Ekansh Agrawal

I am Ekansh Agrawal, currently pursuing my Final-year Bachelor of Technology majoring in Computer Science Engineering at Vellore Institute of Technology, Vellore. 

Recently, I completed my PRISM Research Internship at Samsung R&D, where I was actively involved in designing and developing Bixby capsules for pharmaceutical apps. This experience has not only enhanced my technical proficiency but has also exposed me to the practical application of Artificial Intelligence in addressing real-world challenges.

As a Machine Learning Research Intern at the prestigious Indian Institute of Management, Kozhikode, I analyzed the correlation between financially constrained firms and the MD&A section of annual 10K reports. My work resulted in an 81% accuracy for predicting financially constrained firms using a CNN model over the MD&A section.

In addition to my research experiences, I have actively participated in various software development internships, working on projects related to Industrial IoT solutions, supply chain optimization, and irrigation and crop-health recommendation systems.

One of my notable projects involved an intelligent surveillance system to detect security threats, including physical assault, fraud, and theft. I achieved an accuracy of 96.2% by applying Haar cascades and OpenCV for fast weapon detection in video frames. I analyzed that SOS alerts would be generated within 7 seconds of the incident using Twilio API and utilized MongoDB as the database. I also developed an Indian Native Language Detector. Through the utilization of NLP hybrid models like LinearSVC and Random Forest Classifier, I successfully created a language detection system with an impressive accuracy rate of 86.4%.

In addition to my practical experiences, I have consistently maintained an excellent academic record, consistently ranking in the top 1% of my department with a cumulative GPA of 8.88/10. I have undertaken rigorous coursework in subjects such as Algorithms, Machine Learning, Probability and Statistics, and Deep Learning, equipping me with a strong theoretical foundation in these areas. Proficient in programming languages such as C++, C, and Python, I possess the technical expertise necessary to implement complex algorithms and develop robust solutions.

Apart from my academic background, I am also a part of various clubs and chapters in VIT, Vellore. I am currently the Co-Secretary of IEEE-IAS VIT where I am a part of a 3-tier 10-member team responsible for handling 200+ committee members of various departments and managing a budget of INR 70k. We conducted 10+ international conferences, webinars, and 5+ hackathons for 5000+ participants from all over India for the academic session 2021-22.  I am also the Management Co-ordinator of VIT LEO Club aanNGO where I organized 200+ events including seminars with renowned activists, IAS, IPS, celebrities, and army officers for 50K+ participants and managed a budget of INR 50K for the academic session 2021-22.

Recently, I completed my PRISM Research Internship at Samsung R&D, where I was actively involved in designing and developing Bixby capsules for pharmaceutical apps. This experience has not only enhanced my technical proficiency but has also exposed me to the practical application of Artificial Intelligence in addressing real-world challenges.

As a Machine Learning Research Intern at the prestigious Indian Institute of Management, Kozhikode, I analyzed the correlation between financially constrained firms and the MD&A section of annual 10K reports. My work resulted in an 81% accuracy for predicting financially constrained firms using a CNN model over the MD&A section.

In addition to my research experiences, I have actively participated in various software development internships, working on projects related to Industrial IoT solutions, supply chain optimization, and irrigation and crop-health recommendation systems.

One of my notable projects involved an intelligent surveillance system to detect security threats, including physical assault, fraud, and theft. I achieved an accuracy of 96.2% by applying Haar cascades and OpenCV for fast weapon detection in video frames. I analyzed that SOS alerts would be generated within 7 seconds of the incident using Twilio API and utilized MongoDB as the database. I also developed an Indian Native Language Detector. Through the utilization of NLP hybrid models like LinearSVC and Random Forest Classifier, I successfully created a language detection system with an impressive accuracy rate of 86.4%.

I am currently pursuing my Final-year Bachelor of Technology majoring in Computer Science Engineering at Vellore Institute of Technology, Vellore. I have consistently maintained an excellent academic record, consistently ranking in the top 1% of my department with a cumulative GPA of 8.88/10. I have undertaken rigorous coursework in subjects such as Algorithms, Machine Learning, Probability and Statistics, and Deep Learning, equipping me with a strong theoretical foundation in these areas. Proficient in programming languages such as C++, C, and Python, I possess the technical expertise necessary to implement complex algorithms and develop robust solutions.