Dr. Abhijit Das is a highly experienced Computer Science professional with a Ph.D. in Computer Science and Engineering. He has 17 years of teaching experience at the college level and one year of industry experience. Abhijit’s educational qualifications include a Ph.D. in Computer Science and Engineering from VTU, a Master of Technology (MTech) in Computer Science and Engineering from JNNCE, Shivamogga, and a Bachelor of Engineering (B.E) in Computer Science & Engineering from the National Institute of Technology, Agartala. He has a strong background in teaching various subjects such as Machine Learning, Operating Systems, Java, Python, Computer Networking, and more. His research work has been published in renowned Scopus Indexed Journals, covering topics such as Cyber Security & Deep Learning.  He has 2 Patents to his credit (i). Patent Number: 2021105857 · Issued Nov 3, 2021. (ii). Patent Number: 202221011722 Issued: April 15,2022. He has been Certified by IBM for guiding Projects on Mobile Banking Project listed in Top 10 in IBM-TGMC The Great Mind Challenge,2007. Won 2nd prize in TECHZONE, a State Level Technical Symposium in C programming. Worked as a project coordinator on VGST project Funded by Government of Karnataka Duration of Project 2017-2019.

"The only way to do great work is to love what you do." - Steve Jobs

• To develop a novel ensemble-based model for cyber security using a machine learning classifier to maximize classification accuracy, minimize false alarms, and identify attackers quickly.
• To develop a trust-based DDoS discovery method for encrypted traffic in the cloud environment with the current ML-based IDS to detect DDoS threats over the cloud and combine the cloud service’s security authentication.
• To develop an ensemble-based novel hybrid deep learning approach to provide a better network intrusion detection model by learning complex features automatically and lowering the false alarm.
• To develop an auto encoder-based ensemble learning technique that employs a novel swarm intelligence optimization algorithm to increase accuracy with which it can detect new cyber threats without retraining and minimize the response time to detect an attack within large volumes of data.
• Research Interests - Network Security, Cyber Security, Intrusion Detection and Prevention Systems, Deep Learning

• Have been Certified by IBM for guiding Projects on Mobile Banking (Project listed in Top 10 in IBM-TGMC- The Great Mind Challenge,2007)

• Won 2nd prize in TECHZONE, a State Level Technical Symposium in C programming.

• Worked as a project coordinator on the VGST project Funded by the Government of Karnataka (Duration of Project 2017-2019).