Kamal Qureshi
FAST
· 2022
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I18 - 0438
Email
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Phone
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LinkedIn
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GitHub
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Academic
Program
BSCS
CGPA
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Year
2022
Education
SEECS
Address
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DOB
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Career
Current role
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Target role
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Skills
Flutter, Google Firebase, Librosa, Torch, Google Search API, Beautiful Soup, Python, Google Colab, Urdu Speech Recognition, Machine Learning
Verbatim text
The exact text the LLM saw on the page (or the booklet text from the old import).
This is what powers semantic search.
Smart Grocery Our Project is based on the idea of ordering groceries online through Urdu Speech Recognition as well as making a user profile for further saving the user’s most frequently ordered items and categorizing edible items that would be safe or unsafe for the user (in case of any health issues). In our project for Urdu speech recognition, we will have to train and develop an Urdu based speech recognition model by first using multiple voice recordings as datasets and mapping them out with their corresponding English text by transcribing them. The problem that we discovered was that Urdu doesn't have a global recognition as a language despite there being 70 million native speakers. So, by enabling Urdu Speech we would be promoting an application that has the ability to understand what a native Urdu speaker is trying to order. The next feature is Auto Generation, for this we will have to collect data of a user’s recent purchases as well as their frequently bought items, next after collecting a sufficient amount of data, a grocery list will be generated which matches the user profile. The objective of this is to minimize the amount of time a user takes to select every grocery item on their shopping list. So, generating a grocery list will help users order groceries with less effort and time. Also, to facilitate the users more, Smart Categorization will help users be shown only edible products that would be medically safe for the user based on their health requirements. The problem that we discovered was that, most people cannot differentiate edible items that would be medically safe or unsafe for them, they would tend to ignore labels on food items or even general research on a particular item. So, smart categorization would allow for users to be displayed edible items that are safe for them. Technology Used: Flutter, Google Firebase, Librosa, Torch, Google Search API, Beautiful Soup, Python, Google Colab Supervisor Name: Dr. Shujaat Hussain Group Members: Shujaa Marwat (I18 - 0432) Kamal Qureshi (I18 - 0438) Areesha Maqsood (I18 - 0600)
AI enrichment
Kamal Qureshi is a BSCS graduate who contributed to a university project involving an Urdu speech recognition grocery ordering application. The project utilized Flutter and Python to implement features like auto-generated shopping lists and health-based food categorization.
Skills (AI)
["Flutter", "Python", "Google Firebase", "Librosa", "PyTorch", "Google Search API", "Beautiful Soup", "Speech Recognition", "Data Collection"]
Status: ai_done
Provenance
Source file: Graduate Directory FAST School of Computing 2022 Final Version (07-06-2022).pdfFrom job #25 page 259
Created: 1778150712