Work with thought leaders and academic experts in natural language processing

Companies can greatly benefit from working with natural language processing experts. These researchers can help improve customer experience by developing chatbots and virtual assistants that can understand and respond to customer queries in real-time. They can also automate processes by developing algorithms that can analyze and extract information from large volumes of text data. Additionally, companies can leverage their expertise in sentiment analysis to gain insights from customer feedback and social media data. Natural language processing experts can also assist in developing machine translation systems, voice recognition technologies, and text summarization algorithms. Overall, collaborating with these experts can enhance data analysis, improve decision-making, and drive innovation in various industries.

Researchers on NotedSource with backgrounds in natural language processing include Christos Makridis, Brian Flaxman, Ph.D, Carsten Eickhoff, Ph.D., Joshua Cohen, Jim Samuel, Edoardo Airoldi, Leilani Gilpin, Suhang Wang, Osaye Fadekemi, PhD, Dr. Justin W. Hart, Ph.D., Haining Wang, and Nima Ziraknejad.

Christos Makridis

Nashville, TN
10 Years Experience
Web3 and Labor Economist in Academia, Entrepreneurship, and Policy
Education

Stanford University

Dual Ph.D., Economics and Management Science & Engineering / June, 2018

Stanford, California, United States of America

Arizona State University

B.S., Economics and Mathematics / May, 2012

Tempe, Arizona, United States of America
Experience

Stanford University

Digital Fellow / August, 2020 — Present

Department of Veterans Affairs

Senior Adviser, National AI Institute / January, 2020 — Present

Columbia Business School

Adjunct Associate Research Scholar / February, 2022 — Present

Research Expertise (16)
Finance
Economics and Econometrics
Accounting
Pharmacology (medical)
Law
And 11 more
About
Christos A. Makridis holds academic appointments at Columbia Business School, Stanford University, Baylor University, University of Nicosia, and Arizona State University. He is also an adjunct scholar at the Manhattan Institute, senior adviser at Gallup, and senior adviser at the National AI Institute in the Department of Veterans Affairs. Christos is the CEO/co-founder of [Dainamic](https://www.dainamic.ai/), a technology startup working to democratize the use and application of data science and AI techniques for small and mid sized organizations, and CTO/co-founder of [Living Opera](https://www.livingopera.org/), a web3 startup working to bridge classical music and blockchain technologies. Christos previously served on the White House Council of Economic Advisers managing the cybersecurity, technology, and space activities, as a Non-resident Fellow at the Cyber Security Project in the Harvard Kennedy School of Government, as a Digital Fellow at the Initiative at the Digital Economy in the MIT Sloan School of Management, a a Non-resident Research Scientist at Datacamp, and as a Visiting Fellow at the Foundation for Defense of Democracies. Christos’ primary academic research focuses on labor economics, the digital economy, and personal finance and well-being. He has published over 70 peer-reviewed research papers in academic journals and over 170 news articles in the press. Christos earned a Bachelor’s in Economics and Minor in Mathematics at Arizona State University, as well a dual Masters and PhDs in Economics and Management Science & Engineering at Stanford University.

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Brian Flaxman, Ph.D

Jupiter, Florida, United States of America
8 Years Experience
University of Colorado Boulder
Education

University of Colorado Boulder

Ph.D, Economics / August, 2024

Boulder, Colorado, United States of America

University of Colorado Boulder

MA, Economics / May, 2018

Boulder, Colorado, United States of America

University of Florida

BA, Economics / May, 2014

Gainesville, Florida, United States of America
Experience

University of Colorado Boulder

TA/Instructor / August, 2016 — December, 2023

Was TA or instrcutor of record for a variety of economics courses.

Most Relevant Research Expertise
Natural Language Processing
Other Research Expertise (4)
Political Economy
Public Economics
Policy Economics
Political Economics
About
My name is Brian Flaxman, recent Economics PhD graduate from The University of Colorado-Boulder. My specialties are political and policy economics, with natural language processing applications. My job market paper "Legislation For Sale? The Influence of PhRMA Campaign Donations on US House Health Legislation'' finds that House members who receive more in PhRMA Political Action Committee (PACs) donations sponsor legislation more favorable to PhRMA than legislators who receive less and vice versa. I pride myself in thinking outside of the box when it comes to research, oftentimes taking the form of using relatively basic tools from certain fields and apply them to find easy solutions to problems in other fields (In my job market paper's case, using NLP to solve a problem in political economy).

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Carsten Eickhoff, Ph.D.

Tübingen
15 Years Experience
Professor | Scientific Director | Founder | Board Member | Expert in Natural Language Processing and AI
Education

Technische Universiteit Delft

Ph.D. (Computer Science) / October, 2014

Delft

The University of Edinburgh

M.Sc. (Artificial Intelligence) / November, 2009

Edinburgh

FHDW Hannover

B.Sc. / 2008

Experience

University of Tübingen

Professor / 2022 — Present

Brown University

Manning Assistant Professor / 2018 — 2022

ETH Zurich

Postdoc / 2014 — 2018

Most Relevant Research Expertise
Natural Language Processing
Other Research Expertise (5)
Information Retrieval
Digital Health
Generative AI
Machine Learning
Technology Entrepreneurship
About
Carsten is a Professor at the University of Tübingen where his lab specializes in the development of interpretable natural language processing and AI techniques. Prior to joining Tübingen, he was the Manning Assistant Professor of Medical and Computer Science at Brown University. He received degrees from the University of Edinburgh and TU Delft, and was a postdoctoral fellow at ETH Zurich and Harvard University. Carsten has authored more than 150 articles in computer science conferences (e.g., ICLR, ACL, SIGIR, WWW, KDD) and clinical journals (e.g., Nature Digital Medicine, The Lancet - Respiratory Medicine, Radiology, European Heart Journal). His research has been supported by the Swiss National Science Foundation, NSF, NIH, DARPA, IARPA, Google, Amazon, Microsoft and others. Aside from his academic endeavors, he is a founder and board member of several deep technology startups.

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Joshua Cohen

Cincinnati, Ohio, United States of America
9 Years Experience
PhD in Physics Applies Scientific Expertise to Develop ML Models for Diverse Applications
Education

Tufts University

Ph.D., Physics / July, 2018

Medford, Massachusetts, United States of America
Experience

Clarigent Health

Chief Scientific Officer / January, 2022 — Present

•Leads team's scientific and technical efforts for company focused on identifying mental health risks from speech data •Direct clinical mental health data collection for machine learning model development, validation, and utility assessment •Heads communication of scientific achievements through peer-reviewed publications and conference presentations

Director of Data Science / September, 2020 — January, 2022

•Invented novel quantitative methods to drive product changes and improve end-to-end customer experience (e.g., automatic speaker identification, transcript quality assessments, and on-topic speech detection) •Developed customer facing dashboard and data model in Microsoft PowerBI to communicate sensitive patient data •Published 2 first author articles validating machine learning models and presented findings at international conference •Principal Investigator for Phase I NIH SBIR grant investigating and mitigating machine learning model bias •Oversaw interviewing, onboarding, training, and daily tasks of 5 data scientists

Senior Data Scientist / September, 2019 — September, 2020

Developed and deployed ML models in Python to identify suicidal risk, depression, and anxiety from speech data •Experimented with various ML approaches (e.g., SVM, RF, and ANN) to improve model performance •Utilized advanced NLP (e.g., word embeddings and sentiment analysis) to extract meaningful features and improve accuracy •Designed and implemented ETL pipelines to efficiently extract, transform, and load large volumes of speech data

Freelance

Data Scientist / January, 2019 — September, 2019

Developed models to predict mouse sleep states (sleep, REM, wake) from brain and muscle signals with 96% accuracy

UES at Air Force Research Labs

Research Scientist / August, 2018 — September, 2019

•Lead R&D program for medical countermeasures of directed energy in 711th HPW/Force Health Protection Branch •Principal Investigator: Feasibility of Deployed Medical System Hardening to Directed Energy, In-Vitro Cellular Response to Directed Energy, Rapid Environmental Site Assessment with Readily Available Biomaterials •Characterized emissions from ammunition causing health issues with microscopic, spectroscopic, and statistical analysis

Research Expertise (2)
Public Health, Environmental and Occupational Health
Physical and Theoretical Chemistry
About
I am a highly motivated individual with expertise in various artificial intelligence (AI) tools, including machine learning (ML) and natural language processing (NLP). Over the course of my academic and professional career, I have developed a strong skill set in these areas, and have applied them to various domains, including mental health. At Clarigent Health, I have played a key role in developing and improving machine learning models that analyze patient speech to identify mental health concerns such as depression, anxiety, and suicide risk. In addition, I have been the principal investigator on a NIMH SBIR grant investigating machine learning model performance across different patient characteristics and settings. Moreover, I have experience in developing and implementing customer-facing dashboards using tools like PowerBI, which enable clients to interact with and derive insights from complex data sets. Through my work at Clarigent Health, I have been able to leverage my expertise in ML, NLP, and other AI-related tools to drive innovation and improve mental health outcomes through data-driven solutions.

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Jim Samuel

11 Years Experience
Associate Professor at Rutgers University
Education

Baruch College

PhD, Information Systems / 2007

New York, New York, United States of America
Experience

Rutgers University

Associate Professor / 2021 — Present

Axivest

CIO / 2012 — Present

Research Expertise (22)
Analytics
Artificial Intelligence
Informatics
Machine Learning
NLP NLU NLG Behavioral Finance
And 17 more
About
Jim Samuel is an Associate Professor of Practice and Executive Director of the Informatics Program at the Bloustein School. He is an information and artificial intelligence (AI) scientist, with significant industry experience in finance, technology, entrepreneurship and data analytics. Dr. Samuel’s primary research covers human intelligence and artificial intelligences interaction and information philosophy.  Dr. Samuel’s applied research focuses on the optimal use of big data and smart data driven AI applications, textual analytics, natural language processing and artificially intelligent public opinion informatics. His expertise extends to socioeconomic implications of AI, applied machine learning, social media analytics, AI education and AI bias. Dr. Samuel completed his Ph.D. from the Zicklin School of Business, Baruch College – City University of New York, and he also has M.Arch and M.B.A (International Finance) degrees.  Dr. Samuel has worked with large multinational financial services corporations, and advises businesses and organizations on data analytics and AI driven value creation strategies. He is passionate about research driven thought leadership in AI, information philosophy, analytics and informatics. 

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Edoardo Airoldi

Professor of Statistics & Data Science Temple University & PI, Harvard University
Education

Università Bocconi

B.Sc., Institute for Quantitative Methods

Milano

Carnegie Mellon University

Ph.D., School of Computer Science

Pittsburgh, Pennsylvania, United States of America
Experience

Harvard University

Research Expertise (44)
Statistics
Causal Inference
Network Science
Cell Biology
Molecular Biology
And 39 more
About
Edoardo Airoldi is a Professor in the Department of Machine Learning at Temple University. He is also the Director of the Center for Machine Learning and Health. He is a world-renowned expert in the fields of machine learning and artificial intelligence, with a focus on applications to health. Airoldi is a member of the prestigious Association for the Advancement of Artificial Intelligence (AAAI) and the International Machine Learning Society (IMLS). He has published over 200 papers in leading journals and conferences, and his work has been covered by various media outlets including The New York Times, The Wall Street Journal, The Economist, and Wired.

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Leilani Gilpin

12 Years Experience
Assistant Professor of Computer Science - UC Santa Cruz
Education

Massachusetts Institute of Technology

Ph.D., Electrical Eng. and Computer Science / 2020

Cambridge, Massachusetts, United States of America

Stanford University

M.S., Computational and Mathematical Engineering / 2013

Stanford, California, United States of America

University of California, San Diego

B.S., Computer Science and Mathematics / 2011

San Diego, California, United States of America
Experience

UC Santa Cruz

Assistant Professor of Computer Science / 2021 — Present

Sony

AI Researcher / 2020 — 2021

Palo Alto Research Center

Technical Staff / 2011 — 2013

Research Expertise (12)
Explainable AI
Diagnostics
Anomaly Detection
Commonsense Reasoning
AI and ethics
And 7 more
About
Leilani Gilpin is an assistant professor of computer science at UC Santa Cruz. She holds a Ph.D. in electrical engineering and computer science from the Massachusetts Institute of Technology and a B.S. in computer science and mathematics from the University of California, San Diego. She also has experience as an AI researcher at Sony and the Palo Alto Research Center.

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Suhang Wang

5 Years Experience
Professor at Pennsylvania State University
Education

Arizona State University

PhD, Computer Science / July, 2018

Tempe, Arizona, United States of America

University of Michigan

MS, Electrical Engineering: Systems / December, 2013

Ann Arbor, Michigan, United States of America

Shanghai Jiao Tong University

BS, Electrical and Computer Engineering / July, 2012

Shanghai
Experience

Pennsylvania State University

Assistant Professor / August, 2018 — Present

Research Expertise (21)
Machine learning
Graph Mining
Theoretical Computer Science
Information Systems and Management
Computer Science Applications
And 16 more
About
Dr. Suhang Wang is an Assistant Professor of Computer Science and Engineering at Pennsylvania State University. He received his PhD in Computer Science from Arizona State University in 2018, and his Master's degree in Electrical Engineering: Systems from the University of Michigan in 2013. Before joining Penn State, Dr. Wang was a postdoctoral researcher at the University of California, Santa Barbara. His research interests include natural language processing, artificial intelligence, and machine learning. He was recognized for his work at the International Conference on Knowledge Discovery and Data Mining in 2017 and the Fifth ACM International Conference on Web Search and Data Mining in 2016.

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Osaye Fadekemi, PhD

4 Years Experience
Assistant Professor of Mathematics at Alabama State University with expertise in Graph Theory and Network Modeling
Education

University of Johannesburg

Doctor of Philosophy, Department of Pure and Applied Mathematics / July, 2019

Auckland Park

University of KwaZulu-Natal

Master of Science, School of Mathematics, Statistics and Computer Science / March, 2015

Durban

African Institute For Mathematical Sciences Ghana

Master of Science, Mathematical Sciences / June, 2013

Biriwa
Experience

Auburn University Auburn

Visiting Asisitant Professor / August, 2019 — May, 2021

Alabama State University

Assistant Professor / June, 2021 — Present

Research Expertise (12)
Graph Theory
Network Modeling
Disease Modeling
Discrete Mathematics and Combinatorics
Theoretical Computer Science
And 7 more
About
Dr Fadekemi Janet Osaye is a mathematician whose primary research interest is in graph theory and network modeling. In particular, she is interested in distance measures in graphs and their applications to solving many real-world problems. Her interest in discrete mathematics was inspired by her research project carried out at AIMS Ghana. She has published several articles in reputable journals and has presented in several conferences across the globe. In 2019, she became the first black female to be awarded a PhD in Mathematics by the University of Johannesburg, South Africa, in its 116 years of its existence. Since June 2021, she has been an Assistant Professor of Mathematics at Alabama State University and was previously a Visiting Assistant Professor at Auburn University. She is the founder of GirlsMatics Foundation, a STEM non-governmental organisation for girls in Nigeria which was motivated by her involvement with AIMS Ghana’s outreach programs for high school students in Biriwa, Ghana. She is also the co-founder of FadNna Partners, an analytics and management firm based in Lagos, Nigeria.

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Dr. Justin W. Hart, Ph.D.

10 Years Experience
Professor at UT Austin specializing in artificial intelligence and human-robot interaction
Education

West Virginia University

BS, Computer Science / May, 2001

Morgantown, West Virginia, United States of America

Ph.D, Computer Science / December, 2014

New Haven, CT, Connecticut, United States of America

Cornell University

M.Eng, Computer Science / January, 2006

Ithaca, New York, United States of America
Experience

The University of Texas at Austin

Assistant Professor of Practice / September, 2017 — Present

University of British Columbia

Postdoctoral Fellow / December, 2014 — December, 2016

The University of Texas at Austin

Postdoctoral Fellow / December, 2016 — September, 2016

Research Expertise (12)
Artificial Intelligence
Human-Robot Interaction
Philosophy
Control and Systems Engineering
Social Psychology
And 7 more
About
My research focuses on expanding the places where robots can be deployed. My lab, the Living with Robots Laboratory, has the mission of seeing robots in every home and workplace. To that end, I work on technologies to enable robots to operate in places designed for people, and technologies to enable robots to better interact with people. I am on the executive committee for RoboCup@Home. I am an assistant director of the UT Austin robotics research consortium, Texas Robotics. I am an associate editor for top conferences and journals in robotics. I work on problems relating to autonomous social human robot interaction, artificial intelligence, and robotics architectures.

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Haining Wang

5 Years Experience
Ph.D. candidate specializing in the intersection of privacy and NLP/LLM (https://hainingwang.org).
Education

Wuhan University

Master, Department of Archival Science

Wuhan

Shanxi University

Bachelor, Department of Management

Taiyuan

Indiana University

doctoral student, Department of Information and Library Science

Bloomington
Experience

Indiana University

Research Assistant / August, 2019 — Present

Most Relevant Research Expertise
Natural Language Processing
Other Research Expertise (8)
Large Language Models
Stylometry
Digital Humanities
Open Science
Language and Linguistics
And 3 more
About
Greetings👋 I am a Ph.D. Candidate in Information Science at Indiana University Bloomington. My scholarly inquiries delve into the social dynamics prevalent in privacy, digital humanities, and open science, often through a lens of computational methodologies. I also dedicate significant engineering efforts to developing AI tools for public and community good, including circumventing authorship identification attacks and making scientific knowledge more accessible. I received my master's degree in Archival Studies at Wuhan University.

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Nima Ziraknejad

British Columbia
21 Years Experience
PhD and Co-Founder of Health and Safety Startup
Education

University of British Columbia

PhD, Electrical Engineering - Machine Vision and Robotics / 2014

Vancouver, British Columbia, Canada

University of British Columbia

MS, Electrical and Computer Engineering / 2007

Vancouver, British Columbia, Canada
Experience

NZ Technologies Inc.

Co-Founder & CEO / 2014 — Present

NZ Technologies Inc. (NZTech) is a medical technology innovation and electro-mechanical device production firm with a mission to improve the quality of care and patient outcomes. Focused on revolutionizing modern Human Machine Interfaces (HMI), our systems engineering specialties cover 3D machine vision and sensing, embedded electronics design and assembly, robotics control and manufacturing, and machine learning algorithms. NZTech is proud to have invented TIPSO™, an award-winning product that enables surgeons to touchlessly and ergonomically interact with radiology images and operating room equipment during their surgical operations. As CEO, I am responsible for leadership and operations at NZTech, which includes securing and managing the financing, and making decisions on all strategic activities. My role also extends to cultivating relationships in business, technological and financial spheres to grow business development and productivity. Creating transformative change in the healthcare sector is my passion. I am constantly exploring new horizons and connecting the technologies we have invented to more practical applications in the medical field. My passion and drive to develop new technologies – achieved by understanding users' unmet needs – ensures that we attract highly-skilled experts to our team who have an important contribution to make and who know that something tangible will result from our collaborative efforts.

Auto21

Regional Lead - Western Canada / 2012 — 2014

AUTO21 brings together nearly 200 top Canadian researchers at 46 universities and partners them with 120 industry and government partners. An annual research budget of approximately $11 million in federal and industry support fund projects within six key research themes: Health, Safety and Injury Prevention Societal Issues and the Future Automobile Materials and Manufacturing Powertrains, Fuels and Emissions Design Processes Intelligent Systems and Sensors

Weir Motion Metrics

Product Manager / 2002 — 2009

Research Expertise (24)
Engineering
Robotics
Control
Machine vision
Electric field imaging
And 19 more
About
Dr. Nima Ziraknejad is a Co-Founder and CEO at NZ Technologies Inc., a machine vision and robotics company. He is also the Regional Lead for Western Canada at Auto21, a Canadian national research and development network. Dr. Ziraknejad obtained his PhD in Electrical Engineering from the University of British Columbia in 2014, where his research focused on machine vision and robotics. He also holds a MS in Electrical and Computer Engineering from the University of British Columbia. Prior to his current roles, Dr. Ziraknejad worked as a Product Manager at Weir Motion Metrics, where he was responsible for managing the development and commercialization of new products.

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Example natural language processing projects

How can companies collaborate more effectively with researchers, experts, and thought leaders to make progress on natural language processing?

Customer Service Chatbot

A natural language processing expert can develop a customer service chatbot that can understand and respond to customer queries in real-time. This can greatly improve customer experience by providing instant support and reducing response time.

Text Data Analysis

Companies dealing with large volumes of text data can benefit from collaborating with a natural language processing expert. They can develop algorithms that can analyze and extract valuable information from unstructured text data, enabling companies to gain insights and make data-driven decisions.

Sentiment Analysis

Natural language processing experts can help companies analyze customer feedback and social media data to understand customer sentiment. This can provide valuable insights for improving products, services, and marketing strategies.

Machine Translation

Collaborating with a natural language processing expert can help companies develop machine translation systems that can automatically translate text from one language to another. This can be beneficial for companies operating in global markets.

Voice Recognition

Natural language processing experts can assist in developing voice recognition technologies that can accurately transcribe and understand spoken language. This can be useful in applications such as voice assistants, voice-controlled devices, and speech-to-text systems.