Malhar Dhavale
Self-driven Software Developer with hands-on experience in Full-Stack Development, Mobile Application Development, and Artificial Intelligence/Machine Learning. Skilled in building scalable applications using modern technologies and delivering user-focused solutions. Passionate about solving real-world problems through clean architecture, innovation, and continuous learning.
Experience
Software Developer
Phoenix Computers
Developed mobile and web applications using React Native and Django.
Integrated AI/ML functionalities for analytics and enhanced user interaction.
Collaborated with UI/UX teams and participated in deployment activities.
Contributed to maintenance and enhancement of live projects.
Machine Learning Intern, Cyber Security Projects Operations Department
Tata Advanced Systems Limited (TASL)
Delhi, India
Contributed to the development of an Integrated Detection & ML-Analysis System for cybersecurity applications.
Applied Machine Learning techniques to analyze and address real-world cybersecurity challenges.
Performed data analysis, model development, and system integration to improve detection capabilities.
Studied security threats, detection mechanisms, and analytical workflows in a defense-oriented environment.
Collaborated with cross-functional teams and industry professionals within a structured corporate setting.
AI & ML Intern
Techspot Infotech, Sangli
Worked on practical AI/ML applications and industry-oriented use cases.
Gained hands-on experience in machine learning workflows and implementation.
Education
Dr. D. Patil Pratishthan's College of Engineering, Kolhapur
B.E.
DKTE Society's Yashwantrao Chavan Polytechnic, Ichalkaranji
Diploma
Skills
PROJECTS
Safety Service Mobile App
React Native, Django, MySQL, Firebase
Developed a mobile application enabling users to discover and book verified service professionals through a secure, structured booking workflow.
Focused on women's safety through verified provider profiles and real-time accessibility, using Firebase for real- time sync and MySQL for structured records.
Real-Time HSRP ANPR & Intelligent Vehicle Recognition System
Computer Vision, YOLO, OCR, OpenCV, Real-Time Tracking
Developed a real-time Automatic Number Plate Recognition (ANPR) system to detect and verify High Security Registration Plates (HSRP) using YOLO-based object detection combined with OCR.
Implemented asynchronous processing and multi-object tracking pipelines with OpenCV, and built a real-time dashboard for live vehicle monitoring and recognition results.
Explainable Multimodal AI Cancer Detection System
Deep Learning, Medical Imaging, Multimodal AI, Explainable AI
Built a multimodal deep learning system for cancer detection by combining medical imaging data with complementary clinical inputs to improve diagnostic accuracy.
Integrated explainable AI techniques to generate interpretable predictions, helping visualize the model's reasoning behind each diagnosis.
AI-Powered Network Intrusion Detection & SIEM Analytics System
ML + Cybersecurity, Anomaly/Threat Detection, Graylog/SIEM Integration
Designed a machine learning-based network intrusion detection system to identify anomalous traffic patterns and potential security threats in real time.
Integrated the system with Graylog/SIEM for centralized log analytics and built a dashboard for threat visualization and monitoring.
Squid Examiner
Python, OpenCV, Machine Learning
Designed an AI-powered invigilation system that uses computer vision to detect suspicious activity during examinations, aiming to improve exam integrity.
Leveraged OpenCV for real-time video processing and ML for behavior classification; research published in IJFMR Volume 6, Issue 2.
CERTIFICATIONS
Full Stack Web Development (MERN Stack)
Artificial Intelligence & Machine Learning
Java Programming
Great Learning Academy
Google Developer Groups Solution Challenge Certificate
Course on Computer Concepts (CCC)
NIELIT
LEADERSHIP & ACHIEVEMENTS
Active Technical Team Lead
AWS Builder Group DYPSN (AWSBG)
Active Member
Google Developer Groups On Campus DYPSN (GDGoC)