Backend & DevOps Lead @ Medical Toxicology · M.Sc. Artificial Intelligence Student

Sajjad Fani

Software Engineer & M.Sc. Artificial Intelligence Researcher

Clinical AI · Reliable & Robust LLMs · AI-Enabled Software Systems

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Academic CV Professional Resume

4+Years Experience

M.Sc.Artificial Intelligence

12+Projects

TA ×3Teaching Roles

Selected Work

Featured Projects

Production systems, research prototypes, and engineering case studies.

All Projects

Professional

Completed

MedSpeech

An AI-enabled medical speech processing platform for clinical toxicology: a Django/DRF backend service that took a recorded or typed consultation and carried it all the way to a finalized note — transcription, extracted clinical facts, AI analysis, treatment guidance, and safety alerts, with an audit trail and version history behind every step. Retired in 2026 once its implementation was ported into ToxLumen as the clinical case domain.

PythonDjangoDjango REST FrameworkPostgreSQL+13

Professional

Ongoing

ToxLumen

A case-first clinical toxicology intelligence platform built solo end to end: three applications, one unified Django backend, and an organization-scoped credit and billing model. Clinicians move from raw input — typed, recorded, or a live transcribed call — through AI-assisted analysis, guidance, and safety alerts to a finalized clinical note. AI assists; the clinician decides.

PythonDjangoDjango REST FrameworkPostgreSQL+21

Academic

Completed

FaceCheckIn

An IoT-enabled attendance and affect-logging system: a Raspberry Pi, backend, and mobile system combining identity recognition, image-based inference, secure APIs, PostgreSQL, and containerized deployment. Top-rated project (full marks) in the Fundamentals of IoT course.

PythonDjangoDjango REST FrameworkRedis+13

Academic Direction

Research Interests

Areas I am actively exploring and hope to contribute to through graduate study.

Full Overview

Clinical AI & Decision Support

AI systems that support or evaluate clinical decision-making, with an emphasis on safety, validity, and clinically meaningful behavior.

Reliable & Robust Large Language Models

Evaluation of LLM reliability, robustness, decision-boundary behavior, counterfactual sensitivity, and safe use of tool-augmented language models.

AI-Enabled Software Systems

Design and engineering of production software systems that integrate machine learning and generative AI into real-world workflows.

Distributed Systems, MLOps & Cloud Infrastructure

Reliable backend, distributed, and deployment infrastructure for AI applications, including reproducibility, asynchronous processing, containerization, and production ML systems.

Current Research · M.Sc. Thesis · Artificial IntelligenceDecision-Boundary Robustness in Tool-Using Clinical LLMs: A Counterfactual Benchmark in Clinical Toxicology

Let's Connect

Open to engineering roles and research collaborations

Whether you're building a distributed system, exploring AI applications, or looking for a graduate school collaborator — I'd like to hear from you.

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