FYP Supervision
Explore open COMSATS final-year project topics alongside completed student projects supervised under Dr Junaid Akram's SCSA Laboratory.
Supervision Directory
Explore running research projects, completed student capstones, and future MS/PhD research topics led by Dr. Junaid Akram at SCSA Lab.
A supervised final-year engineering development project combining a full-stack freelancing marketplace with AI decision assistance and blockchain payment escrow.
A running research project leveraging Large Language Models (LLMs) to detect complex software vulnerabilities in source code through fine-tuning and AST-based prompt engineering.
A running software security project building a scalable token-based semantic code clone detection platform to capture Type-3 and Type-4 clones across large open-source repositories.
A running research project developing an automated patch optimization engine powered by LLMs that synthesizes and verifies security patch suggestions for vulnerable code snippets.
An intelligent code smell detection tool targeting Feature Envy through AST structural analysis, Graph Neural Networks, and automated refactoring recommendations with interactive visual analytics.
A multi-modal web-based AI screening platform combining vision analytics, behavioral questionnaires, and machine learning models for early screening of autism spectrum and psychological disorders.
Future / MS research thesis evaluating search-based evolutionary algorithms to synthesize test vectors and test paths automatically from complex UML state machine and sequence models.
Future / MS research thesis investigating multi-step LLM prompting and retrieval-augmented patch generation to recommend verified security fixes for complex source code vulnerabilities.
Future / MS research topic exploring in-context learning, few-shot prompting strategies, and domain adapter tuning for software vulnerability detection across multi-language code bases.
Future / MS research thesis modeling code program dependence graphs (PDG) and abstract syntax trees (AST) into Graph Neural Networks to automate Feature Envy detection and method relocation refactoring.
Future / MS research thesis building structural AST and Control Flow Graph (CFG) representations to enhance LLM code summarization and documentation generation accuracy.
Future / MS research thesis developing static analysis algorithms to identify test smells in Behavior-Driven Development (BDD) Cucumber/Gherkin feature files and recommend refactoring steps.
Future / MS research thesis formulating semantic embeddings and LLM representations to detect deep Type-4 (syntactically different but semantically identical) code clones.
Completed supervised project implementing static disassembly analysis, APK opcode feature vectors, and ensemble machine learning classifiers for resilient Android malware detection.
Completed biomedical machine learning project deploying deep convolutional neural networks to classify blood cell microscopic images and detect diagnostic anomalies automatically.
Completed web security capstone project delivering an automated Cross-Site Scripting (XSS) static code auditor and dynamic browser defense extension.
Completed sports analytics platform combining computer vision for ball-tracking, player biomechanics assessment, and statistical match prediction.
Completed biomedical signal processing system utilizing audio sensor processing and machine learning to detect nocturnal sleep apnea events in real time.
Completed software vulnerability management platform aggregating CVE repositories, automated severity scoring, and code vulnerability tracking across enterprise projects.
Completed static code analysis suite detecting structural code smells (God Class, Long Method, Feature Envy) and generating safe automated refactoring patches.
Completed research project capturing hierarchical Abstract Syntax Tree and Control Flow Graph structures to recommend software architectural improvements.
Completed computer vision healthcare system utilizing deep convolutional networks for automated skin lesion segmentation and dermatological risk classification.
Supervised student project implementing machine learning algorithms to detect synthetic financial fraud signals generated by the PaySim simulator.
Static and dynamic security analysis project auditing OpenSSL memory safety vulnerabilities and buffer overflow defenses.
Malware analysis project extracting assembly opcode instruction frequency patterns to classify binary malware variants.
Supervised research evaluating feature selection techniques for automated malware detection across PE executable headers.
Cryptographic analysis project evaluating fast correlation attack algorithms against linear feedback shift registers (LFSR).
Mobile software engineering project building a user-centered Android application for medication reminders and emergency alerts.
Future research topic extracting vulnerable code fragments from patch files to build a reusable benchmark for vulnerability research.
Future research topic analyzing code clone and dependency propagation ratios across related software systems.
Future research topic developing a tool that propagates approved vulnerability patches to matching code clones across repositories.
Placement outcomes
Ernst & Young Advisory Services Sdn. Bhd.
Maxwell Cloud Technology Sdn. Bhd.
China ASEAN Information Harbor
Beijing Megvii Corporation, Ltd.
Returnstar Interactive Technology
Zoho Technology Co., Hangzhou
Meiya Pico, Xiamen Software Park
How to apply
BS Software Engineering and BS Computer Science students interested in FYP supervision at COMSATS University Islamabad, Lahore Campus should email Dr Junaid Akram with the following details:
