Farheen Asif

Position title: Ph.D. Student

Email: fasif@wisc.edu

Phone: +1 (608) 9600273

3605 Engineering Hall


I received my BS in Electrical Engineering from National University of Sciences and Technology, Pakistan. I worked in Techlogix as Machine Learning Engineer and in RWR as Embedded Software Engineer afterwards. Currently, I am pursuing a PhD in Electrical and Computer Engineering at UW-Madison.


University of Wisconsin–Madison
PhD in Electrical and Computer Engineering
September 2022 – Present

National University of Sciences and Technology University
Bachelor of Science in Electrical Engineering
September 2017 – June 2021

Research Interests

  • Embedded systems
  • Computer Architecture
  • Energy-efficient Computing 


HLS based implementation of epileptic seizure detection on FPGA using DNNs

The project aims to use DNN to detect epileptic seizure from EEG recordings and use XILINX high level synthesis tool kit to implement on FPGA board. Fast inference along with comparable accuracy is the main target. I am working on PyTorch implementation as well as C based streaming layers in network.

Training Aware Quantization of Deep Neural networks

Worked on ResNet, Inception and LeNet architectures, binarization and quantization of weights and activation bits to adjust precision and achieve a suitable trade-off between computational power and accuracy on FPGAs. Used XILINX PYNQ and Zybo board for inference, implemented fixed point arithmetic and streaming of CNNs for hardware platform.

Analyzing data on the COVID-19 pandemic to make predictive algorithms

Worked on diagnosis and prognosis algorithmic models based on clinical and lung ultrasound features of patients. The cohort was divided in to COVID positive for prognosis and complete data for diagnosis. Handled missing data, worked on relevant features selection and elimination and finally prediction with and without resampling

Ultra-fast Machine Learning Inference for triggering at the CMS Experiment

The Large Hadron Collider experiments present an extreme challenge for real time analysis and to decide which events are to be discarded. The goal is to bring boosted decision trees from ML methods in order to make instant decisions about events, keeping in mind the suitability to low power, low resource edge processing and targeting extremely low latency.

Smart Cylinder

A gas cylinder which detects fire/smoke and weighs the cylinder continuously to notify owner through text message using GSM module about cylinder refilling. I used Atmel AVR micro controller and different sensors for the project.


  • Summer Studentship at CERN, the European Organization for Nuclear Research, Switzerland
    June 2021August 2021
  • Summer Fellow at MLO Lab, EPFL, Switzerland
    May 2020Oct 2020

Research Experience

  • Research Assistant at WISEST Lab, UW-Madison
    September 2022 – Present
  • Research Assistant at TU Kaiserslautern Lab-NUST SEECS (NCAI now), NUST, Pakistan
    June 2019 – March 2021

Industry Experience

  • Embedded Design Engineer at RWR, Pakistan
    May 2022August 2022
  • Software Engineer (Machine Learning) at Techlogix, Pakistan
    January 2022May 2022


  • Electrical and Computer Engineering Chancellor’s Opportunity Fellowship (COF), 2022
  • Academic Excellence Award (Gold Medalist), 2017