Senior Software Engineer & Tech Lead
Antardip Himel
CSE (University of Toledo)
Antardip Himel is a Senior Software Engineer & Tech Lead at HaorGrix, specializing in machine learning, computer vision, and scientific image analysis. He is a Computer Science and Engineering student at the University of Toledo, recognized on the Dean's List and President's List, and a research assistant at The Ray Research Laboratory building reproducible ML pipelines for large-scale microscopy datasets. He authored OncoLens, a cancer-cell classification desktop application whose ResNet+LSTM model reached 96.58% test accuracy (AUC 0.988), and has published deep-learning microscopy research at SPIE 2026 and APS 2025. His award record includes the NASA Space Apps Galactic Problem Solver Award and competitive University of Toledo research scholarships.
Experience
Senior Software Engineer & Tech Lead
HaorGrix
- —Leads engineering delivery across machine learning and full-stack product work.
Research Assistant — Image Analysis and Machine Learning
August 2024 – PresentThe Ray Research Laboratory
- —Curates large-scale microscopy datasets and builds data ingestion and preprocessing pipelines with reproducible splits and evaluation (precision/recall, ROC, calibration).
- —Trains and tunes perception models (detection, classification, segmentation) and applies clustering (k-means, DBSCAN) to clean labels, delivering 95%+ accuracy on benchmarked tasks.
Automotive Software Engineering Intern
May 2024 – August 2024Talascend
- —Validated newly flashed automotive modules, created defect logs, and supported test-bench setup and data capture.
- —Partnered with engineers to reproduce issues and tighten release checks, improving reliability and deployment speed.
Teaching Assistant
January 2023 – April 2024University of Toledo — College of Engineering
- —Facilitated lab sessions for 200 students in programming tools, signal analysis, and version control.
- —Mentored students on debugging strategies and software development best practices.
Publications & Research
- ◦Deep Learning–Based Screening of Sperm Centriole Integrity Using Multimodal Optical Microscopy — SPIE 2026
- ◦Automated Image Analysis for Multimodal Optical Microscopy — APS 2025