37 citations · 120 across the 24 of their papers we have counts for
28 papers
LO-FAR: A Cost-Aware Local Filter for Sparse Feature Ranking in Industrial Ad Recommendation
Egemen Erbayat, Luis Duque, Sohini Roychowdhury +2
Industrial ad recommendation models rely heavily on sparse, high-cardinality ID-list features that encode user histories and contextual identifiers. Each is backed by a dedicated e…
COFFEE: COdesign Framework for Feature Enriched Embeddings in Ads-Ranking Systems
Sohini Roychowdhury, Doris Wang, Qian Ge +2
Diverse and enriched data sources are essential for commercial ads-recommendation models to accurately assess user interest both before and after engagement with content. While ext…
DynamiX: Dynamic Resource eXploration for Personalized Ad-Recommendations
Sohini Roychowdhury, Adam Holeman, Mohammad Amin +3
For online ad-recommendation systems, processing complete user-ad-engagement histories is both computationally intensive and noise-prone. We introduce Dynamix, a scalable, personal…
SIDE: Semantic ID Embedding for effective learning from sequences
Dinesh Ramasamy, Shakti Kumar, Chris Cadonic +4
Sequence-based recommendations models are driving the state-of-the-art for industrial ad-recommendation systems. Such systems typically deal with user histories or sequence lengths…
FiSTECH: Financial Style Transfer to Enhance Creativity without Hallucinations in LLMs
Sohini Roychowdhury, Marko Krema, Brian Moore +3
Recent trends in Generative AI have emerged towards fine-tuning foundational large language models (LLMs) to create domain-specific LLMs for automation and chatbot-like application…
ERATTA: Extreme RAG for Table To Answers with Large Language Models
Sohini Roychowdhury, Marko Krema, Anvar Mahammad +3
Large language models (LLMs) with retrieval augmented-generation (RAG) have been the optimal choice for scalable generative AI solutions in the recent past. Although RAG implemente…
Journey of Hallucination-minimized Generative AI Solutions for Financial Decision Makers
Sohini Roychowdhury
Generative AI has significantly reduced the entry barrier to the domain of AI owing to the ease of use and core capabilities of automation, translation, and intelligent actions in…
Hallucination-minimized Data-to-answer Framework for Financial Decision-makers
Sohini Roychowdhury, Andres Alvarez, Brian Moore +8
Large Language Models (LLMs) have been applied to build several automation and personalized question-answering prototypes so far. However, scaling such prototypes to robust product…
NUMSnet: Nested-U Multi-class Segmentation network for 3D Medical Image Stacks
Sohini Roychowdhury
Semantic segmentation for medical 3D image stacks enables accurate volumetric reconstructions, computer-aided diagnostics and follow up treatment planning. In this work, we present…
Semi-supervised and Deep learning Frameworks for Video Classification and Key-frame Identification
Sohini Roychowdhury
Automating video-based data and machine learning pipelines poses several challenges including metadata generation for efficient storage and retrieval and isolation of key-frames fo…
Video-Data Pipelines for Machine Learning Applications
Sohini Roychowdhury, James Y. Sato
Data pipelines are an essential component for end-to-end solutions that take machine learning algorithms to production. Engineering data pipelines for video-sequences poses several…
QU-net++: Image Quality Detection Framework for Segmentation of Medical 3D Image Stacks
Sohini Roychowdhury
Automated segmentation of pathological regions of interest aids medical image diagnostics and follow-up care. However, accurate pathological segmentations require high quality of a…
SISE-PC: Semi-supervised Image Subsampling for Explainable Pathology
Sohini Roychowdhury, Kwok Sun Tang, Mohith Ashok +1
Although automated pathology classification using deep learning (DL) has proved to be predictively efficient, DL methods are found to be data and compute cost intensive. In this wo…
OPAM: Online Purchasing-behavior Analysis using Machine learning
Sohini Roychowdhury, Ebrahim Alareqi, Wenxi Li
Customer purchasing behavior analysis plays a key role in developing insightful communication strategies between online vendors and their customers. To support the recent increase…
Cirrus: A Long-range Bi-pattern LiDAR Dataset
Ze Wang, Sihao Ding, Ying Li +7
In this paper, we introduce Cirrus, a new long-range bi-pattern LiDAR public dataset for autonomous driving tasks such as 3D object detection, critical to highway driving and timel…
Categorizing Online Shopping Behavior from Cosmetics to Electronics: An Analytical Framework
Sohini Roychowdhury, Wenxi Li, Ebrahim Alareqi +3
A success factor for modern companies in the age of Digital Marketing is to understand how customers think and behave based on their online shopping patterns. While the conventiona…
Few Shot Learning Framework to Reduce Inter-observer Variability in Medical Images
Sohini Roychowdhury
Most computer aided pathology detection systems rely on large volumes of quality annotated data to aid diagnostics and follow up procedures. However, quality assuring large volumes…
FuSSI-Net: Fusion of Spatio-temporal Skeletons for Intention Prediction Network
Francesco Piccoli, Rajarathnam Balakrishnan, Maria Jesus Perez +13
Pedestrian intention recognition is very important to develop robust and safe autonomous driving (AD) and advanced driver assistance systems (ADAS) functionalities for urban drivin…
Range Adaptation for 3D Object Detection in LiDAR
Ze Wang, Sihao Ding, Ying Li +5
LiDAR-based 3D object detection plays a crucial role in modern autonomous driving systems. LiDAR data often exhibit severe changes in properties across different observation ranges…
Computer Aided Detection of Anemia-like Pallor
Sohini Roychowdhury, Donny Sun, Matthew Bihis +3
Paleness or pallor is a manifestation of blood loss or low hemoglobin concentrations in the human blood that can be caused by pathologies such as anemia. This work presents the fir…
Automated OCT Segmentation for Images with DME
Sohini Roychowdhury, Dara D. Koozekanani, Michael Reinsbach +1
This paper presents a novel automated system that segments six sub-retinal layers from optical coherence tomography (OCT) image stacks of healthy patients and patients with diabeti…
Automated Selection of Uniform Regions for CT Image Quality Detection
Maitham D Naeemi, Adam M Alessio, Sohini Roychowdhury
CT images are widely used in pathology detection and follow-up treatment procedures. Accurate identification of pathological features requires diagnostic quality CT images with min…
Blind Analysis of CT Image Noise Using Residual Denoised Images
Sohini Roychowdhury, Nathan Hollraft, Adam Alessio
CT protocol design and quality control would benefit from automated tools to estimate the quality of generated CT images. These tools could be used to identify erroneous CT acquisi…
Classification of Large-Scale Fundus Image Data Sets: A Cloud-Computing Framework
Sohini Roychowdhury
Large medical image data sets with high dimensionality require substantial amount of computation time for data creation and data processing. This paper presents a novel generalized…