Parmida Beigi
| Parmida Beigi | |
|---|---|
| Born | |
| 🏳️ Nationality | Canadian |
| 🎓 Alma mater | University of British Columbia Stanford University |
| 💼 Occupation | |
| Known for | ML/AI Social Influence |
| 🏅 Awards | * Best AI Leaders and Contributors by Global AI Hub (2021)
|
Parmida Beigi is a computational scientist, an NSERC scholar and a senior research scientist currently working at Amazon Alexa AI lab. Her research primarily focuses on machine learning and artificial intelligence for natural language processing, speech recognition, computer vision and information retrieval and ranking. Beigi is known for her contributions as a philanthropist and as an advocate in the tech sector, democratizing AI/ML.[1][2] She is committed to diversity and equity within the tech industry, and to contributing to the community, utilizing her expertise to foster positive change particularly in the domains of AI/ML, big data and data science and women in Tech/STEM.[1][3]
Education and research[edit]
Beigi's interest in mathematics and computing began at a young age. [3][4] She pursued a bachelor's degree in electrical engineering, a master's degrees in electrical engineering from Simon Fraser University,[5] and another master's degree in biomedical engineering with a dual degree in engineering management from University of British Columbia (UBC).[6] She also obtaineda Ph.D. in Electrical and Computer Engineering from UBC.[7][6]
As a data science researcher at the BC Cancer Research Center, Beigi researched the potential of non-invasive approaches for the early diagnosis of lung cancer. Her findings were published in IEEE Transactions on Biomedical Engineering.[8] She also taught computer science and biomedical engineering.[9]
Beigi's research center on the intersection of ML/AI and medical imaging. The key aspect of her research was the spatiotemporal spectral analysis proposal[10] in needle tracking and localization for image-guided procedures leveraging time series forecasting and computer vision.[11] Collaborating with accomplished physicians from BC Women's Hospital and Philips Research, Beigi worked towards the practical application of her research for real-life applications of epidurals to reduce procedural complications and improve patient outcomes. Her ML-based tracking work was published in the International Journal of Computer Assisted Radiology and Surgery.[12][13] She published a review article on tracking and localization techniques in the field in the same.[14]
AI/ML democratization[edit]
Beigi is also a technology evangelist and a tech influencer.[15][16] In October 2018, Beigi launched a nonprofit organization dedicated to promoting the democratization of AI/ML[1][17] and data science trainings,[18] with an emphasis on fostering community engagement and knowledge sharing.
Bibliography[edit]
- P. Beigi, et al., "Enhancement of needle visualization and localization in ultrasound," International Journal of Computer Assisted Radiology and Surgery, 16, pp. 345–347, 2021.
- P. Beigi, et al., "CASPER: Computer-aided segmentation of imperceptible motion - A learning-based tracking of an invisible needle in ultrasound," International Journal of Computer Assisted Radiology and Surgery, 12, pp. 1–10, 2017.[12]
- P. Beigi, et al., "Spectral Analysis of the Tremor Motion for Needle Detection in Curvilinear Ultrasound via Spatio-temporal Linear Sampling," International Journal of Computer Assisted Radiology & Surgery, 11(6), pp. 1183–1192, 2016.[10]
- P. Beigi, et al., "Enhancement of needle visualization and localization in ultrasound," International Journal of Computer Assisted Radiology and Surgery, pp. 1–10, 2020.[14]
- P. Beigi, et al., "Detection of an invisible needle in ultrasound using a probabilistic SVM and time-domain features," The Journal of Ultrasonics, 78, pp. 18–22, 2017.
- P. Beigi, et al., "3D Ultrasound-guided Real-time Midline Epidural Needle Placement with Epiguide: A Prospective Feasibility Study," Journal of Ultrasound in Medicine & Biology, 43(1), pp. 375–379, 2016.[13]
- P. Beigi, et al., "Sex and Smoking Status Effects on the Early Detection of Lung Cancer in High-Risk Smokers using an Electronic Nose," IEEE Transactions on Biomedical Engineering, 62(8), pp. 2044–2054, 2015.[8]
- P. Beigi, et al., "Needle trajectory and tip localization in real-time 3-D ultrasound using a moving stylus," Ultrasound in medicine & biology 41 (7), 2057–2070, 2015.
- P. Beigi, "Image-based enhancement and tracking of an epidural needle in ultrasound using time-series analysis", 2017.[7]
References[edit]
- ↑ 1.0 1.1 1.2 "On a mission to demystify artificial intelligence". Amazon Science. 2023-02-07. Retrieved 2023-05-21.
- ↑ "Speakers Silicon Valley". Tech Summit. 2023-04-11. Retrieved 2023-05-21.
- ↑ 3.0 3.1 "Sharing Career Insights Featuring Parmida Beigi, Amazon Tech Lead and Senior Research Scientist". Apple Podcasts. Retrieved 2023-05-21.
- ↑ Meet The Big Data Queen: Ai & Automation (The Biggest Soceital Revolution Ever), 2023-04-19, retrieved 2023-05-21
- ↑ Beigi, Parmida (2011-08-26). "Compressive sensing based multiview image coding with belief propagation". summit.sfu.ca. Retrieved 2023-05-21.
- ↑ 6.0 6.1 "Parmida Beigi". scholar.google.ca. Retrieved 2023-05-21.
- ↑ 7.0 7.1 Beigi, Parmida (2017). Image-based enhancement and tracking of an epidural needle in ultrasound using time-series analysis (Thesis). University of British Columbia.
- ↑ 8.0 8.1 Beigi, et al., "Early Detection of Lung Cancer in High-Risk Smokers using an Electronic Nose", IEEE Transactions on Biomedical Engineering 62 (8), 2044-2054 https://www.sensigent.com/img/newspdf/sexandsmoking.pdf
- ↑ "Teaching Assistantships | School of Biomedical Engineering". www.bme.ubc.ca. Retrieved 2023-05-21.
- ↑ 10.0 10.1 Beigi, Parmida; Rohling, Robert; Salcudean, Septimiu E.; Ng, Gary C. (2016-06-01). "Spectral analysis of the tremor motion for needle detection in curvilinear ultrasound via spatiotemporal linear sampling". International Journal of Computer Assisted Radiology and Surgery. 11 (6): 1183–1192. doi:10.1007/s11548-016-1402-7. ISSN 1861-6429. PMID 27059024. Unknown parameter
|s2cid=ignored (help) - ↑ Beigi, Parmida; Rohling, Robert; Salcudean, Tim; Lessoway, Victoria A.; Ng, Gary C. (2017-07-01). "Detection of an invisible needle in ultrasound using a probabilistic SVM and time-domain features". Ultrasonics. 78: 18–22. doi:10.1016/j.ultras.2017.02.010. ISSN 0041-624X. PMID 28279882. Unknown parameter
|s2cid=ignored (help) - ↑ 12.0 12.1 Beigi, Parmida; Rohling, Robert; Salcudean, Septimiu E.; Ng, Gary C. (2017-11-01). "CASPER: computer-aided segmentation of imperceptible motion—a learning-based tracking of an invisible needle in ultrasound". International Journal of Computer Assisted Radiology and Surgery. 12 (11): 1857–1866. doi:10.1007/s11548-017-1631-4. ISSN 1861-6429. PMID 28647883. Unknown parameter
|s2cid=ignored (help) - ↑ 13.0 13.1 Beigi, Parmida; Malenfant, Paul; Rasoulian, Abtin; Rohling, Robert; Dube, Alison; Gunka, Vit (2017-01-01). "Three-Dimensional Ultrasound-Guided Real-Time Midline Epidural Needle Placement with Epiguide: A Prospective Feasibility Study". Ultrasound in Medicine & Biology. 43 (1): 375–379. doi:10.1016/j.ultrasmedbio.2016.08.033. ISSN 0301-5629. PMID 27720520.
- ↑ 14.0 14.1 Beigi, Parmida; Salcudean, Septimiu E.; Ng, Gary C.; Rohling, Robert (2021-01-01). "Enhancement of needle visualization and localization in ultrasound". International Journal of Computer Assisted Radiology and Surgery. 16 (1): 169–178. doi:10.1007/s11548-020-02227-7. ISSN 1861-6429. PMID 32995981 Check
|pmid=value (help). Unknown parameter|s2cid=ignored (help) - ↑ Komarraju, Apoorva (2021-04-29). "Be Updated With Big Data On Instagram With These 10 Profiles". Analytics Insight. Retrieved 2023-05-21.
- ↑ "Strategic Systems International on LinkedIn: #strategicsystemsinternational #aiproduct #machinelearning…". www.linkedin.com. Retrieved 2023-05-21.
- ↑ "Parmida (@bigdataqueen) • Instagram photos and videos". www.instagram.com. Retrieved 2023-05-21.
- ↑ Parmida Beigi, @bigdataqueen offers a fresh take on data science and ML https://www.kdnuggets.com/2021/07/learning-data-science-through-social-media.html#:~:text=%40bigdataqueen%C2%A0offers%20a%20fresh%20take%20on%20data%20science%20and%20ML
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