Dr. S. Srikrishnan

Professor, Dean-CSE

As Dean of Computer Science, Dr. S. Srikrishnan brings a distinctive combination of academic excellence and industry expertise to the department. He holds a Ph.D. from CUSAT, an MTech degree from IIT Kharagpur, and a B.Sc. in Engineering from CET, Thiruvananthapuram.

He has over 14 years of experience as a professor and 25 years as an IT Consultant.

Dr. S Srikrishnan has previously held various tenured and visiting professorships in computer science and business analytics at institutions such as the Kerala University of Digital Sciences, Innovation, and Technology; Loyola Institute of Business Administration, Chennai; LM Thapar School of Management; Agni College of Technology; and SCMS-Cochin.

As an IT consultant, he has successfully led multicultural teams in software application development and technology centers of excellence in India, the UK, and the USA.

He has worked with esteemed organizations including Tata Consultancy Services, Covansys Inc. USA, UST Global, and HCL Technologies Ltd.

Publications

Dr.S Srikrishnan, Ashwin Pushparaj, Advaith Suresh, Akash Krishnan Nair (2024). Survey on personalized voice assistant. In 6th International Conference on Recent Advances in Intelligent Computational Systems IEEE RAICS 2024.
Shanmugam, S., Krishnan, S. S., & Tholath, D. I. (2021, January). A behavioral study on the factors influencing selection of restaurants online during COVID-19 using multivariate statistical analysis. In 2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence) (pp. 996-1003). IEEE.
Srikrishnan, S. (2020). Business Analytics–Overview, Curriculum, Opportunities and Skills. Management Matters (LIBA's journal of management), 18(1)
Sundararajan, S., Marath, B., & K. Vijayaraghavan, P. (2019). Variation of risk profile across software life cycle in IS outsourcing. Software Quality Journal, 27, 1563-1582.
Sundararajan, S., Bhasi, M., & Pramod, K. V. (2017). Managing software risks in maintenance projects, from a vendor perspective: a case study in global software development. International Journal of Information Technology Project Management (IJITPM), 8(1), 35-54.
Sundararajan, S., Bhasi, M., & Vijayaraghavan, P. K. (2014). Case study on risk management practice in large offshore‐outsourced Agile software projects. IET Software, 8(6), 245-257.
Sundararajan, S., Bhasi, M., & Pramod, K. (2013). An empirical study of industry practices in software development risk management. International Journal of Scientific and Research Publications, 3(6), 1-11.
Sundararajan, S., Bhasi, M., & Pramod, K. V. (2013). A Case Study on Risk Management Practice in Outsourced Software Migration Projects. International Journal of Computers and Technology, 11, 2601-2617.

Book

Sundararajan, S. (2025). Multivariate Analysis and Machine Learning Techniques: Feature Analysis in Data Science Using Python. Springer Nature.

Book Chapters

S. Srikrishnan, “Introduction and overview,” in Multivariate Analysis and Machine Learning Techniques: Feature Analysis in Data Science Using Python. Singapore: Springer Nature, 2025, pp. 1–26. [Online]. Available: https://link.springer.com/chapter/10.1007/978-981-99-0353-5_1
S. Srikrishnan, “Python for data analytics,” in Multivariate Analysis and Machine Learning Techniques: Feature Analysis in Data Science Using Python. Singapore: Springer Nature, 2025, pp. 29–80. [Online]. Available: https://link.springer.com/chapter/10.1007/978-981-99-0353-5_2
S. Srikrishnan, “Introduction to probability and statistics,” in Multivariate Analysis and Machine Learning Techniques: Feature Analysis in Data Science Using Python. Singapore: Springer Nature, 2025, pp. 81–111. [Online]. Available: https://link.springer.com/chapter/10.1007/978-981-99-0353-5_3
S. Srikrishnan, “Hypothesis testing,” in Multivariate Analysis and Machine Learning Techniques: Feature Analysis in Data Science Using Python. Singapore: Springer Nature, 2025, pp. 113–141. [Online]. Available: https://link.springer.com/chapter/10.1007/978-981-99-0353-5_4
S. Srikrishnan, “Regression analysis,” in Multivariate Analysis and Machine Learning Techniques: Feature Analysis in Data Science Using Python. Singapore: Springer Nature, 2025, pp. 143–182. [Online]. Available: https://link.springer.com/chapter/10.1007/978-981-99-0353-5_5
S. Srikrishnan, “Classification,” in Multivariate Analysis and Machine Learning Techniques: Feature Analysis in Data Science Using Python. Singapore: Springer Nature, 2025, pp. 183–210. [Online]. Available: https://link.springer.com/chapter/10.1007/978-981-99-0353-5_6
S. Srikrishnan, “Factor analysis,” in Multivariate Analysis and Machine Learning Techniques: Feature Analysis in Data Science Using Python. Singapore: Springer Nature, 2025, pp. 211–239. [Online]. Available: https://link.springer.com/chapter/10.1007/978-981-99-0353-5_7
S. Srikrishnan, “Cluster analysis,” in Multivariate Analysis and Machine Learning Techniques: Feature Analysis in Data Science Using Python. Singapore: Springer Nature, 2025, pp. 239–269. [Online]. Available: https://link.springer.com/chapter/10.1007/978-981-99-0353-5_8
S. Srikrishnan, “Survival analysis,” in Multivariate Analysis and Machine Learning Techniques: Feature Analysis in Data Science Using Python. Singapore: Springer Nature, 2025, pp. 271–307. [Online]. Available: https://link.springer.com/chapter/10.1007/978-981-99-0353-5_9
S. Srikrishnan, “Computational techniques,” in Multivariate Analysis and Machine Learning Techniques: Feature Analysis in Data Science Using Python. Singapore: Springer Nature, 2025, pp. 309–347. [Online]. Available: https://link.springer.com/chapter/10.1007/978-981-99-0353-5_10
S. Srikrishnan, “Machine learning,” in Multivariate Analysis and Machine Learning Techniques: Feature Analysis in Data Science Using Python. Singapore: Springer Nature, 2025, pp. 349–390. [Online]. Available: https://link.springer.com/chapter/10.1007/978-981-99-0353-5_11
S. Srikrishnan, “Artificial intelligence and deep neural networks,” in Multivariate Analysis and Machine Learning Techniques: Feature Analysis in Data Science Using Python. Singapore: Springer Nature, 2025, pp. 391–435. [Online]. Available: https://link.springer.com/chapter/10.1007/978-981-99-0353-5_12
“IoT-Enabled Smart Traffic Management: Reducing Congestion with AI and Sensors,” in Advancements in Science, Engineering, and Technology: A Modern Perspective, N. Sureshkumar, V. Satheeswaran, and M. Murugesan, Eds. : PROTEK Publications, 2025.
“A Smart AIoT-Enabled Agricultural System for Pest Detection,” in Advancements in Science, Engineering, and Technology: A Modern Perspective, N. Sureshkumar, V. Satheeswaran, and M. Murugesan, Eds. : PROTEK Publications, 2025.
“Predicting Lateral Movement in Azure Hybrid Networks using GNNs,” in Advancements in Science, Engineering, and Technology: A Modern Perspective, N. Sureshkumar, V. Satheeswaran, and M. Murugesan, Eds. : PROTEK Publications, 2025.
“AI-Driven Identity Verification in Decentralized Identity Systems,” in Advancements in Science, Engineering, and Technology: A Modern Perspective, N. Sureshkumar, V. Satheeswaran, and M. Murugesan, Eds. : PROTEK Publications, 2025.
“Exposing Deepfake Deception: Real Time Deepfake Detection using GNN,” in Advancements in Science, Engineering, and Technology: A Modern Perspective, N. Sureshkumar, V. Satheeswaran, and M. Murugesan, Eds. : PROTEK Publications, 2025.

Achievements in ASIET

Convenor of the International Conference on Emerging Trends in Applied Science, Management & Technology (ICEAMT-2025) held from July 31 – August 1, 2025 at Adi Shankara Institute of Engineering & Technology, Kalady.
Keynote Speaker at the AI in Healthcare Conference (HOSPEX-2025), organised by Hospex/SMART Hospitals and QAI at KINFRA International Exhibition Center, Kochi from August 22–24, 2025. Presented on August 23, 2025: “Integrating Generative and Agentic AI into Next-Generation Multi-Modal and Interoperable Healthcare Systems.”
Coordinator for the Atal FDP program titled 'Exploring Explainable and Generative AI in Contemporary Machine Learning' from January 15-20, 2024.
Served as a resource person on the topic ‘Research Methodology’, in the Atal FDP program Exploring Explainable and Generative AI in Contemporary Machine Learning
Provided leadership in the development of ASIET's current regular technical training program.
Led a team of CSE and CSE-AI faculty in the design and implementation of an 80-hour training program titled 'Data Science using Python,' catering to second-year BTech students across all branches. This hands-on program offers comprehensive coverage of data science topics, including Python for Data Science, Advanced Statistics, Machine Learning, and Deep Learning, concluding with a capstone project.

Professional Certifications

ITIL – EXIN (Information Technology Infrastructure Library), EXIN. Issued Jan 2012 · No Expiration Date
PMP – PMI (Project Management Professional), PMI. Issued Jan 2003 · Expired
CSQA - QAI (Certified Software Quality Analyst), QAI. Issued Jan 1998 · No Expiration Date.

IT Industry Projects

As an IT consultant/Technical Architect at the Center of Excellence, he has fulfilled various roles both onsite and offshore, contributing to the development, maintenance, modernization, and testing of information systems projects for several Fortune 500 multinational corporations, including: