CV

Objective

Skilled R&D expert in Computer Vision and eXplainable AI (XAI) specializing in Precise object localization using eXplainable AI and Visual Anomaly Detection. My previous work spans object detection, video surveillance, and computer vision aided medical imaging disease recognition

Work experience

• Jan 2025 - ~Aug 2025: Visiting PhD Researcher - @Valeria-Lab

  • Valeria-Lab, Dept. of Computer Engineering, Automation and Robotics Department, University of Granada, Spain
  • Duties_: generation of synthetic data for a use case of EU project DistriMuSe
  • Supervisor: _Jesús Garrido_
  • Contributions: Contributing in European industrial projects DistriMuSe where my role is to improve, develop and utilize the eXplainable AI (XAI) algorithms to add transparency and trust in the complex AI Models.

• Nov 2022 - ~Nov 2025: Doctoral Researcher on Industrial Needs @ Dept. of Computer Science, University of Turin, Italy

  • Institute: Dept. of Computer Science, University of Turin, Italy
  • Duties: : Automatic extraction of high-level semantic features, Object Localization, Anomaly Detection and Visual explanations for Anomalies
  • Contributions: Contributing in European industrial projects DistriMuSe & DistriMuSe details on UniTo Portal and NextPerception where my role is to improve, develop and utilize the eXplainable AI (XAI) algorithms to add transparency and trust in the complex AI Models.
  • Supervisor: Elvio Gilberto Amparore

• November 2022: PhD Student (Research & Development) @Rulex Innovation Labs

  • Institute: Rulex Innovation Labs, Genova, Italy.
  • Duties: eXplainable AI, XAI, Computer Vision, Trustworthy AI, Trustworthy ML
  • Supervisor: Enrico Ferrari, Damiano Verda

Education

a. PhD(CS):

Details about PhD work:

• Title, & Type: Industrial PhD funded by PNRR-CINECA Italy for European Projects
• University & Industry: University of Turin, Rulex Innovation Labs, _Italy_
• Duration: Oct 2022 - ~ Dec 2025
• Objectives: Automatic extraction of high-level semantic features, Object Localization, Anomaly Detection and Visual explanations for Anomalies.
• Training Activities & Courses: Check Courses Details Here and other Training Activities Here.
• Keywords: eXplainable AI, XAI, Computer Vision, Trustworthy AI, Trustworthy ML
• Image Datasets Used: ImageNet, ImageNet-S, MVTec, MS-COCO, Robotics.

Proudly Supervised by

• Academic: Elvio Gilberto Amparore , Dept. of Computer Science, University of Turin, Italy.
• Industrial: Enrico Ferrari, HEAD OF R&D PROJECTS, Rulex Innovation Labs, Italy.
• Industrial: Damiano Verda, HEAD OF DATA SCIENCE, Rulex Innovation Labs, Italy.

Contributions to European Project:

• DistriMuSe Website: My task here is to implement Anomaly Detection(AD) in robotics use case for human safety, read more details here at DistriMuSe Website.

Achievements:

Acheivements in this study are the following Publications made and also available at UniTo portal.

Sr. No.	Title	Journal / Conference	Dates	Location	Publication Date	LINKS
1.	Anonumous Submission.	A+ Ranked Conference	-	-	Under Review	Codes
2.	Can I trust my anomaly detection system? A case study.	XAI-World ( World Conference on eXplainable Artificial Intelligence)	17-19 July 2024	Valletta, Malta	10 July 2024	Paper PDF Link -:- Codes -:- Medium Blog
3.	Using Stratified Sampling to Improve LIME Image Explanations.	AAAI-24 (38th Annual AAAI Conference on Artificial Intelligence)	22-27 feb 2024	Vancouver, Canada.	24-03-2024	Paper PDF Link -:- Stratified LIME -:- Examples -:- Medium Blog

b. Master Degree

Degree Details:

• Title & Duration: Master of Science (Computer Vision and Graphics), 2017-2019
• Courses Taken: Here is the summary of Courses and other Training Activities.
• Dataset Used: Caltech-101, Caltech-256, PascalVOC-3D, Flower, Butterfly
• Keywords: Object Detection, Object Localization, Computer Vision, Deep Learning, Feature Engineering, Feature Selection and Optimization.

Achievements:

Sr. No.	Type	Title	Journal	PDF Link	Codes
1.	Research Thesis	Object Detection and Classification based on Feature Fusion and Deep Convolutional Networks.	—	—	GitHub Repo
2.	Published Research Article	A sustainable deep learning framework for object recognition using multi-layers deep features fusion and selection.	Sustainability	PDF Link	GitHub Repo, Mathworks
3.	Published Research Article	Object Detection and Classification: A Joint Selection and Fusion Strategy of Deep Convolutional Neural Network and SIFT Point Features.	Multimedia Tools and Applications	PDF Link	GitHub Repo , Mathworks

NOTE: Few of the research activities/publications were outcome of collaboration work with other members of the research group. See

c. Bachelor Degree

Bachelor of Science (Computer Science - Web Development)

Degree Details:

• Title: Bachelor of Science (Computer Science - Web Development) (2016)
• Keywords: Software Engineering, Web development, Web Applications, Web Security, Information Security.

Achievements:

Sr. No.	Title
Product	Developed A secure Web Application using MVC architecture and CodeIgnitor Framework
Name	OVBTP, A Secure AI based Web Application for Venue Booking and Tour Planning
Website	http://www.ovbtp.com
CODES	GITHUB - -
Tools Used	MVC, MS-SQL, CodeIgnitor, PhP, Javascript, HTML, CSS

Publications

Using Stratified Sampling to Improve LIME Image Explanations

Rashid,Muhammad et al. (2024). "." Proceedings of the AAAI Conference on Artificial Intelligence. 38(13).

A novel light u-net model for left ventricle segmentation using MRI

Rashid,Muhammad et al. (2024). "." In Mathematics 11, no. 14 (2023): 3245..

Region-based active contour JSEG fusion technique for skin lesion segmentation from dermoscopic images

Rashid,Muhammad et al. (2019). "." In Biomedical Research.

Deep CNN and geometric features-based gastrointestinal tract diseases detection and classification from wireless capsule endoscopy images

Rashid,Muhammad et al. (2019). "." In Journal of Experimental & Theoretical Artificial Intelligence .

An Optimized Approach for Breast Cancer Classification for Histopathological Images Based on Hybrid Feature Set

Rashid,Muhammad et al. (2021). "." In Current Medical Imaging..

An integrated framework of skin lesion detection and recognition through saliency method and optimal deep neural network features selection

Rashid,Muhammad et al. (2020). "." In Neural Computing and Applications .

A sustainable deep learning framework for object recognition using multi-layers deep features fusion and selection

Rashid,Muhammad et al. (2024). "." In Sustainability.

Classification of gastrointestinal diseases of stomach from WCE using improved saliency-based method and discriminant features selection

Rashid,Muhammad et al. (2024). "." In Multimedia Tools and Applications .

Object Detection and Classification: A Joint Selection and Fusion Strategy of Deep Convolutional Neural Network and SIFT Point Features

Rashid,Muhammad et al. (2024). "." In Multimedia Tools and Applications.

Can I trust my anomaly detection system? A case study based on explainable AI

Rashid,Muhammad et al. (2024). "." In World Conference on Explainable Artificial Intelligence, pp. 243-254. Cham: Springer Nature Switzerland, 2024.

Talks

Can I trust my anomaly detection system? A case study based on explainable AI

July 17, 2024

Talk at Mediterranean Conference Centre, La Valletta, Malta

Using Stratified Sampling to Improve LIME Image Explanations

February 21, 2024

Talk at Vancouver Convention Centre, Vancouver, Canada

Skills

• Technical Skills
  • Machine Learning
  • Computer Vision
  • Deep Learning (TensorFlow, PyTorch)
  • Anomaly detection
  • Generative AI
  • GitHub
  • Basics of Graphic Designing
  • Web development
• Programming Languages
  • Python
  • Matlab
  • C/C++
  • Basics of Visual Bsaic, C#, and Java

Languages

Awards

Certifications

a. Certificates of Conferences:

b. Certificates of Courses:

c. Certificates of Workshops/Seminars/Journals: