Pattern recognition expert witness candidates typically have extensive experience and expertise in computer science, data science, artificial intelligence, neural networks, electrical engineering, and/or machine learning. Cahn Litigation Services is frequently called upon by legal professionals to locate expert witnesses that can support pattern recognition matters, on behalf of the plaintiff or defendant.
With applications in statistical data analysis, signal processing, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning, pattern recognition refers to the automated recognition of patterns and regularities in data. Common applications of pattern recognition techniques are speech recognition, speaker identification, textual classification, handwriting recognition, and facial recognition. Pattern recognition is used in image processing, such as identification and authentication (e.g., license plate recognition and fingerprint analysis), medical diagnosis, defense (e.g., target recognition), and mobility (e.g., advanced driver assistance systems and autonomous vehicle technology).
Pattern recognition matters that require technical expertise typically involve intellectual property, such as patent infringement or trade secret misappropriation. Pattern recognition can also be used to aid in a criminal investigation and to predict criminal behavior.
Litigation support by a pattern recognition expert witness could include forensic analysis, data analysis, an expert report, expert opinion, and expert witness testimony at a trial. In a high-profile case, or litigation involving a significant financial stake, a law firm may request a technical expert with prior expert witness experience. In addition, clients often seek a pattern recognition subject matter expert for pre-litigation consulting work. Whether the case involves computer vision, voice identification, biometrics, or machine learning, Cahn Litigation Services has the experience required to turn an expert witness search around quickly and provide the right balance of expertise and testimony to support each unique project.
Please Note: All Cahn Litigation expert witness searches are customized to attorneys' precise specifications and preferences. Attorneys are encouraged to discuss search parameters with a Cahn search specialist.
The below expert witness bios represent a small fraction of those Pattern Recognition experts known by Cahn Litigation Services. These bios are provided to give attorneys a sense of the Pattern Recognition landscape.
This expert holds a Ph.D. This expert's Doctoral thesis was on Learning Control and Neural Network Learning. This expert has conducted research and development in the fields of Biometrics, Optimization, Pattern Recognition, Machine Learning, and Internet-Commerce. This expert's work has included research and development, leading to the production of a series of Speaker Recognition, Speech Recognition, Face Recognition, and Signature Recognition software engines. This expert is the author of a textbook on speaker recognition.
This expert developed a procedure for the conversion of classically written articles into articles in Unicode-16. This included working with the editors of an encyclopedia, in detail, to design a character set based on Unicode to be able to handle hundreds of languages (modern and archaic). In addition, automation software was developed for the conversion of articles, while indexing and cross-referencing then automatically. This expert created search mechanisms for searching the articles in any of the many nonstandard transcription techniques used by the readers to transcribe the relevant languages. The mapping, search, and multiple transcription style mapping are quite complex. The indexing included automatic indexing plus keyword references created manually by editors and incorporated into the search and indexing.
This expert has been an Adjunct Professor at the Computer Science department, as well as Mechanical Engineering and Electrical Engineering departments of a major University. This expert has been teaching the following graduate courses: Fundamentals of Speaker Recognition, Fundamentals of Speech Recognition, Digital Control Systems, Applied Signal Recognition and Classification, and Speech and Handwriting Recognition. This expert is also actively involved in several standards bodies.
This expert holds a PhD in Electrical Engineering, has many years of experience in Image and Video Processing, Digital Signal Processing, Embedded Systems, Digital Telecommunications and is a University Chair of Telecommunications. As a university professor, with awards in teaching and two Fulbright scholar experiences that involved engineering instruction, this expert is a consummate explainer of complex facts to audiences at any level. This expert's expertise and experience with Near-Neighbor Searching, Pattern Recognition and feature extraction from audio and or video dates back many years. Further, this expert has taught the subject at the graduate level for years and is highly confident in the ability to handle any discussion having to do with the associated technologies. This expert has extensive prior litigation experience including jury testimony in two patent matters, before en banc panels of 1 to 15 Judges (who can ask questions), and in deposition. This expert has been the primary, testifying expert in HDTV litigations. This expert has written numerous expert reports and declarations as well as participated in technical tutorials for the court.
This expert received a Ph.D. in Mechanical Engineering from a prestigious university. This expert has provided consulting and expert witness services in the robotics sensors and controls arena for decades. This expert has performed significant research and development in reinforcement learning and image pattern recognition and has designed robots with sensitive force feedback. This expert holds multiple patents, and has participated as an expert witness in numerous patent infringement matters involving robotics, sensors, and automation.