2021

  • December: Our paper, with Saria Goudarzvand, "Similarity-based Second-Chance Autoencoders for Textual Data" has been accepted for publication in the Applied Intelligence journal (in publication)

  • November: Our paper, with Saria Goudarzvand, "Competitive Coherence-based Autoencoders for Document Understanding" has been accepted to the AAAI-22 Workshop on Scientific Document Understanding

  • October: Our tool demo paper is accepted at NeurIPS 2021 (tool website).

  • August: Taught an online course in Arabic entitled "Deep Learning with PyTorch"

  • August: Submitted several patents on privacy-preserving and secure multi-party computation methods for AI

  • June: Presented "Privacy-Preserving Decentralized Learning: Innovations and Challenges" at the UCI Edge Lab

  • May: Serving as a PC member at the Secure and Privacy-Preserving Machine Learning for Medical Imaging: MICCAI 2021 Workshop and Tutorial

  • March: Served as a PC member for the Distributed and Private Machine Learning, ICLR workshop

  • March: Presented a workshop, "Federated Learning for Data Privacy", at Byan School for Data Science.

  • March: Presented a workshop, "Blind Learning: An efficient privacy-preserving approach for distributed learning", at the Split Learning for Distributed Machine Learning workshop, MIT Media Lab

  • February: Presented a workshop, "Practical Intro to Deep Learning Computer Vision using PyTorch", at Saudi Data Community, Alkhobar

2020

  • December: Received my PhD Degree!

  • October: Filed my third provisional patent with TripleBlind for a new approach for model Fingerprinting.

  • August: Presented a workshop, "Generating Arabic Text using TensorFlow", at Byan

  • August: Filed my second provisional patent with TripleBlind for a new approach for privacy-preserving learning.

  • July: Filed my first provisional patent with TripleBlind for a new approach for distributed private learning.

  • May: Started my interneship as a Research Scientist at TripleBlind, specialized in privacy-preserving ML.

  • May: Presented "Privacy-Preserving ML; Membership Inference Attacks" at the Virtual W&B Salon.

  • April: Served as an external reviewer for the AMIA 2020 Annual Symposium

  • March: Served as a PC member for the DEEM workshop in conjunction with SIGMOD/PODS 2020

  • Feb: Our deep learning model for detecting DeepFakes, named Defakify, won the Second place in UM System DeepFake competition. Check UMKC News.

  • Jan: started my research internship as a Research Scientist in KC.

  • Jan: Our deep learning model for detecting DeepFakes, named Defakify, made it to the final round of the UM System DeepFake competition

  • Jan: I received the Research-A-Thon Travel Award, SCE, UMKC


2019

  • December: I received the Balaji Travel Award for presenting our accepted paper at the IEEE BigData 2019.

  • November: Our research paper "Characterizing and Understanding Software Evolution using Call Graphs" is accepted at the BigGraphs workshop, IEEE BigData conference.

  • October: Presented my research work on Managing the Modeling Lifecycle of Deep Learning at the NSF-Center for Big Learning at the University of Floriday, Florida

  • October: Presented a research roadmap for Private and Secure Deep Learning for the Board of Trustees of UMKC (one of three students from UMKC to present).

  • September: Presented my research work on Private and Secure Deep Learning for the Board of Curators of the University of Missouri System (one of five students from UMKC).

  • May: Our research project "Medl.AI" won the First place at the Research-A-Thon competition, UMKC

  • May: Our startup won both the First place and the Audience Award at the Regnier Venture Creation Challenge.

  • April: Our paper "Automated Management of Deep Learning Experiments." has been accepted at DEEM ’19 (an ACM SIGMOD/PODS workshop).

  • March: Our venture "DeepLens" won the first prize at the Entrepreneurship Quest, Regnier Institute for Entrepreneurship and Innovation.

  • March: Our paper "ModelKB: Towards Automated Management of the Modeling Lifecycle in Deep Learning" is accepted at the 7th workshop on Realizing Artificial Intelligence Synergies in Software Engineering (co-hosted with ICSE 2019).


2018

  • December: Won the third place at the IEEE BigData BDGMM Hackathon (analyzing and visualizing EEG brain signals).

  • December: Our Startup "DeepLens" passed the second Pitch Deck (top 10) towards winning $30K. We also won the Audience Award.

  • November: Our paper "Automatic Hierarchical Clustering of Static Call Graphs for Program Comprehension " is accepted at the BigGraphs workshop at the 2018 IEEE BigData Conference.

  • October: Led the organizing team of the Hack-A-Roo event.

  • September: Served as a Program Committee member at the 2nd International Workshop on Knowledge Discovery in Translational Biomedical Informatics (KDTBI 2018).

  • July: Our paper "Code2graph: Automatic generation of Static Call Graphs for Python Source Code" is accepted at the 2018 33rd ACM/IEEE International Conference on Automated Software Engineering (ASE'18).

  • May: Presented a poster at the NSF-Center for Big Learning, University of Florida.

  • April: Received the Outstanding Doctoral Student in Computer Science Award, UMKC.

  • February 2018: Received the Best Overall Podium Presentation Award, Community of Scholars, UMKC.


2017

  • November: Received the Love of Learning Award, national office of Phi Kappa Phi Honor Society.

  • November: Passed the I.PhD. qualifier exam.

  • October: Graduated from the Graduate Student Leadership Development Program, University of Missouri System.

  • October: presented "Increasing Collaborative and Interactive Online Learning through Constructive Pedagogy Practices and Technological Innovation and Diversity". A group project at the School of Education, UMKC

  • July: Attended the 2017 Phi Kappa Phi Leadership Development Summit in Denver.