Her academic background also includes a Master’s degree in Mathematical Engineering (Applied Statistics) from Paris-Sud University (2004–2007) and a Master’s degree in Mathematics from the University of Marmara in Istanbul (1995–1999). Since September 2022, she has been an Assistant Professor of Data Science at IPAG Business School in Nice and Paris. With extensive experience in the insurance sector, she integrates her professional insights into the classroom, emphasizing practical AI applications. Her curriculum reflects the latest trends in data science, fostering a dynamic learning environment tailored to students’ needs. She adapts resources and pedagogical methods to specific course objectives, utilizing tools such as Tableau for data visualization and exploring real-world business applications, including Netflix, Uber, ChatGPT, Gemini, and facial recognition technologies.

 

Work experience

She has held various academic and professional roles, combining her expertise in data science, machine learning, and business analytics. From September 2022 to January 2023, she was an adjunct faculty member at the International University of Monaco, where she taught Mathematics for Business. Prior to that, from September 2021 to August 2022, she served as an adjunct faculty member at IPAG Business School (Nice), teaching courses such as “Data Analysis for Business Management” (BBA3), “Data Processing” (MSc, e-learning), “Digital and Sales” (GEP 5th year), and “Introduction to Statistics” (BBA1). Between September 2020 and October 2021, she was an adjunct faculty member at EMLV (Paris), where she taught “Quantitative Data Analytics – SPSS” (GEP 4th year, hybrid learning) and supervised master’s theses for GEP 5th-year students.

In addition to her academic roles, she has extensive experience in the consulting and insurance sectors. From March to November 2020, she worked as a Senior Consultant at Fraeris (Paris), supporting clients in project development and providing technical solutions. She collaborated with the “Caisse de Prévoyance Sociale” (CPS) of French Polynesia, modeling healthcare expenditures using machine learning techniques. She developed predictive models to analyze healthcare costs from both the insured’s and CPS’s perspectives, offering actionable insights and data-driven forecasts to aid long-term financial planning. Prior to that, in 2019–2020, she was a Senior Manager in Pricing & Data P&C at Addactis (Paris), where she supported clients in project development, innovation, and strategic planning. As an expert referent for ADDACTIS® Pricing software, she worked on database processing for BNP Paribas Cardif, facilitating APLe software operations for quarterly account closings.

Memberships and Projects:

• Membership of the American Risk and Insurance Association (ARIA)
• Membership of the academic association AFSE.
• Member of the RED Flag Project of the University of Orléans in cooperation with CRJPothier.
• Participation at 3 Erasmus+ Projects: Artificial Intelligence to support Education (EducAItion).
• Virtual Incubator Tailored to All Entrepreneurs (VITAE).
• Artificial Intelligence in high Education (PRAIME),

Research topics:

Studies focus on the application of data science techniques to business issues, particularly in the insurance
sector, and on climate change. Another topic of study is the relationship between AI and education.

Publication

  • Yankol-Schalck, M. (2023). Auto Insurance Fraud Detection: Leveraging Cost Sensitive and Insensitive
    Algorithms for comprehensive Analysis, Insurance: Mathematics and Economics.(
    (https://www.sciencedirect.com/science/article/abs/pii/S0167668725000216)
    Banulescu‐Radu, D., & Yankol‐Schalck, M. (2024). Practical guideline to efficiently detect insurance fraud
    in the era of machine learning: A household insurance case. Journal of Risk and Insurance, 91(4), 867-
    913.
    Yankol-Schalck, M. (2022). A Fraud Score for the Automobile Insurance Using Machine Learning and
    Cross-Data set Analysis, Research in International Business and Finance, Volume 63, 101769.
    Schalck, C., Yankol-Schalck, M. (2021). Failure Prediction for SME in France: New evidence from
    machine learning techniques, Applied Economics, 53(51), 5948-5963.
    On- going research:
    Yankol-Schalck (2025). Auto Insurance Fraud Detection: Machine Learning and Deep Learning
    Applications, submitted in Journal of Risk and Insurance.
    Schalck, C., Yankol-Schalck, M. (2024). Churn prediction in the French insurance sector using Grabit
    model, revision in Journal of Forecasting.
    Schalck, C., Seungho, L., Yankol-Schalck, M. (2024). Characteristics of firms and climate risk
    management: a machine learning approach. Work in progress for The Journal of Financial Economics.
    Yankol-Schalck M.and Chabert Delio C., (2024). The application of machine learning to analyse changes in
    consumer behaviour in a major crisis. Work in progress.
    Yankol-Schalck M. and Nasseri A. (2024).An investigation into the integration of artificial intelligence in
    education: Implications for teaching and learning methods. Work in progress.