Akbar Ali

Selected for an international research program at HZDR, working with the exploration group on computational imaging and AI-driven scientific applications — hyperspectral analysis and 3D reconstruction for geoscience. The visit means operating inside a different institutional culture and set of research conventions from my own.

Working on visual learning and generative representations, with the aim of building interpretable and efficient systems for image restoration and hyperspectral imaging.

Worked on Volume Estimation of Complex Objects Using Hyperspectral Imaging and Stereo Vision Fusion, applying both imaging modalities to measure irregular objects for industrial automation and robotics. My first sustained work at the boundary between sensing hardware and vision algorithms.

Thesis at the intersection of machine learning and medical data analysis, building predictive models for healthcare. It proposed a descriptive predictive framework for Parkinson’s disease analysis, later published by Springer Nature in 2023.

Built an IoT-based home automation system for remote control and monitoring of household devices, using sensor integration and wireless communication. This project is what turned my interest towards machine learning and deep learning.

Led the teaching assistant team for a cohort of 45 students, covering data structures, algorithms, data analysis in Python (Pandas, Matplotlib), SQL and introductory machine learning. Set the QA session format and coordinated grading standards across assistants with the instructor.

Guided 35 students through classwork, assessment and progress tracking, holding individual reviews with students falling behind.

Ran flight training and field sessions for around 30 students on drone data acquisition and processing with RGB and multispectral imagery. Responsible for pre-flight checks, airspace discipline and student safety during live flights.

Ran labs and tutorials for 50+ students across three semesters using the Python data science stack, and supported the Probability and Randomization course.

Supervise B.Tech and M.Tech students on hyperspectral imaging, image editing and GAN inversion projects — scoping the problem, setting milestones, and reviewing code and results through to a working system. Two of these collaborations became co-authored submissions.

A year-long collaboration with geoscientists, translating 3D geophysical scans into photorealistic virtual outcrop geology. Required learning enough field geology to know what a plausible result looks like, and translating that back into a generative formulation.

Designed and ran a six-month acquisition campaign with agricultural researchers, flying weekly missions at 10 m, 15 m and 115 m from July to December 2023 to track weather and pest effects across a full growth cycle. I owned the flight schedule, the multi-altitude protocol and the resulting dataset, which was released as COT-AD.

Planned and led three multi-day campaigns (May 2023, Aug 2024, Nov 2024) for aerial and core sample collection, coordinating logistics, equipment and flight operations with a team from another department. Site names withheld for confidentiality.

Data collection visits to Silvassa and Aurangabad.

Week-long school on deep learning for 3D vision. The Gaussian splatting sessions here shaped the direction my hyperspectral work took afterwards.

Presented my work to an interdisciplinary audience of scholars from across engineering disciplines.

DJI Mavic and Bajrang platforms. Mission planning, pre-flight checks, spectral data capture and aerial inspection.

Three during B.Tech and two during M.Tech.