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Aadil Jaleel C. - Fullstack Developer, Qt Framework, Data Science

Being part of Softaims has allowed me to see the full spectrum of what technology can achieve when guided by empathy, discipline, and creativity. Each assignment, regardless of size, represents an opportunity to bring clarity to complexity and to turn ambitious ideas into tangible outcomes. I’ve come to realize that successful development isn’t just about writing code—it’s about listening carefully, understanding deeply, and designing thoughtfully. Every client brings unique challenges, and I make it a priority to align my work with their goals, ensuring that the end result is both effective and lasting. Softaims fosters an environment where collaboration is not optional—it’s essential. The collective expertise within the team pushes me to think beyond conventional boundaries, to question, refine, and innovate. I believe that this process of shared learning and experimentation is what makes our solutions resilient and impactful. My ultimate goal is to build technology that feels effortless to use yet powerful in function. I approach every task with the mindset that small details can make a big difference. Through continuous refinement and dedication, I aim to contribute to the kind of work that not only serves today’s needs but anticipates tomorrow’s possibilities.

Main technologies

  • Fullstack Developer

    11 years

  • Computer Vision

    6 Years

  • TensorFlow

    4 Years

  • Python

    1 Year

Additional skills

  • Computer Vision
  • TensorFlow
  • Python
  • C++
  • Robot Operating System
  • Image Processing
  • MATLAB
  • Linux
  • Embedded Linux
  • Keras
  • Machine Learning
  • Automotive Engineering
  • TCP/IP
  • DevOps
  • Qt Framework
  • Data Science

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Potentially possible

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Experience Highlights

[AI / LLM / GenAI] Qazi.ai - Llama 3.1 based Legal Case Management

* Legal Document Generation (e.g, Summons, Petitions, Draft Judgement) * Legal Document Analysis (e.g., Arguments, Precedence) * End-to-End Case Management

[AI / Qt ] Nvidia Deepstream AI Pipeline with Qt for Jetson Orin

The goal was to * Training AI Model per user requirements * Optimizing and Deploying the AI Model on Nvidia Jetson Orin * Implement Tracking Algorithm * Picture-in-Picture Replay * Integration of Deepstream with Qt frontend (C++)

[Embedded Linux / Hardware / C++ / FreeRTOS / STM32] Handheld Device

Problem: Require a rich GUI but real-time sensor data acquisition. Solution: A multi-core embedded system running Linux and FreeRTOS simultaneously. Hardware: OSD32MP1-BRK with touchscreen and touch controller directly interfaced. Schematics and PCB Design is covered by NDA. Software: The exact details of the project are subject to an NDA, but the following technologies were used: 1. FreeRTOS running on cortex M4 on Octavo OSD having STM32MP157. The FreeRTOS code handled obtained real time data from a proprietary sensor. The data was then time stamped and sent to the A7 core over IPCC. The whole toolchain was optimized for real-time data communication from sensor to A7 2. Cortex A7 coprocessor ran OpenSTLinux. A GUI application was made using Qt6. 3. Crystalfontz 2.4" LCD (CFAF240320A0-024SC) was integrated directly with OpenSTLinux via SPI and slightly modified linux kernel drivers and device tree. 4. Similarly the touch controller from CFAF240320A0-024SC was integrated with I2C kernel drivers. 5. The proprietary sensor was interfaced using SPI on Cortex-M4. 6. Device tree and kernel customizations were done to optimize OSTLinux for product usecase 7. The Qt Application featured, multiple screens, with charts for sensor data, provision to record data and to display live data 8. The Qt application and also allowed for CSV export of recorded sensor data and backup to PC via USB. 9. Django application was also deployed on A7 for device configuration to download data and upload settings.

[C++ / ROS / Qt] Sensor Data Decoding & Visualization

Automotive Bus Data / Sensor data playback, decoding and visualization * development of playback for mdf4/mf4, dat and rosbag files in C++ * development of data decoding (CAN, CANFD, SomeIP, TAPI with DBC, FIBEX, ARXML databases) lib in C++ * development of data flows in in ROS * development of video data decoder and post processing in CUDA * Visualization of data (video, LIDAR, etc) in RViz

[AI / GPT API] Automatic Comparison of PDF with Audio in Danish

Given an audio sample and a PDF, the goal was to compare them and find any discrepancies. The project was aimed at Danish language. Audio samples were converted to text using Google Speech to Text API, and then corrected for artifacts using GPT4 API. PDF was converted and calibrated using various techniques including GPT4 API. Off-the-shelf Whisper API struggled with Danish but fine-tuning could produce results comparable to Google STT API. Image for Illustration.

Education

  • Georgia Institute of Technology

    Master of Science (MS) in Computer Science - Specialization in Machine Learning

    2018-01-01-2020-01-01

  • NUST School of Electrical Engineering and Computer Science

    Bachelor of Engineering (BEng) in Electrical - Digital Systems and Signal Processing

    2011-01-01-2015-12-01

Languages

  • English
  • Urdu

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