Computer Vision Fellow (Hospitality + Travel Focus)

FairwAI building the next-generation platform to improve service optimization, evaluate fairness, and quality control in real-time human service interactions — starting with hospitality. Our aim is to help hotels, restaurants, and service venues deliver equitable, consistent guest experiences across demographics. Backed by experts from MIT, Harvard, and hospitality veterans, we are applying behavioral signal analysis, computer vision, and machine learning to detect and reduce disparities in service delivery.

The Challenge:
Across the hospitality industry, service quality can vary significantly based on perceived race, gender, or age. Bias shows up not only in what is said, but in how guests are greeted, how attentively they're served, and how complaints are handled. These signals often go unnoticed by staff and leadership alike until reputational damage or litigation occurs. Owners of establishments typically can not fully govern their operations unless on site.

The Role:
We’re looking for a mission-aligned Computer Vision Intern to help develop prototype systems that analyze guest-staff interactions from publicly available or synthetic video data. Your work will focus on identifying behavioral discrepancies — such as facial expressions, posture, and attention patterns — and aligning those with service outcomes and guest demographics.

What You’ll Do:

• Build CV models that can detect nonverbal cues in guest-staff interactions (eye contact, gesture frequency, proximity, etc.)

• Explore time-synced behavioral analytics using video and audio inputs

• Use tools like OpenCV, MediaPipe, YOLOv8, and others to process frame-level event data

• Assist in labeling datasets and refining annotation guidelines for hospitality-specific behaviors

• Contribute to a service fairness dashboard or report pipeline shared with partner venues

Preferred Skills:

• Experience with OpenCV, MediaPipe, Dlib, or CV models like YOLO, Detectron2

• Familiarity with behavioral science in service contexts (e.g., body language, micro-interactions)

• Comfort working with video annotation platforms (Label Studio, CVAT)

Awareness of social equity frameworks or interest in algorithmic fairness

Bonus: Understanding of multimodal learning (video + audio/text), or transformers

What Success Looks Like:

• Prototype models or scripts detecting behavioral gaps in guest interactions

• A structured rubric or tagging system for service quality indicators

• Code that feeds into dashboards or scorecards for internal demo

• A well-documented GitHub repo showing your pipeline and insights

Dataset Access:
You will primarily work with:

-Public-facing or synthetic service interaction videos

• Annotated hospitality datasets.

An internal dataset focused on service scenarios at check-ins, tables, and reception areas (fully anonymized, synthetic, and privacy-compliant). No real hotel surveillance footage will be used unless publicly available or explicitly permitted.

What You’ll Gain:

• Exposure to real-world fairness and service optimization tools

• A chance to contribute to tech being used for compliance and guest dignity

• Mentorship from engineers, behavioral scientists, and hospitality executives

• Opportunity to shape tools that may inform certification, reviews, or training

• Improve your skills. If you have no experience with CV you shouldn't apply. This is for people who want to go from a level 6/7 to 9/10.

Who You Are:

Curious and proactive

Python + OpenCV / MediaPipe Proficiency
You must be comfortable writing Python scripts for frame-by-frame video processing. OpenCV and MediaPipe are core libraries used for gesture, facial expression, and movement tracking — foundational to every prototype you’ll build.

Understanding of Nonverbal Behavior in Human Interaction
You need to know what matters in a hospitality setting — gaze direction, distance, posture shifts, delay in response. You don’t need a psych degree, but you need a feel for how these signals map to fairness or bias

Competent in Python-based CV or ML workflows, Knowledge of Computer Vision Models (YOLO, Detectron2, etc.),

Ability to Work with Noisy, Public, or Synthetic Data
You won’t be handed a clean benchmark dataset. Success depends on creatively working with YouTube clips, synthetic interactions, and imperfect

Comfort with Video Data and Annotation Workflows
This includes slicing video, syncing timestamps, cleaning annotations, and integrating metadata. Tools like Label Studio or CVAT are a plus. Much of the insight comes from how well video is structured and annotated.

Motivated by equity and operational innovation

Comfortable with ambiguity and experimentation

Timeline & Logistics:

Duration: 12 weeks, flexible start

Format: Remote (US time zone or Western European time preferred)

Hours: 20–40 hours/week depending on your availability for summer and for fall/spring 10-20hrs

We welcome international students with CPT or OPT authorization. Just let us know in advance

You will work with a multi-disciplinary team:

Shaurjya Mandal – Head of Research, AI Systems & Clinical Innovation
Role: Shaurjya leads FairwAI's research function and the development of its AI methodology — including structured retrieval architectures, sentiment and bias detection systems, and validation frameworks for fairness in clinical and high-stakes AI environments. He ensures FairwAI's research meets the standards of peer-reviewed clinical AI while remaining accessible and useful in real-world deployment.

Bio: Shaurjya Mandal is a machine learning research scientist at Mass General Brigham and Harvard Medical School, where he develops and evaluates AI systems for clinical settings. His research sits at the intersection of responsible AI, healthcare equity, and applied machine learning — with published and applied work in algorithmic bias, fairness in clinical decision support, and AI safety for vulnerable populations. He holds an M.S. in Artificial Intelligence from Carnegie Mellon University, where he conducted research at the Robotics Institute on machine perception and learning systems. Prior to his work at Harvard, Shaurjya served as a research engineer at India's Defence Research and Development Organisation (DRDO) and contributed to AI policy and infrastructure projects across the MENA region, including the design of responsible AI deployment frameworks for healthcare and insurance systems in the United Arab Emirates. He is a Nucleate Pittsburgh fellow, a recognized convener in early-stage biotechnology and AI commercialization. At FairwAI, Shaurjya bridges frontier clinical AI research with practical, ethical deployment — ensuring that what we build for the most underserved populations is also held to the highest scientific standard

Dr. John Cooley – Technical Advisor
Role: Leads FairwAI’s technical architecture, AI compliance engine, and research partnerships.
Bio: Dr. John Cooley is a renowned technologist and serial entrepreneur who holds five degrees from MIT: B.S. in Electrical Engineering, B.S. in Physics, M.S. in Electrical Engineering, an Engineer’s Degree, and a Ph.D. in Electrical Engineering. He earned the David Adler Memorial Thesis Prize and the Morris Joseph Levin Award, recognizing his groundbreaking work in engineering and systems design. John was the CTO and later CEO of Nanoramic Laboratories, where he led the company to raise $100+ in capital and developed cutting-edge battery and nanotechnology solutions. With 15+ years of experience at the frontier of hardware-software integration and AI systems, John brings a rare blend of research rigor and venture-scale execution. He now advises FairwAI on tech architecture, compliance logic, and academic research integration across MIT and international institutions.

Dr. Niousha Roshani – Social Systems Strategist
Role: Co-leads FairwAI’s strategy, focusing on culturally responsive AI, equity frameworks, and global engagement.
Bio: Dr. Niousha Roshani is a leading voice in the intersection of AI, social justice, and public interest technology. She is a former Fellow at the Berkman Klein Center at Harvard University and co-founder of the Center for Democracy Development and Rule of Law at Stanford University. With a background spanning the UN system, Latin American human rights movements, and Stanford’s impact tech community, Niousha brings a transnational lens to algorithmic fairness and ethical design. Her expertise ensures FairwAI builds tools that not only detect discrimination—but empower communities and institutions to address it systemically. Based in Brazil, she anchors our Global South partnerships and pilots. Brazil is the last country in the western hemisphere to abolish slavery.

Dr. Ryan Chin – Strategic Advisor, Urban Tech & Mobility Systems
Role: Ryan advises FairwAI on systems architecture, urban integration, and commercial strategy. He brings expertise in AI-driven mobility, sensor networks, and resilient infrastructure to inform how FairwAI scales across physical environments like hotels, hospitals, and cities.
Bio:
Dr. Ryan Chin is a globally recognized expert in smart cities, urban mobility, and sustainable design systems. He co-founded Optimus Ride, a leading autonomous vehicle company spun out of MIT, where he served as CEO and led the development of self-driving tech for campuses, cities, and business districts. Prior to that, Ryan was Managing Director of the City Science Initiative at the MIT Media Lab, where he pioneered AI-integrated mobility systems and urban computing platforms.
Ryan holds a Ph.D. and two Master's degrees from MIT in Media Arts and Sciences and Architecture. A serial entrepreneur and systems thinker, Ryan has advised Fortune 100 companies, U.S. government agencies, and international city governments on emerging technologies, sustainability, and mobility innovation. He is a frequent keynote speaker at Davos, Smart City Expo, and the UN.
At FairwAI, Ryan supports us with building out our advisory team and the integration of computer vision, IoT, and AI fairness protocols into real-world infrastructure, ensuring our platform is adaptable, sensor-compatible, and aligned with the future of ethical urban technology.

Mike Rinella – Government Affairs & Financial Strategy
Role: Shapes FairwAI’s public policy strategy, unions to get ivolved, government, and compliance market integration.
Bio: Mike Rinella brings decades of experience in public finance, state governance, and strategic planning. He served as a senior advisor to two Governors of New York, including Governor Mario Cuomo, where he worked on economic development, energy regulation, and state-level policy reform. He was also Director of Strategic Planning at SolarFi, helping guide federal partnerships and compliance infrastructure for renewable energy deployments. A graduate of Harvard Kennedy School (’86), Mike is instrumental in crafting FairwAI’s pathways to adoption by Attorneys General, state legislatures, and procurement agencies. He also helps navigate our positioning with foundation-aligned capital like PRIs and MRIs.

Carson Smuts – IoT & Hardware Integration Advisor (MIT Media Lab)
Role: Advises on spatial sensing, IoT systems, and architecture for real-world monitoring.
Bio: Carson Smuts is a Senior Research Scientist at the MIT Media Lab’s City Science Group, where he has spent over a decade developing sensor platforms, digital twins, and hardware systems that interact with real-world environments. He co-created the CityScope urban simulation platform and led the design of MIT’s Environmental Sensing Infrastructure, a foundational piece of the lab’s smart city research. Trained as an architect at Columbia University, Carson transitioned into full-stack engineering with a passion for embedding fairness into built environments. He guides FairwAI’s integration with CCTV, IoT sensors, and spatial computing to power real-time bias detection in travel, healthcare, and hiring.

Dr. Taj Ahmad Eldridge – Strategic Advisor, Capital & Climate Justice
Role: Taj advises FairwAI on capital formation, social impact investment strategy, and ESG-aligned growth. He brings deep expertise in climate finance, racial equity, and fund structuring—ensuring FairwAI’s monetization models and funding pathways align with both mission and market.
Bio:
Taj Ahmad Eldridge is a leading voice in climate justice investing and equitable capital innovation. A former Senior Director of Investment at the Los Angeles Cleantech Incubator (LACI), Taj has helped deploy hundreds of millions of dollars toward sustainable technologies and underrepresented founders. He is currently Managing Partner at Include Ventures, where he builds investment vehicles that close wealth gaps and accelerate climate solutions—particularly in communities historically excluded from capital access.

With 20+ years of experience in banking, venture capital, and fund management, Taj has advised funds and institutions including the Ford Foundation, MacArthur Foundation, Elemental Excelerator, and Capria Ventures. He is also a Senior Advisor to Jobs for the Future (JFF) and a board member of multiple national investment networks and ESG platforms.
Taj’s unique strength lies in combining climate policy, community wealth-building, and financial engineering to drive systems-level impact. As an advisor to FairwAI, he supports efforts to build revenue models rooted in risk mitigation, government accountability, and regulatory tech—while helping ensure capital raised aligns with the venture’s vision of equity-first compliance.

Stipend: Unpaid, but eligible for school credit and includes mentorship, reference, and portfolio support. The goal is to turn this into a paid role but it is not promised.

Top-performing interns will be:
Referred to graduate fellowships or full-time impact AI roles.
Eligible for future paid positions with FairwAI or its nonprofit arm if funding is available.
Supported in publishing or presenting findings at tech and policy forums.

FairwAI strongly encourages applications from women, BIPOC, LGBTQ+, first-gen, and underrepresented groups in tech. We believe those most impacted by bias should help design the systems that fix it.