ASHOK
Deep learning · Data Analysis · Computer vision
B.Tech — Artificial Intelligence and Data Science
Kumaraguru College of Technology · Coimbatore, Tamil Nadu · 2023 – 2027 · Present
Education
SRFP Research Intern
IIT Gandhinagar · May 2025 – July 2025
Internship
- Implemented an image enhancement system on Zynq UltraScale+ FPGAs via Vitis-AI.
- Deployed a 10K-parameter custom finetuned ZeroDCE++ model for real-time inference.
- Replaced unsupported operators to avoid CPU fallback and reduced complexity by 87.5%.
NanoDCE
Knowledge distillation compressing ZeroDCE++ down to a tiny model while preserving
low-light enhancement quality.
PyTorchComputer VisionKnowledge
Distillation
Satellite Visual Search
Few-shot Siamese + ResNet pipeline to detect objects in satellite imagery with
minimal examples.
PyTorchResNet50Siamese
Networks
CHB-MIT EEG Analysis
Exploratory analysis comparing seizure vs non-seizure signals with preprocessing
and statistics.
PythonEDASignals
FPGA ZeroDCE++
Deployed and optimized an image enhancement pipeline on DPU architecture of Zynq
UltraScale+ zcu104 board via Vitis-AI Framework.
FPGAVitis-AIEdge AI
MuViz
Music visualizer with Milkdrop and spectrum modes, queue playback, and synced
karaoke-style lyrics.
DjangoJavaScriptWeb Audio
244 / 3357
Kaggle — Santa 2025
Bronze medal. Ranked 244th out of 3,357 teams in the Santa 2025 competition on
Kaggle.
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1st
Design Competition — Taylor's University
First place in the design competition conducted at Taylor's University, Malaysia.
MADE program 1st edition.
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29 / 4206
Kaggle — Diabetes Prediction 2025
Placed 29th out of 4,206 teams on the Kaggle Diabetes Prediction Challenge, 2025
edition.
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Languages
Python, C++, SQL, R
Tools
Git, Docker, GitHub, PowerBI, AWS, Supabase, Vercel
Libraries
Pandas, NumPy, Matplotlib, PyTorch, OpenCV, Scikit-learn, Seaborn
Focus
Optimization, deployment, real-time inference, data analysis