AI Research Engineer & Electrical Engineer
Ahtisham
Saleem
Building intelligent systems at the intersection of hardware and machine learning — from brain-computer interfaces to cloud-deployed AI.
Expertise
Building intelligent systems at the intersection of hardware and machine learning — from brain-computer interfaces to cloud-deployed AI.
15 university and research projects spanning ML, digital systems, control, RF, and networking.
Classifies 7 Pakistani rice varieties using 49 handcrafted features and XGBoost, deployed on Namal HPC Cloud via Streamlit.
32-bit, 5-stage pipelined RISC-V processor in Verilog with forwarding and hazard detection.
Closed-loop PID in Simulink for straight-line driving with encoder feedback.
Psychophysics experiments + SVM, MLP, CNN for synthetic media detection.
Rogers 5880, –19.57 dB return loss in Ansys HFSS.
Automatic noise detection and adaptive filtering in MATLAB across 5 noise types.
MATLAB GUI for dark region enhancement with gamma correction and masking.
Complete SSB transmitter/receiver in GNU Radio using Hilbert transform.
VLSM subnetting with 5 routers from a single Class C block in Packet Tracer.
LDR + BJT automated lighting with AC-to-DC supply. Proteus + hardware.
12V to 48V IRFZ44N at 75% duty cycle. Verified in Proteus.
Bare-metal AVR on ATmega328P with L293D and HC-SR04.
Hardware ICs on trainer board + Verilog/ModelSim simulation. 8 operations.
Role-based Python system with CSV persistence and authentication.
Console-based C++ with OOP, file handling, and persistent storage.
Positions of responsibility that shaped my ability to lead, communicate, and serve.
Competitions won, talks delivered, and communities served.
I am Ahtisham Saleem, a graduate Electrical Engineer from Namal University, Mianwali (BS EE, 2021–2025), currently working as an AI Research Engineer at E-Intel, LCE (LUMS) — a deep-tech startup building Brain-Computer Interface systems.
My work involves designing ML pipelines for biosignal classification (EEG/EMG), writing Python for hardware–software integration, and automating workflows from data collection through model validation.
Over four years, I completed 15 technical projects spanning machine learning, computer architecture, control systems, image processing, RF engineering, and networking. I held leadership positions in two societies, delivered a TEDx talk, and volunteered as a community tutor for 2+ years.
I am currently exploring real-time ML inference on embedded devices, brain and biosignal decoding for BCI, and Cloud–Edge hybrid AI architectures.
Whether it's a collaboration, research discussion, or opportunity — I'd love to hear from you.
"Merging hardware and intelligence — building systems that think, sense, and adapt."