Interview Report

D

Dr. Sanjeet Kumar Subudhi

s************[email protected]

Interviewed on Jan 22, 2026

Completed
Flagged for suspicious behaviour
80SCORE

Overall performance

Professor

Good fit for roleAcademic

Candidate excels in must-have skills and overall performance.

Summary

Report summary

Candidate Snapshot

The candidate exhibits a structured and methodical approach to teaching and research. They emphasize real-world applications of concepts and demonstrate strong interdisciplinary focus, integrating AI/ML, power electronics, and nonlinear dynamics into their teaching and research. Their ability to simplify complex topics through incremental learning and hands-on examples is notable, alongside their strategic approach to fostering innovation and research among students.

Primary Challenges

Let us delve into your credentials and teaching experience. First, you mentioned a strong interest in interdisciplinary research. Could you elaborate on how you have woven this interdisciplinary approach into your teaching or curriculum design? For example, are there courses or modules you've introduced that reflect this philosophy?

Discuss how interdisciplinary research is integrated into teaching or curriculum design.

The candidate mentioned introducing AI/ML into the syllabus and assigning projects on transformer condition monitoring and health monitoring using machine learning techniques. They also worked with students from various branches on projects like corrosion management and analysis using machine learning, and conducted a project on Parkinson's disease detection using machine learning in their postgraduate program.

Observations

  • Interdisciplinary integration
  • AI/ML application in curriculum
  • Real-world project application
  • Depth of curriculum design process
  • Specific challenges faced during curriculum integration

Could you walk me through how you typically mentor students through such interdisciplinary projects? For instance, how do you ensure students from different academic backgrounds collaborate effectively and achieve impactful results?

Explain mentorship method for interdisciplinary projects.

The candidate emphasized the importance of team formation based on students' strengths and weaknesses. They assign topics for literature review, encourage team discussions, and ensure alignment with the curriculum and real-world applications. They also guide students in implementing learned concepts in practical research.

Observations

  • Team formation strategy
  • Encouraging collaboration
  • Aligning projects with real-world applications
  • Handling conflicts or challenges in team dynamics
  • Specific examples of impactful interdisciplinary outcomes

Could you elaborate on the process you follow for assessing students, both in theory-based and project-based courses? Specifically, how do you ensure an objective and comprehensive evaluation of their learning and application skills?

Discuss student evaluation methods for theory-based and project-based courses.

The candidate described using a mix of assignments, internal assessments, mid-semester evaluations, and end-semester evaluations. They incorporate experiential learning, project case studies, seminar topics, and simulation-based studies for indirect assessment. They also assign incremental real-world application projects linked to lab courses.

Observations

  • Comprehensive evaluation methods
  • Incorporation of experiential learning
  • Handling subjectivity in indirect assessments
  • Specific challenges in implementing these assessments

Observed Capabilities

  • Interdisciplinary integration
  • Mentorship in collaborative projects
  • Comprehensive student evaluation methods
  • Application of AI/ML in real-world projects
  • Focus on real-world applicability
  • Addressing team dynamics challenges
  • Managing subjectivity in assessments
  • Depth of curriculum design
  • Specific examples of challenges faced during curriculum design or project mentorship

Real-World Indicators

  • Introduced AI/ML into curriculum design.
  • Guided students in interdisciplinary projects like corrosion analysis and Parkinson's detection using machine learning.
  • Implemented real-world applications in student projects, such as transformer condition monitoring.

Contextual Gaps

  • Details on challenges faced during interdisciplinary curriculum integration.
  • Examples of conflict resolution in student collaboration.
  • Specific methods to handle subjectivity in assessments.

Strength Areas

Interdisciplinary Research
  • Curriculum integration of AI/ML
  • Guidance on interdisciplinary projects
Mentorship
  • Team formation based on strengths
  • Encouraging collaboration and literature review
Student Evaluation
  • Comprehensive assessment framework
  • Use of experiential and project-based learning

Recording

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Transcript

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Technical skills

6
MATLAB & SimulinkPythonXPP AUTOLaTeXMS OfficeOPAL-RT Real-Time Simulator

Soft skills

3
MentoringLeadershipCurriculum Design

Detected events

  • 0:00Multiple Monitors

Speakers

1 speaker

Face preview

Face analysis

Resume score

Resume

Resume.pdf

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