R.C.Patel Institute of Technology Faculty Details 2026-27

R.C. Patel Institute of Technology (RCPIT), an autonomous engineering college located in Shirpur, Dhule, Maharashtra, hosts a highly structured and research-driven faculty ecosystem across its undergraduate (B.Tech) and postgraduate technical divisions. Approved by the AICTE, accredited with an 'A' grade by NAAC, and permanently affiliated with Dr. Babasaheb Ambedkar Technological University (DBATU), the institution maintains a rigorous academic environment by recruiting seasoned academicians, active research guides, and industry experts.

The teaching staff at RCPIT plays a dual role: delivering a state-of-the-art ICT-based curriculum and actively guiding students through specialized skill development blueprints. Rather than operating purely as classroom lecturers, the faculty serves as technical mentors, steering innovation, patent filings, and corporate collaboration to prepare engineering graduates for the demands of the modern technical workforce.

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Teaching Staff Details

The academic framework at RCPIT is organized into several key engineering disciplines: Computer Engineering, Computer Science & Engineering (Data Science), Artificial Intelligence and Machine Learning (AI&ML), Electronics and Telecommunication Engineering (E&TC), Information Technology (IT), Electrical Engineering, Civil Engineering, Mechanical Engineering, and the Department of Applied Sciences & Humanities.

The teaching staff complies with the statutory guidelines of the University Grants Commission (UGC) and DBATU, dividing faculty members into structured, performance-indexed tiers:

• Director and Professors: Senior academicians who orchestrate long-term institutional development policies, lead research initiatives, and manage broad departmental administrations.

• Associate Professors: Faculty members who balance advanced engineering classroom instructions, hold administrative dean positions, and manage laboratory design pipelines.

• Assistant Professors: Dedicated educators focusing on the daily execution of technical modules, primary laboratory sessions, and continuous evaluation systems.

The faculty team includes a dynamic mix of permanent experts and active researchers. For example, within the core Department of Computer Engineering, 14 out of 28 faculty members hold a Ph.D. degree, while the remaining members are actively engaged in doctoral research or advanced corporate consultancy projects.

Qualifications and Industry Experience

The qualification metrics at RCPIT demonstrate an emphasis on academic excellence and research capabilities. A high percentage of the teaching staff possess postgraduate degrees (M.Tech/M.E.) from premium institutions, alongside a robust contingent of doctoral (Ph.D.) holders.

Senior professors and heads of departments at the Shirpur campus boast between 15 to 40 years of continuous teaching, research, and consulting experience. The areas of expertise within the technical departments cover highly competitive and modern domains:

• Computing and Software Engineering: Machine Learning, Deep Learning, Data Mining, Web Security, Soft Computing, and Network Security.

• Electronics & Telecommunications: Medical Image Processing, Digital Communication, Antenna Design, Embedded Systems, and AI in Healthcare.

• Applied Sciences & Humanities: Numerical Methods, Organic Synthesis, Nanomaterials, Energy Conversion Devices, and English Language Teaching (ELT).

This research focus directly enhances the academic environment, with the engineering faculty contributing over 300 research papers to peer-reviewed international journals, filing over 30 patents, and registering 18+ copyrights.

Student–Faculty Ratio

RCPIT maintains an optimal student-to-faculty ratio in alignment with standard AICTE parameters, facilitating a personalized approach to technical instruction.

• Personalized Attention: General lectures are organized to maximize peer interaction, while advanced laboratory classes are split into smaller batches to provide hands-on experience and direct faculty support.

• Structured Mentorship Framework: Every department implements an active mentorship network. A dedicated faculty advisor is assigned to a specific group of students to guide them through continuous internal evaluation (CIE), internship opportunities, and career choices.

• Remedial & Advanced Tracking: The balanced ratio allows the faculty to run targeted diagnostic sessions, ensuring slow learners receive remedial classes while advanced students receive guidance for competitive exams like GATE, GRE, TOEFL, and IELTS.

Faculty List

The following table presents a non-exhaustive sample of prominent faculty members, administrators, and departmental heads at R.C. Patel Institute of Technology, Shirpur:

Teaching Methods and Pedagogy

The faculty at RCPIT utilizes student-centric teaching methodologies designed to foster problem-solving capabilities and industry readiness.

• ICT-Enabled Blended Learning: Lectures are delivered in fully smart, ICT-enabled classrooms utilizing presentations, digital visualizers, and online learning platforms. Complex algorithms and architectural setups are simplified through structural audio-visual tools.

• Outcome-Based Education (OBE): The academic staff enforces strict OBE metrics where individual course outcomes (COs) are explicitly mapped to broad program outcomes (POs) defined by the National Board of Accreditation (NBA), checking student comprehension via continuous internal assessments.

• Interactive Learning Communities: Faculty members actively manage and mentor student-led innovation clubs, including the Google Developer Student Club (GDSC/GDG) and competitive coding fraternities. Group discussions are held in small batches of 7 to 8 students to foster collaborative peer learning and clear doubts effectively.

• Industrial & Experiential Synergy: The teaching staff integrates standard textbook theories with engineering hackathons (such as the Smart India Hackathon) and competitive platform coding. Regular industry-institute interactions ensure that laboratory experiments are continually updated to model contemporary corporate requirements.