A5071606441- Topic Modeling
- Natural Language Processing Techniques
- Multimodal Machine Learning Applications
- Speech Recognition and Synthesis
- Speech and dialogue systems
- Advanced biosensing and bioanalysis techniques
- Cell Image Analysis Techniques
- Neural dynamics and brain function
- Plasmonic and Surface Plasmon Research
- Speech and Audio Processing
- Music and Audio Processing
- Biosensors and Analytical Detection
- Optimization and Search Problems
- Advanced Fluorescence Microscopy Techniques
- CCD and CMOS Imaging Sensors
- Ultrasound and Hyperthermia Applications
- Agricultural and Rural Development Research
- Sparse and Compressive Sensing Techniques
- Turkish Urban and Social Issues
- Interpreting and Communication in Healthcare
- Bacterial Identification and Susceptibility Testing
- Microfluidic and Bio-sensing Technologies
- Microbial infections and disease research
- Hate Speech and Cyberbullying Detection
- SARS-CoV-2 detection and testing
Menlo School
2024
Stanford University
2014-2021
Meta (Israel)
2020-2021
Center for NanoScience
2019
LinkedIn (United States)
2017-2018
Clark University
2018
Bluebird Bio (United States)
2016-2017
Zirve University
2016
Palo Alto Institute
2016
Çanakkale Onsekiz Mart Üniversitesi
2015
In this work, we develop and release Llama 2, a collection of pretrained fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70 parameters. Our LLMs, called 2-Chat, are optimized for dialogue use cases. outperform open-source chat on most benchmarks tested, based our human evaluations helpfulness safety, may be suitable substitute closed-source models. We provide detailed description approach fine-tuning safety improvements 2-Chat order enable the community build work...
Recurrent neural networks have been very successful at predicting sequences of words in tasks such as language modeling. However, all models are based on the conventional classification framework, where model is trained against one-hot targets, and each word represented both an input output isolation. This causes inefficiencies learning terms utilizing information number parameters needed to train. We introduce a novel theoretical framework that facilitates better modeling, show our leads...
State-of-the-art calcium imaging studies that monitor large-scale neural dynamics can produce video datasets tally up to ~100 TB in size (~10 days transfer over 1 Gbit/s ethernet). Processing such data volumes requires automated, general-purpose and fast computational methods for cell identification are robust a wide variety of noise sources. We present EXTRACT, an algorithm is based on estimation theory uses graphical processing units (GPUs) extract from typical computing times ~10-times...
We introduce Llama Guard, an LLM-based input-output safeguard model geared towards Human-AI conversation use cases. Our incorporates a safety risk taxonomy, valuable tool for categorizing specific set of risks found in LLM prompts (i.e., prompt classification). This taxonomy is also instrumental classifying the responses generated by LLMs to these prompts, process we refer as response classification. For purpose both and classification, have meticulously gathered dataset high quality....
Talent search and recommendation systems at LinkedIn strive to match the potential candidates hiring needs of a recruiter or manager expressed in terms query job posting. Recent work this domain has mainly focused on linear models, which do not take complex relationships between features into account, as well ensemble tree introduce non-linearity but are still insufficient for exploring all feature interactions, strictly separate generation from modeling. In paper, we present results our...
Human Papillomavirus (HPV) infection has been recognized as the main etiologic factor in development of various cancers including penile, vulva, oropharyngeal and cervical cancers. In cancer, persistent HPV infections induce E6 E7 oncoproteins, which promote cell proliferation carcinogenesis resulting elevated levels host antibodies (e.g., anti-HPV16 antibody). Currently, these are clinically diagnosed using invasive biopsy-based tests, performed only centralized labs by experienced clinical...
Abstract Extracellular matrix (ECM) stiffness is correlated to malignancy and invasiveness of cancer cells. Although the mechanism change unclear, mechanical signals from ECM may affect physical properties cells such as their density profile. The current methods, Percoll density‐gradient centrifugation, are unable detect minute differences. A magnetic levitation device developed (i.e., MagDense platform) where levitated in a gradient allowing them equilibrate height that corresponds unique...
Ankit Arun, Soumya Batra, Vikas Bhardwaj, Ashwini Challa, Pinar Donmez, Peyman Heidari, Hakan Inan, Shashank Jain, Anuj Kumar, Shawn Mei, Karthik Mohan, Michael White. Proceedings of the 28th International Conference on Computational Linguistics: Industry Track. 2020.
We report on the implementation of an automated platform for detecting presence antibody biomarker human papillomavirus-associated oropharyngeal cancer from a single droplet serum, in which nanostructured photonic crystal surface is used to amplify output fluorescence-linked immunosorbent assay. The comprised microfluidic cartridge with integrated chips that interfaces assay instrument automates introduction reagents, wash steps, and drying. Upon completion, custom laser-scanning couples...
We studied the paracrine function of mesenchymal stem cells (MSCs) derived from various sources in response to pulsed focused ultrasound (pFUS). Human adipose tissue (AD), bone marrow (BM), and umbilical cord (UC) MSCs were exposed pFUS at two intensities: 0.45 W/cm 2 I SATA (310 kPa PNP) 1.3 (540 PNP). Following pFUS, viability proliferation assessed using a hemocytometer confocal microscopy, their secreted cytokine profile determined multiplex ELISA. Our findings showed that can stimulate...
Neutrophils have a critical role in regulating the immune system. The system is compromised during chemotherapy, increasing infection risks and imposing need for regular monitoring of neutrophil counts. Although commercial hematology analyzers are currently used clinical practice counts, they only available clinics hospitals, use large blood volumes, not at point care (POC). Additionally, phlebotomy processing require trained personnel, where patients often admitted to hospitals when...
In recent years, DNA nanotechnology has matured to enable robust production of complex nanostructures and hybrid materials. We have combined with sensitive optical detection create functional single-molecule devices that new applications in biosensing superresolution microscopy. Starting nanorulers brightness reference samples we determined the resolving power microscopes evaluated sensitivity smartphone cameras. To improve created origami antennas for metal enhanced fluorescence. The unique...
Abstract Recent advances in calcium imaging enable simultaneous recordings of up to a million neurons behaving animals, producing datasets unprecedented scales. Although individual and their activity traces can be extracted from these videos with automated algorithms, the results often require human curation remove false positives, laborious process called cell sorting . To address this challenge, we introduce ActSort, an active-learning algorithm for large-scale that integrates features...
Araştırma,
Text segmentation aims to divide text into contiguous, semantically coherent segments, while segment labeling deals with producing labels for each segment. Past work has shown success in tackling and documents conversations. This been possible a combination of task-specific pipelines, supervised unsupervised learning objectives. In this work, we propose single encoder-decoder neural network that can handle long conversations, trained simultaneously both using only standard supervision. We...
Question answering (QA) is an important use case on voice assistants. A popular approach to QA extractive reading comprehension (RC) which finds answer span in a text passage. However, answers are often unnatural conversational context results suboptimal user experience. In this work, we investigate generation for QA. We propose AnswerBART, end-to-end generative RC model combines from multiple passages with passage ranking and answerability. Moreover, hurdle applying hallucinations where the...
In this paper, we show that a simple self-supervised pre-trained audio model can achieve comparable inference efficiency to more complicated models with speech transformer encoders. These transformers rely on mixing convolutional modules self-attention modules. They state-of-the-art performance ASR top efficiency. We first employing these as an encoder significantly improves the of well. However, our study shows advanced solely. demonstrate simpler approach is particularly beneficial low-bit...