Flagship Engineering Program

B.Tech Computer Science & Engineering – Sreyas Institute

Engineering systems, not just writing code.

Software development, systems thinking, cloud engineering, and industry-ready problem solving.

640

Intake

2011

Established

120+

Build Projects / Year

CSE students presenting technical projects

Head of Department – Computer Science & Engineering

Head of Department

Dr. U. M. Fernandes Dimlo

Dr. U. M. Fernandes Dimlo

Head of the Department, CSE

Qualification: B.E. M.E Ph.D Computer Science and Engineering

Contact:
+91 9701056819
cse.hod@sreyas.ac.in

Qualifications:

  • Ph.D from University of Mysore, Mysore, Karnataka .

  • M.E in CSE from Hindustan College of Engineering, Chennai Affiliated to Anna University, Chennai (2004-2006)

  • B.E in CSE from Jayaram College of Engineering and Technology, Trichy, Tamil Nadu affiliated to Bharathidasan University, Trichy (1994-1998).

Experience:

  • 24 years of experience.

  • 24 years of teaching experience for both UG and PG. Taught subjects like Compiler design, Formal languages and Automata theory, Design and Analysis of Algorithms, Machine Learning, Data Structures, Mathematical Foundations of Computer Science, Information Security

Current Association:

  • Professor & Head of the Department  Computer Science and Engineering, at SREYAS Institute of Engineering and Technology, affiliated to JNTUH.

Professional Memberships:

  • Life Member – ISTE (LM -99187, Year: 2014)

Research, Projects & Publications

  • Published 22 papers in National and International Conferences and Journals.

  • Organized and Attended several Faculty Development Programs (FDPs) / Workshops / Seminars.

Achievements:

  • Delivered Guest lectures / Expert lectures on Automata theory in various Engineering colleges across Hyderabad.

  • Acted as Judge for various National Level Technical Fests.

Books/Chapters Reviewed:

  • Published book titled “Python for Professionals” in BP Publications PVT.LTD.

Research Areas:

  • Automata Theory

  • Machine Learning

  • Information Security