Apr 2023 – Dec 2024 · 1 yr 8 mos · Victoria, Australia

• As a Machine Learning Engineer at Digital Barriers, I have played a pivotal role in enhancing our video analytics solutions. My work involves collaborating with the CTO AI and various cross-functional teams to improve and maintain the video analytics C++ SDK. I have spearheaded the development of a natural language-based smart search product for CCTV activity search, optimized deep learning modules for performance, and contributed to integrating cutting-edge technologies for cloud and edge video analytics.
• 𝐂𝐨𝐧𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧𝐬:
• Improved and maintained the video analytics C++ SDK.
• Developed a natural language-based smart search product for CCTV grids.
• Optimized deep learning modules with multithreading and model sharing.
• Integrated video analytics with vector databases and pub/sub architectures.
• Developed a Yocto layer for cross-compilation of the video analytics SDK.
• Led proof-of-concept development for the ONVIF Profile-M metadata feature and represented the organization in the ONVIF semantic metadata working group.
• 𝐊𝐞𝐲 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬:
• C++, Python, Transformers, Vector Databases, Pub/Sub Architectures, ONVIF, Multithreading, AWS, Yocto

Aug 2022 – Mar 2023 · 7 mos · Victoria, Australia

Aug 2022 – Feb 2023 · 6 mos · Victoria, Australia

• As the AI/DS Tech Lead for Gopher Industries during my capstone project at Deakin University, I led the development of an innovative application - PainRate; to monitor pain levels in non-verbal patients using facial images. My role involved designing the backend architecture, developing REST endpoints, and integrating these into a comprehensive application.
• 𝐂𝐨𝐧𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧𝐬:
• Led the development of an application for monitoring pain levels.
• Designed and developed the backend architecture and REST endpoints.
• Person of contact for all AI and backend development stories.
• 𝐊𝐞𝐲 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬:
• Flask, Python, GCP

Aug 2021 – May 2022 · 9 mos · Gurugram, Haryana, India

• At Mercer Mettl, I enhanced AI-driven features, significantly improving system accuracy and user experience. I developed a real-time proctor assistance pipeline using audio-visual data, optimized inference by migrating AI modules to the browser, and led the development of various AI pipelines for online proctoring and user monitoring.
• 𝐂𝐨𝐧𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧𝐬:
• Improved system accuracy and reduced processing time.
• Developed real-time proctor assistance and user monitoring pipelines.
• Enhanced facial landmarks and detection accuracy.
• 𝐊𝐞𝐲 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬:
• Python, MediaPipe, SpeechBrain, Browser-based AI

Oct 2019 – Aug 2021 · 1 yr 10 mos

• In my role at iOmniscient, I developed advanced C++ solutions for deep-learning-based face recognition and other computer vision applications. My contributions included creating lightweight APIs for object detection and classification, debugging Intel RealSense 3D cameras, and implementing model encryption to safeguard proprietary software.
• 𝐂𝐨𝐧𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧𝐬:
• Developed C++ solutions for face recognition and object detection.
• Created and optimized APIs for various computer vision tasks.
• Implemented model encryption and managed C++/C# interoperability.
• 𝐊𝐞𝐲 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬:
• C++, C#, Python, OpenCV, DLStreamer, Visual Studio, Entity Framework

Mar 2019 – Sep 2020 · 1 yr 6 mos · Rajasthan, India

• As a co-founder of Virescent Technologies, I spearheaded initiatives to solve and monitor air pollution. I partnered with the Rajasthan Traffic Police to launch the state’s first pollution removal tower and handled the entire IT infrastructure of the organization. My responsibilities included setting up real-time air pollution monitoring systems, designing and managing the company’s website, and mentoring a team of interns in IoT and web development tasks.
• 𝐂𝐨𝐧𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧𝐬:
• Co-founded and led a for-profit organization focused on air pollution solutions.
• Partnered with the Rajasthan Traffic Police to launch a pollution removal tower.
• Managed IT infrastructure and real-time air pollution monitoring systems.
• Designed the company website and set up an e-store with payment gateway integration.
• Mentored a team of interns in IoT and web design tasks.
• 𝐊𝐞𝐲 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬:
• IoT, Cron jobs, Razorpay API, Web Development

Jul 2018 – Oct 2019 · 1 yr 3 mos · Noida Area, India

• At Vehant Technologies, I developed essential C++ APIs for vehicle manufacturer recognition and general-purpose classification and detection. I also optimized deep learning models and created detection algorithms using traditional computer vision techniques.
• 𝐂𝐨𝐧𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧𝐬:
• Developed and optimized C++ APIs for recognition systems.
• Designed detection algorithms using traditional computer vision techniques.
• 𝐊𝐞𝐲 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬:
• C++, Linux, OpenCV, CAFFE, OpenVINO

Jan 2018 – Jun 2018 · 5 mos · Noida Area, India

Jul 2017 – Jul 2017 · 0 mo · Singapore

• During my time as a Summer Exchange Student at Ngee Ann Polytechnic, I focused on developing real-time image processing solutions. This program provided me with hands-on experience in object recognition and traditional computer vision techniques, enhancing my skills in C++ and DSP boards.
• 𝐂𝐨𝐧𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧𝐬:
• Developed an object recognition framework using chain codes and shape correlation.
• Worked on real-time image processing on a DSP board in C++.
• Implemented traditional computer vision functions and background subtraction from scratch.
• 𝐊𝐞𝐲 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬:
• C++, DSP, Computer Vision

Jun 2017 – Jul 2017 · 1 mo · Ahmedabad, Gujarat, India

• As a Computer Vision Intern at ProfiledSkin, I developed frameworks for image segmentation and object localization. This role allowed me to apply my knowledge of color spaces and build tools for image annotation and modification.
• 𝐂𝐨𝐧𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧𝐬:
• Developed a framework for image segmentation and object localization using color spaces.
• Built a tool for image annotation and modification.
• 𝐊𝐞𝐲 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬:
• Python, OpenCV, Image Processing

May 2016 – Jul 2016 · 2 mos · Varanasi, Uttar Pradesh, India

• As a Summer Research Intern at IIT BHU, I designed a neural network to detect compound faults in roller bearings using acoustic signal data. This experience deepened my understanding of machine learning and signal processing.
• 𝐂𝐨𝐧𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧𝐬:
• Designed a neural network to detect compound faults in roller bearings with acoustic signal data.
• Conducted a literature survey on deep learning techniques for signal processing.
• Learned fundamentals of machine learning and deep learning.
• 𝐊𝐞𝐲 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬:
• Python, Neural Networks, Signal Processing