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PLACEMENTS - 2024-25 - 614*- Still Counting , INFOSYS - 42 , COGNIZANT - 35 , TCS - 31 , PEGA - 01 , TECH MAHINDRA - 10 , PALTECH - 09 , WIPRO - 07 , MINDX360 - 05 , HCL TECHNOLOGIES - 20 , JMAN GROUP - 18 , PEOPLE TECH - 13 , CALIBER - 20 , MEDHA SERVO - 07 , VIRTUSA - 12 , EFFTRONICS - 12 , DELOITTE - 03 , TATA STRIVE - 35 , SMART ED - 02 , SIMPLYFI - 02 , M-CORE TECHNOLOGIES - 13 , TILICHO LABS - 05 , WELLNESS 360 - 01 , SOTI - 01 , COFORGE - 02 , BRAKES INDIA PVT LTD - 84 , TURTIL - 10 , GLOBAL LOGIC - 51 , TEKWISSEN GROUP - 18 , MOVATE - 14 , VERIZON - 01 , HANSA SOLUTIONS - 03 , BOSCH - 10 , EQIC - 10 , APMOSYS - 14 , STEELCUBE ENGINEERING PVT LTD - 13 , COVALENSE DIGITAL - 09 , ZFTECH - 01 , JOHN DEERE - 01 , QNUEVE SOLUTIONS - 10 , QUALITYKIOSK TECHNOLOGIES - 16 , HDFC BANK - 18 , SOLAR EDGE - 01 , CCC DIGITAL WORLD - 06 , GROW CONTROLS - 14 , DEALATECORP - 01 , APTROID - 02 , VEM - 10 , EVIONICS - 03 , AMARA RAJA - 01 Many More.....

V A Sai  Deepak

V A Sai Deepak

Assistant Professor, CSIT
saideepak.av@lendi.edu.in
Profile

4 Years

Male

Cyber Forensics & Information Security

M.Tech

2025-07-21
Experience
Organization Role Period
Schemax Tech Software Web Developer 2021-08-01 ~ 2023-08-20
Seminars & Workshops

Attended workshop on Machine Learning at IIT madras Research Park

Projects & Others

*Data protection in automated vehicles using blockchain and privacy by design in India: This project proposes a privacy-preserving framework for data handling in automated vehicles, aligned with the Digital Personal Data Protection (DPDP) Act, 2023, in India. The system ensures that vehicle and user data are collected only with explicit consent, stored securely using blockchain technology, and shared selectively for analytics or maintenance. By applying Privacy-by-Design principles, the framework minimizes personal data exposure while maintaining operational efficiency. The use of blockchain guarantees data integrity, transparency, and traceability, addressing trust and security challenges in intelligent transportation systems.

* Rainfall Prediction using Machine Learning: This project develops a predictive model to forecast rainfall using historical meteorological data, including temperature, humidity, wind speed, and atmospheric pressure. The approach uses machine learning algorithms such as Random Forest and Support Vector Regression for accurate prediction. Data preprocessing, feature selection, and model optimization are applied to improve reliability. The system can assist in agricultural planning, disaster management, and water resource management, offering a cost-effective decision-support tool.

*Cybersecurity on IoT: This project focuses on securing Internet of Things (IoT) devices and networks against common cyber threats such as unauthorized access, data breaches, and denial-of-service attacks. The framework employs lightweight encryption algorithms and intrusion detection systems (IDS) tailored for resource-constrained IoT devices. It also integrates blockchain-based authentication to ensure trust between devices and secure data exchange. The solution addresses vulnerabilities in IoT ecosystems, enhancing reliability and resilience in smart home, healthcare, and industrial applications.