Photo of University Hall

View Profile Page

Faculty/Staff Login:

Vaibhav Anu

Assistant Professor, School of Computing

Download vCard


Dr. Anu is an Assistant Professor of Computer Science at Montclair State University. He joined Montclair State in Fall 2018. Before joining Montclair State, he received a PhD in Software Engineering from North Dakota State University.

Undergraduate Courses Taught at Montclair State University:
# CSIT 416 - IT Project Management (Sessions: SP23, FA22, FA21, SP21, FA20, SP20, FA19, SP19, FA18)
# CSIT 315 - Software Engineering I (Sessions: FA22, FA21)
# CSIT 415 - Software Engineering II (Sessions: SP22)
# CSIT 104 - Python Programming I (Sessions: FA21, FA20, SP19)
# CSIT 460 - Computer Security (Sessions: SP20)

Graduate Courses Taught at Montclair State University:
# CSIT 590 - Cyberspace Governance, Policy, and Ethics (Sessions: SP23, SP22)
# CSIT 555 - Database Systems (Sessions: SP21)
# CSIT 610 - IT Project Management (Sessions: SU20, FA19)
# CSIT 615 - Advanced Topics in Software Engineering (Sessions: SP20)

Undergraduate Courses Taught at North Dakota State University:
# CSCI 116 - Business Use of Computers (Sessions: SP10, FA10, SP11)


Dr. Anu is interested in software development planning, analysis, and management, and particularly in improving software quality by improving the processes and practices involved in software development.

The primary focus of Dr. Anu's research is on development and empirical validation of effective methods for verification and validation (V&V) of software artifacts.

Dr. Anu's Research Interests include:
Software Engineering, Requirements Engineering, Human Error in Software Engineering, Software Inspections, Software Quality Improvement, Empirical Software Engineering, Software Engineering Education, Human Factors in Cybersecurity

Office Hours


1:30 pm - 2:30 pm
1:30 pm - 2:30 pm


1:00 pm - 2:00 pm
1:00 pm - 2:00 pm


Research Projects

CS for Everyone Everywhere (CSEE) Program

The Montclair State University CS for Everyone Everywhere (CSEE) Program supports participating Local Educational Agency (LEA) representatives in developing a standards-aligned, high-quality K-12 computer science program. This project is funded by NJ DOE (NJDOE Standards 22E00178).

Using Maching Learning to Automate the Procedures Involved in Requirements Inspections

Requirements inspections involve multiple inspectors independently reviewing a requirements document and reporting faults in the document. But, inspectors report both faults and non-faults (false-positives). We are using machine learning based approaches to validate requirements reviews. Our approach uses supervised machine learning algorithms to isolate faults from false-positives. An important feature that we use for training our classifiers is labeling our review data with the fault-types (ambiguity, inconsistent, incorrect requirements, omission, etc.).