DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
cse
G.Priyadharshini
 |
| Designation | : | Assistant Professor |
| Nature of Employment | : | Regular |
| Date of Joining | : | |
| Qualification | : | B.E,.M.Tech,(Ph.D) |
| Phone | : | +91 44 2275 1347,48,50 (Office) |
| Email ID | : | priyadharshini@crescent.education |
Teaching
Educational Background
| Degree | Discipline | Year of Passing | University |
|---|---|---|---|
| Ph.D | Machine Learning | Pursuing | SRM Institute of Science and Technology, Chennai |
| M.Tech | Computer and communication Engineering | 2012 | Karunya University, Coimbatore |
| B. E | Computer science and engineering | 2010 | Anna University, Chennai |
Work Experience
| Designation | Institution | Duration | No. of Years |
|---|---|---|---|
| Asst. Professor | B.S. Abdur Rahman Crescent Institute of Science & Technology | July 2023 to till date | Till date |
| Asst. Professor | Prince Shri Venkateswara Padmavathy College of Engineering and Technology, Chennai | Dec 2014-June 2015 | 6 months |
| Asst. Professor | Sri Krishna College of engineering and Technology, Coimbatore | June 2012-november 2013 | 1 year 6 months |
Lecture Courses
- AI & ML
- DBMS
Research
Areas of Research Interest
- Machine Learning
- Deep Learning
Publications
- Published a paper titled ”CSO-CNN: Circulatory system optimization-based cascade region CNN for fault estimation and driver behavior detection” Published in Signal, Image and video processing 2023, Springer Nature. Impact factor:1.583
- Published a paper titled, “Stacking optimized with artificial bee colony for driving style classification by feature reconstruction from obd ii data” in Soft Computing 27, 591–603 (2023) Impact factor: 3.732
- Published a paper titled, “An empirical evaluation of importance-based feature selection methods for the driver identification task using OBD data” in International Journal of System Assurance Engineering and Management 2022, Springer Nature, Impact factor:2.018
- Published a paper titled, “A detailed review of various data collection approaches, parameters and algorithms used for classification for driving pattern analysis “Published in IOP conference series: Material Science and Engineering 2020, SNIP-0.53.
