Faheem Zafari      

alt text 

[google scholar]
faheem16@imperial.ac.uk
Research Interests: Resource allocation in Wireles Networks, Distributed Optimization, Internet of Things, LTE/LTE-A, 5G
Smart Architectures, Indoor localization
Ph.D. Candidate: Department of Electrical and Electronics Engineering
Imperial College, London, UK

Detailed Resume (last updated: September. 2018) (pdf)

CV (last updated: November. 2018) (pdf)

I joined Imperial College London in September’ 16 as a Ph.D. student in the Department of Electrical and Electronics Engineering at Imperial College London, working under the supervision of Professor Kin K. Leung. I am also mentored by Dr. Athanasios (Thanos) Gkelias. Furthermore, I work in close collaboration with Professor Don Towsley of University of Massachussetts Amherst and Ananthram Swami, Paul Yu of Army Research Lab, USA.
During my master's at Purdue University, I worked with Ioannis Papapanagiotou and Baijian Yang on Indoor Localization using iBeacons for Internet of Things and Smart Buildings. iBeacons are Bluetooth Low Energy Enabled devices that are intended to provide proximity-based services to IoT equipped smart buildings. My research revolved around improving their accuracy not only for proximity-based services but also utilized them for indoor localization.
Prior to joining Purdue University, I completed my Bachelor's degree in Electrical Engineering at University of Engineering and Technology (UET) Peshawar, Peshawar, Pakistan. I worked with Dr. Muhammad Inayatullah Khan Babar on traffic shaping in computer networks.

Research

  • Indoor Localization

  • Distributed Optimization

  • Internet of Things (IoT)

  • Game Theory

  • Wireless/Cellular Networks

  • Smart Grids

  • Intelligent Transportation Systems (ITS)

Education

  • Doctor of Philosophy, Electrical and Electronics Engineering, 2016-
    Imperial College, London. UK
  • Master of Science, Computer and Information Technology, 2014-2016

    Purdue University, West Lafayette. USA

  • Bachelor of Science, Electrical Engineering, 2008-2013
    University of Engineering and Technology (UET) Peshawar, Peshawar Pakistan.
    Graduated: June 2013

  • Non-Degree Exchange Student, Electrical Engineering, Fall 2011
    University of Idaho, Moscow. USA

    • Funded By: US Department of State

    • GPA: 3.53/4.0

    • Selected Publications

    • Nitish K. Panigrahy, Jian Li, Faheem Zafari, Don Towsley, Paul Yu, “ Jointly Compressing and Caching Data in Wireless Sensor Networks ” (Accepted for publication in IEEE Smartcomp 2019) (pdf)

    • Faheem Zafari, Kin K. Leung, Don Towsley, Prithwish Basu, Ananthram Swami, “ A Game-Theoretic Framework for Resource Sharing in Clouds ” (Available online on arXiv and accepted for publication in IFIP WMNC 2019) (pdf)

    • Faheem Zafari, Jian Li, Kin K Leung, Don Towsley, Ananthram Swami, “ Optimal Energy Consumption for Communication, Computation, Caching and Quality Guarantee ” (Accepted for publication in IEEE Transactions on Control of Network Systems)

    • Faheem Zafari, Jian Li, Kin K Leung, Don Towsley, Ananthram Swami, “A Game-Theoretic Approach to Multi-Objective Resource Sharing and Allocation in Mobile Edge” ACM Mobicom workshop on Technologies for the Wireless Edge, New Delhi, India, 02-02 November, 2018 (pdf)

    • Jian Li, Faheem Zafari (primary co-author), Don Towsley, Kin K Leung, Ananthram Swami, “Joint Data Compression and Caching: Approaching Optimality with Guarantees” 9th ACM/SPEC International Conference on Performance Engineering, Berlin, Germany, 09-13 April, 2018 (pdf)

    • Faheem Zafari, Ioannis Papapanagiotou, Thomas J. Hacker, “A novel Bayesian filtering based algorithm for RSSI-based indoor localization” IEEE Conference on Communications (ICC) 2018 (pdf)

    • Faheem Zafari, Jian Li, Kin K Leung, Don Towsley, Ananthram Swami, “Optimal Energy Trade Off among Communication, Computation and Caching with QoI-Guarantee” (Available online on arXiv) (pdf)

    • Faheem Zafari, Jian Li, Kin K Leung, Don Towsley, Ananthram Swami, “E3C3: Enhancing Energy Efficiency among Communication, Computation and Caching with QoI-Guarantee” (Accepted as a long paper in the Annual Fall Meeting of DAIS-ITA 2017), London, UK (pdf)

    • Nitish Panigrahy, Jian Li, Faheem Zafari, Don Towsley, Paul Yu, “What, When and Where to Cache: A Unified Optimization Approach” (Available online on arXiv) (pdf)

    • Faheem Zafari, Athanasios Gkelias, and Kin Leung, “A Survey of Indoor Localization Systems and Technologies” Accepted for publication in IEEE Communication Surveys & Tutorials (Available online on arXiv) (pdf)

    • Faheem Zafari, Ioannis Papapanagiotou, Michael Devetsikiotis and Thomas J. Hacker, “An iBeacon based Proximity and Indoor Localization System” (Available online on arXiv) (pdf)

    • Faheem Zafari, Ioannis Papapanagiotou, Michael Devetsikiotis and Thomas J. Hacker, “Enhancing the Accuracy of iBeacons for Indoor Proximity-based Services” IEEE Conference on Communications (ICC) 2017 (pdf)

    • Saurav Nanda, Faheem Zafari, Casimer Decusatis, Eric Wedaa and Baijian Yang, “Predicting Network Attack Patterns in SDN using Machine Learning” IEEE Conference on Network Function Virtualization and Software Defined Networks 2016 (pdf)[slides]

    • Faheem Zafari, Ioannis Papapanagiotou, and Konstantinos Christidis, “Micro-location for Internet of Things equipped Smart Buildings”, IEEE Internet of Things Journal (Impact factor: 7.596), 3(1), 96-112, June, 2015 (pdf)

    • Faheem Zafari, and Ioannis Papapanagiotou, “Enhancing iBeacon based Micro-Location with Particle Filtering”, IEEE Global Communication Conference, Dec 06-10, 2015, San Diego, California (pdf)[slides]

    • Gul Muhammad Khan, Faheem Zafari, “Dynamic Feedback neuro-evolutionary networks for forecasting the highly fluctuating Electrical Loads ” Genetic Programming and Evolvable Machines (Impact factor: 0.9), , 1-18, 2016 (pdf).

    • Faheem Zafari, Gul Muhammad Khan, Mehreen Rahman and Sahibzada Ali Mahmud, “Evolving Recurrent Neural Network using Cartesian Genetic Programming to Predict The Trend in Foreign Currency Exchange Rates,” Applied Artificial Intelligence (Impact factor:0.53), 28(6), 597-628, 2014 (pdf)

    • Gul Muhammad Khan, Faheem Zafari, and Sahibzada Ali Mahmud, “ Very Short Term Load Forecasting using Cartesian Genetic Programming evolved Recurrent Neural Networks (CGPRNN),” 2013 12th International Conference on Machine Learning and Applications (ICMLA), 2, 152-155, Miami, Florida, December 2013 (pdf)

    • Jawad Ali, Faheem Zafari, Gul Muhammad Khan, and Sahibzada Ali Mahmud, “Future Client’s Requests Estimation for Dynamic Resource Allocation in Cloud Data Center using CGPANN,” 2013 12th International Conference on Machine Learning and Applications (ICMLA), 2, 331-334, Miamia, Florida, December 2013 (pdf)

    • Faheem Zafari, Sahibzada Ali Mahmud, Gul Muhammad Khan, Mehreen Rahman, and Haseeb Zafar, “A Survey of Intelligent Car Parking System”, Elsevier Journal of Applied Research and Technology (Impact factor: 0.80), 2013 (pdf)

    • Faheem, Fahd Humayoun, Muhammad Inayatullah Babar, Haseeb Zafar, and MF Zuhairi “Performance analysis of a Token Bucket Shaper for MPEG4 video and Real Audio signal,”2013 IEEE International Conference on Smart Instrumentation, Measurement and Applications, 1-4, Kuala Lampur, Malaysia, November, 2013 (pdf)

    • Gul Muhammad Khan, Atif Rashid Khattak, Faheem Zafari, and Sahibzada Ali Mahmud,“Electrical load forecasting using fast learning recurrent neural networks,”2013 International Joint Conference on Neural Networks (IJCNN), 1-6, Dallas, Texas, August, 2013 (pdf)

    Talks/Presentations

    • Faheem Zafari, “ Multi-Objective Optimization”, Talk at University of Massachusetts, Amherst, USA. (pdf)

    • Faheem Zafari, “E3C3: Enhancing Energy Efficiency among Communication, Computation and Caching with QoI-Guarantee ”, Presentation at DAIS-ITA Annual Fall Meeting (AFM) September 2017, London, UK. (pdf)

    • Faheem Zafari, “E3C3: Enhancing Energy Efficiency among Communication, Computation and Caching with QoI-Guarantee ”, Talk at IBJ T.J Watson Center, August 2017, Yorktown Heights, New York, USA. (pdf)

    • Faheem Zafari, and Kin K. Leung, “Optimizing the computation and communication energy costs of Wireless Sensor Networks ”, Presentation at IBM BootCamp for International Technology Alliance (ITA) consortium, IBM, 2017. (pdf)

    • Faheem Zafari, “Indoor Localization for Internet of Things and Smart Entities ”, Presentation at Center for Education and Research in Information Assurance and Security, Purdue University, 2015. (pdf)

    • Faheem Zafari, “Internet of Things, Smart Buildings and Indoor Localization”, Presentation to TECSUP students from Peru, Purdue University, 2014. (pdf)

    Research Experience:

    • Distributed Systems Optimization     – Fall 2016 to Present

      • Adviser: Prof. Kin K Leung

    • IEEE Try-Cyber Security Initiative (Try-CybSI)     – Fall 2015 to Spring 2016

      • Adviser: Prof. Baijian Yang

      • The project intended to develop tools for assisting programmers to understand the importance of security.

    • Internet of Things, Smart Buildings and Indoor Localization     – Fall 2014 to Spring 2016

      • Adviser: Dr. Ioannis Papapanagiotou

      • This project was based on utilization of iBeacons for indoor localization and how it can be leveraged for Internet of Things equipped Smart Buildings

    • Location based appliance control     – Spring 2014 to Summer 2014

      • Adviser: Dr. Ioannis Papapanagiotou

      • During this project, we developed an iBeacon based fully automatic appliance control. The devices could turn on and off based on the user's location and proximity to the appliance.

    • Micro-Controller Based Solving Robot     – Spring 2011 to Spring 2011

      • Adviser: Dr. Gul Muhammad Khan

      • During the semester project, my team and I developed maze solving robot that could solve a particular maze using AT89C51 microcontroller.

    • Performance Analysis of a Token Bucket Shaper     – Fall 2011 to Spring 2012

      • Adviser: Dr. Mohammad Inayatullah Khan Babar

      • In this project, we analyzed the performance of a token bucket shaper using real world traffic including video and audio signals. The simulation study was carried out using Network Simulator-2 and and results of the project were published in IEEE ICSIMA 2013.

    Work Experience

    • Research Assistant - Purdue University     – Spring 2015 to Spring 2016

      • Projects: a) Beacon-based indoor localization b) IEEE Cyber Security c) Location based appliance control

      • Purdue University, West Lafayette, USA

    • Visiting Research Scholar - North Carolina State University     – Summer 2015

      • Project: iBeacon-based indoor proximity system

      • Hosted by: Dr. Michael Devetsikiotis (Fellow IEEE)

      • North Carolina State University, Raleigh, USA

    • Research Assistant - Koc University     – Fall 2013 to Summer 2014

      • Wireless Network Laboratory, Department of Electrical and Electronics Engineering,

      • Energy Efficiency of Machine to Machine Communication in LTE/LTE-A Networks

      • Koc University, Istanbul, Turkey

    • Undergraduate Researcher: University of Engineering and Technology Peshawar     – Fall 2011 to Spring 2012

      • Project: Performance analysis of a token bucket shaper for different communication streams

      • Peshawar, Pakistan

    Teaching Experience

    • Imperial College London Jan. 2018 - present
      Department of Electrical and Electronics Engineering

      • Study Group Leader for EE1-06 Introduction to Signals and Communications - Spring 2018