Wael Nackasha

Associate
Email: [email protected]
Phone: 1-416-624-0877

Wael Louis Nackasha focuses on M&A due diligence and technology-related transactional matters. Wael specializes in open source and commercial software licensing, agreements for the sharing of strategic and commercially sensitive technology, and IP strategy advice, as well as artificial intelligence and generative artificial intelligence related matters, including risk management, policies, and assessment of training datasets.

Wael drafts and prosecutes patent applications covering a wide range of technologies, including machine learning, blockchain, electrical, telecommunications, and computer-related technology. Before joining GTC, Wael was an Associate at Ridout and Maybee LLP where he practiced before both the USPTO and CIPO.

Prior to becoming an attorney, Wael spent several years as a research scientist and software developer. He has published scientific papers in conferences and journals on machine learning, biometrics, computer vision, signal and image processing, and statistical signal processing. Wael holds a J.D. from Osgoode Hall Law School, a Ph.D. and a Master of Applied Science in Electrical and Computer Engineering from the University of Toronto with dissertations focused on artificial intelligence, and a Bachelor of Engineering in Electrical Engineering from Ryerson University (renamed as Toronto Metropolitan University).

In his Ph.D. dissertation titled “Online and Continuous Electrocardiogram (ECG) Biometric System” (2017), Wael proposed a biometric system for continuously monitoring the identity of subjects using their electrocardiogram signals. The dissertation includes proposing novel feature extraction and detecting and removing abnormal electrocardiogram signals using statistical models.

In his Master of Applied Science dissertation titled “Weakly Trained Parallel Classifier and CoLBP Features for Frontal Face Detection in Surveillance Applications” (2010), Wael developed a computer vision system for face detection using novel discriminative features.

Selected technical publications:

  • Louis, Wael. Online and Continuous Electrocardiogram (ECG) Biometric System. University of Toronto (Canada), 2017.
  • Komeili, Majid, Wael Louis, Narges Armanfard, and Dimitrios Hatzinakos. “Feature selection for nonstationary data: Application to human recognition using medical biometrics.” IEEE Transactions on Cybernetics 48, no. 5 (2017): 1446-1459.
  • Louis, Wael, Shahad Abdulnour, Sahar Javaher Haghighi, and Dimitrios Hatzinakos. “On biometric systems: electrocardiogram Gaussianity and data synthesis.” EURASIP Journal on Bioinformatics and Systems Biology 2017, no. 1 (2017): 1-10.
  • Louis, Wael, Majid Komeili, and Dimitrios Hatzinakos. “Continuous authentication using one-dimensional multi-resolution local binary patterns (1DMRLBP) in ECG biometrics.” IEEE Transactions on Information Forensics and Security 11, no. 12 (2016): 2818-2832.
  • Louis, Wael, Dimitrios Hatzinakos, and Anastasios Venetsanopoulos. “One dimensional multi-resolution local binary patterns features (1DMRLBP) for regular electrocardiogram (ECG) waveform detection.” In 2014 19th International Conference on Digital Signal Processing, pp. 601-606. IEEE, 2014.
  • Louis, Wael, and Konstantinos N. Plataniotis. “Co-occurrence of local binary patterns features for frontal face detection in surveillance applications.” EURASIP Journal on Image and Video Processing 2011 (2011): 1-17.
  • Louis, Wael, and Konstantinos N. Plataniotis. “Frontal face detection for surveillance purposes using dual Local Binary Patterns features.” In 2010 IEEE International Conference on Image Processing, pp. 3809-3812. IEEE, 2010.
  • Louis, Wael. Weakly trained parallel classifier and CoLBP features for frontal face detection in surveillance applications. University of Toronto (Canada), 2010.