Artificial Intelligence

Machine Learning, Computer Vision, and Multimedia

Farshid Farhat

  • Email: farshid83 AT gmail, LinkedIn, GSite, GitHub, GitLab
  • Dexterity Inc., AI Roboticist, 2019-present.
  • RoboticEQ (aka Simplr Technologies, an AI-based startup), CEO, 2017-2019.
  • Computer Science PhD at School of Electrical Engineering and Computer Science, The Pennsylvania State University.
  • Electrical Engineering PhD at School of Electrical Engineering, Sharif University of Technology.

About Me

Working at a Robotic startup (Dexterity.AI) is my current status. My broad experience is specialized in executive management (4+yr), artificial intelligence (AI) specially machine learning (ML), computer vision (CV), and image processing (8+yr), back-end/infrastructure development (4+yr), front-end development (4+yr), and networking/security (3+yr).

While I am highly interested to create/exploit open-source code in an optimized way for a new/better solution of challenging problems while no fear to explore any new research area or technology.

I joined RoboticEQ (aka Simplr Technologies) as the CEO in June 2017. RoboticEQ was the spin-off of the project that I was working since my CS PhD by a seed fund for innovation from Penn State.

I was a member of Intelligent Information Systems (IIS) research lab at Penn State. I was working with Prof. James Wang (adviser) and Prof. Jesse Barlow (co-adviser), also collaborating with Prof. Zihan Zhou.

My research interests lie in the area of computer vision, machine learning and big data computing. More specifically, I am interested in image aesthetics/composition understanding using conventional machine and deep learning, image retrieval and ranking, and multimedia processing. Also I am working in the field of big data computing specially on resource allocation in distributed systems and parallel computing.

Research and Development

  • Diversity Index across Photo Collection, Unsupervised ML and CV on Big Visual Data, New trending developed technology, 2018.
  • Comprehensive Composition Assistance through Meaningful Exemplars, Deep ML and CV on Big Visual Data, PhD Dissertation, August 2018. [Portrait Dataset]
  • Triangle Detection in Portrait and Landscape Images, ML and CV on Big Data, Part of CS PhD Dissertation, 2017.
  • Emotion-aware Local Guide Technology, ML and CV on Big Data, Part of an NSF Project, 2017.
  • Severe Weather Prediction from Radar Images, ML and CV on Big Data, Part of an NSF Project, 2016.
  • Parallel Aesthetic Scoring Developed in Android by Render-Script, ML and CV on Big Data, Requirement of Innovation Seed Grant, 2016.
  • Image re-Targeting Developed in Android by JNI, ML and CV on Big Data, Requirement of Innovation Seed Grant, 2016.
  • Vanishing Point Detection in Natural Images, ML and CV on Big Data, Part of CS PhD Dissertation, 2015-2016.
  • Stochastic Modeling and Optimization of Stragglers in Parallel Frameworks, Big Data Analytics with Queueing Theory, CS MSc Thesis, 2014-2015.
  • Big Data Analytics on Hadoop/MapReduce Logs, Statistical Analysis, Internship at WD, 2014.
  • Performance Evaluation of Map-Reduce Framework, Big Data Analytics, Research Assistantship, 2014.
  • Optimal Placement of Network on Chip Components, Convex Optimization, Interconnect Network Course Project, 2013.
  • Parallel File System Server with Disk Scheduler and Serializer, Distributed System, OS Design Course Project, 2013.
  • P2P-like DHT-based Network, Distributed Systems, Course Project, 2013.
  • Pluto Compiler Optimization for Fusion and Fission, Compiler Design, Course Project, 2012.
  • Information-theoretic Steganalysis of Very Low Rate Hidden Messages inside the Image, Image Processing, EE PhD Dissertation, 2012.
  • Cloud-segmented Multi-Dimensional Steganalysis, Image Processing, Research Assistantship, 2011.
  • Eigenvalues-based Steganalysis (EVS), Image Processing, Research Assistantship, 2010.
  • Multi-Dimensional Correlated Steganalysis (MDCS), Image Processing, Research Assistantship, 2010.
  • Designing Game-Theoretic Network Simulator (GTNS), Network Security, Co-worker of an MSc Thesis, 2009.
  • Analysis of 3G/4G Cellular Communications Authentication Protocol, Cellular Security, Internship Project, 2008.
  • Improvement of Ad-hoc Network Routing Protocols, Network Security, EE MSc Thesis, 2005-2007.
  • QoS-based Protocol Analysis in Ad-hoc Networks, Networking, Co-worker of an MSc Thesis, 2007.
  • Designing Wireless Mobile Ad-hoc Network Simulator (WMANETSEC), Network Security, Internship Project, 2007.
  • Analysis of 3G, WiFi, WiMax, and Bluetooth Systems Authentication, Cellular Security, Internship Project, 2006.
  • Implementing Data Link Layer Algorithms in Optical CDMA Network Simulator, Networking, EE BSc Thesis, 2004-2005.

Collaborators

  • Graduates: Mohammad-Mehdi Kamani, Yu Luo, Diman Zad Tootaghaj.
  • Undergrads: Sahil Mishra, Shengguang Bai, Jeremy Ong, Yizhi Huang, Jeffery Cao, Luke Porupski.

Publications