Interview Report

M

Mr. Subhadip Roy

s**********[email protected]

Interviewed on Apr 20, 2026

Completed
52SCORE

Overall performance

Assistant Professor - Mathematics

Not a fitAcademic

Lacks must-have expertise in AI ML and industry projects

Summary

Report summary

Preliminary Screening

Executive Summary

The candidate holds a mathematics major and has submitted a PhD thesis focused on metric fixed point theory, with a solid publication record including SCI and Q1 journals. He demonstrates clear experience in teaching theory and lab sessions, student evaluation, and research supervision, particularly in pure mathematics topics such as fractals and fixed point theory. The most critical gap is his lack of expertise and practical experience in advanced statistical methods, supply chain management, AI/ML mathematics, and industry-linked projects or consultancy. He shows willingness to adapt teaching methods and participate in departmental governance but lacks familiarity with accreditation processes and cross-disciplinary applications. Overall, his profile aligns with foundational academic and research strengths but reveals significant gaps in industry relevance and interdisciplinary breadth required for the role.

Strengths

  • Clear articulation of teaching experience during PhD, including assisting with course materials and student engagement.
  • Demonstrated method of adapting lectures based on student understanding and using visualization for abstract concepts.
  • Specific example of using the geometrical illustration of Rolle's theorem to make abstract ideas accessible.
  • Supervised master's student projects on fractals and fixed point theory, guiding research question development.
  • Encourages creativity in student solutions as long as logical reasoning is maintained in mathematical answers.
  • Strong theoretical research background with 17–18 publications, several in SCI and Q1 journals.
  • Willingness to participate in departmental governance, curriculum activities, and academic discussions.
  • Open to feedback and committee review in case of grading disputes.

Gaps / Risks

  • No experience or demonstrated knowledge in supply chain management, advanced statistical methods, or AI/ML mathematics.
  • No direct industry project or consultancy experience; only exposure is through conference attendance.
  • Limited examples of interdisciplinary teaching or research integration beyond pure mathematics.
  • Unfamiliarity with accreditation processes and standardized outcome assessment procedures.
  • No clear evidence of developing industry connections for student placements or internships.
  • Lack of hands-on experience in teaching applied mathematics or laboratory courses outside abstract theoretical domains.
  • Did not provide concrete examples for supply chain or advanced statistical modeling in teaching or research.

What to Probe in the Next Round

  • Request a detailed example of applying mathematical concepts to an interdisciplinary or industry-relevant project, especially in supply chain management or AI/ML.
  • Probe for practical experience or planned approach to teaching advanced statistical methods, including laboratory settings.
  • Assess understanding of university accreditation standards and how to implement standardized outcome assessment across courses.
  • Explore strategies for building industry partnerships or consultancy opportunities relevant to mathematics students.
  • Clarify approach to integrating applied mathematics topics into curriculum and fostering student exposure to real-world problem-solving.

Final Recommendation

Foundational Alignment

Candidate demonstrates strong academic grounding and experience in pure mathematics teaching and research but shows significant gaps in applied, interdisciplinary, and industry-relevant areas critical for the role.

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Technical skills

8
CMatlabMicrosoft OfficeExcelWordPowerPointLATEXWolfram Mathematica

Soft skills

3
TeachingResearchAnalysis

Speakers

1 speaker

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Resume score

Resume

Resume.pdf

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