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IIT Lucknow - Indian Institute of Information Technology Facilities Details

The faculty at the Indian Institute of Information Technology (IIIT), Lucknow, is characterized by its high academic pedigree and a modern, industry-focused approach to technical education. As an Institute of National Importance, it attracts educators who are primarily focused on high-end research in Artificial Intelligence, Data Science, and Management.

Faculty Profile & Qualifications

  • Academic Excellence: Nearly 100% of the permanent faculty members hold a Ph.D., with many having earned their degrees from premier institutions such as IIT Kanpur, IIT Roorkee, IIT Delhi, and JNU, as well as reputed international universities.

  • Research Focus: Many faculty members have distinguished research backgrounds, including Fulbright Fellows and former scientists from organizations like DRDO. 

  • Student-to-Faculty Ratio: The institute maintains a healthy ratio of approximately 1:8 to 1:12, allowing for significant individual interaction, especially for students pursuing research projects or niche specializations in B.Tech and M.Tech. 

    Key Academic Leaders

     

    Name

    Designation

    Dr. Arun Mohan Sherry

    Director

    Dr. Saurabh Shukla

    Assistant Professor

    Dr. Deepshikha Agarwal

    Assistant Professor

    Dr. Mary Samuel

    Assistant Professor

    Dr. Niraj K. Vishvakarma

    Assistant Professor

     

     Teaching Methodology

    • Coding Culture: Faculty members are known for fostering a strong competitive programming environment from the very first year. Unlike traditional colleges, the curriculum focuses immediately on core CS/IT subjects. 

    • Approachable Mentorship: Student feedback consistently highlights that the faculty is "approachable" and "supportive," particularly regarding final-year projects and startup incubation through the institute's Incubation Centre. 

    • Digital Integration: Lectures frequently utilize a mix of modern PPT-based delivery for conceptual clarity and traditional blackboard methods for complex mathematical and algorithmic derivations.

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