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Behzad Vahedi doing a PhD Residency at X - The Moonshot Factory

Last August I started a PhD residency at  X, the moonshot factory . X is a research and development branch of Google (or more precisely Alphabet).  X  is a diverse group of inventors and entrepreneurs who build and launch technologies that aim to improve the lives of millions, even billions, of people. The goal is 10x impact on the world’s most intractable problem. X approaches projects that have the aspiration and riskiness of research with the speed and ambition of a startup. 

In 2010, Google founders Larry Page and Sergey Brin decided to form a new division of the company to work on moonshots: far-out, sci-fi sounding technologies that could one day make the world a radically better place. It was a grand experiment with ambiguous wording in vision. 10 years in, X website mentions that it has incubated hundreds of different moonshot projects, many of which have gone on to become independent businesses. 

As an AI Resident, I'm engaged in an early stage project where I work on various facets of GeoAI model development and deployment, encompassing everything from model design to DevOps and MLOps practices. This role has afforded me the great opportunity of learning the implementation and deployment of AI models at the forefront of the industry, while also being exposed to the practical, conceptual, and theoretical challenges that emerge due to scalability issues.

My academic background and research in the Geography Department at CU Boulder have been instrumental in preparing me for this role. In particular, courses such as Geospatial machine learning in the Geography Department, along with deep learning courses in the Computer Science and Applied Mathematics Departments, have been significant. Additionally, an equally impactful course, software engineering for scientists, has also greatly contributed to the skills I use on a daily basis in this position.

In light of this experience, I look forward to my return to academia to complete my PhD leveraging the insights and skills I have gained in this role. I am excited to integrate the practical knowledge I have acquired from the industry into my doctoral research.

Behzad Vahedi   page

• Behzad Vahedi

X is Alphabet’s moonshot factory. We are a diverse group of inventors and entrepreneurs who build and launch technologies that aim to improve the lives of millions, even billions, of people. Our goal: 10x impact on the world’s most intractable problems, not just 10% improvement. We approach projects that have the aspiration and riskiness of research with the speed and ambition of a startup.

THE FOUNDATION OF AN AMAZING JOURNEY

Our goal at X is to make the world a radically better place. In order to do that we seek fresh unexpected perspectives, from different fields, and that’s why we’re excited about you. 

Life here isn’t easy, but it’s fun. We’re trying to build things most people can’t even imagine, and we’re doing it with the hope of making a huge, positive impact on the world. You’ll be embedded into a moonshot project, where you’ll partner with team members to solve key challenges. 

This isn’t your ordinary internship. You’ll be positively challenged and pushed professionally, in ways that you may have never experienced. If this excites you - keep reading.

DURING YOUR INTERNSHIP YOU CAN EXPECT:

• To be placed on one of our confidential or public X projects
• To get paid competitively and with Google benefits
• To be part of a lively community of other Interns and Residents 
• To attend colloquium and discussions with team leads from across Google, DeepMind and external organizations
• Location: X's headquarters in Mountain View, CA
• Start Date(s): Year-round rolling basis
• Duration: a flexible 4 mo. to 1 year program based on project team needs and your availability

Job Description: 

A chemical engineering resident with experience in solid-liquid separation, liquid-liquid separation and seawater/wastewater treatment.

• Collaborate with the X Project teams on a pilot-scale process development:
• Develop solid-liquid and liquid-liquid separation methodologies that are optimized for the chemicals generated in the lab.
• Design and conduct experiments to treat wastewater generated in other laboratory processes, with the goal of recovering valuable materials and minimizing waste.
• Perform literature research on industrial separation methods and apply small scale test systems in the lab and develop techno-economic models at different scales.
• Develop standard operation and maintenance procedures.
• Manage vendors and suppliers ensuring components are within specifications and are delivered in a timely manner.
• Conduct interdisciplinary research.
• Engaging with the Intern community during the program, engaging with the X community, attending colloquia and tech talks.

Minimum Qualifications:

• Currently enrolled in a PhD program in a STEM field such as Chemical Engineering, Civil Engineering, Process Engineering, Mechanical Engineering, Materials Engineering or Chemistry with expertise in reactor design.
• Solid understanding of thermodynamics, transport, fluid mechanics, and heat transfer.
• Extensive hands-on experimental and hardware experience related with solid-liquid and liquid-liquid separation and water treatment.
• Experience to create engineering drawings with a fundamental understanding of geometric dimensioning and tolerancing, and ability to interpret various engineering standards (ASTM, EIGA, etc.) to guide designs.
• Effective at navigating ambiguity and managing time constraints in a dynamic environment and strong technical communication skills (presentations/reports) with diverse audiences.

Preferred Qualifications:

• Experience with the construction materials industry or mining and geological engineering.
• Demonstrated large-scale chemical processing project and/or publications in relevant conference or journals
• Experience with one or more general purpose programming languages such as Python, C/C++ etc.

At X, we don't just accept difference - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

If you have a disability or special need that requires accommodation, please contact us at:  [email protected] .

PLEASE NOTE:

This role requires exposure to technologies subject to heightened controls under US export laws.  Due to our immediate need to fill this role and the lengthy process required to obtain export licenses, we will not be able to move forward with anyone requiring a license for such technologies .  This applies to individuals ineligible for license exception "TSR" (commonly described as "controlled-country nationals") under the US Commerce Department's Export Administration Regulations .  As of July 2018, a controlled country national is anyone who is a national of one of the following countries ( excluding US green card holders and US citizens with dual citizenship ):  Armenia, Azerbaijan, Belarus, Burma (Myanmar), Cambodia, Cuba, the People's Republic of China, Georgia, Iran, Iraq, Kazakhstan, Kyrgyzstan, Laos, Libya, Macau, Moldova, Mongolia, North Korea, Russia, Sudan, Syria, Tajikistan, Turkmenistan, Ukraine, Uzbekistan, and Vietnam .  Please review up-to-date information about the Commerce Department's export regulations, including the current list of countries, here .  

The US base salary range for this full-time position is between $118,000 - $145,000 + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.Please note that the compensation details listed in US role postings reflect the base salary only, and do not include benefits.

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As set forth in X, the moonshot factory’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

Thank you for applying to X, the moonshot factory!

Your application has been received. We appreciate your interest in the open roles at X. Our team will review your materials and if there is a fit, a member of our team will contact you with more information.

Maks Sorokin

I'm a fourth-year Robotics Ph.D. student at Georgia Tech, advised by Dr. Sehoon Ha and Dr. C. Karen Liu . I am interested in applications of vision-based robot learning in real-world robotics. Currently, I am working on outdoor navigation and environment interaction problems.

• JUL'23 - Our work on Learning-oriented Robot Design was accepted at IROS 2023 [project page]
• MAR'23 - Check out our latest work on Design a Learning Robot [project page]
• APR'22 - Human Motion Control of Quadrupedal Robots accepted at RSS [project page]
• SEP'21 - Excited to be joining X - the moonshot factory ( Everyday Robots ) for PhD Residency!
• SEP'21 - Check out our work on Learning Sidewalk Navigation [project page]
• MAY'21 - Awarded the fellowship by the Machine Learning Center at Georgia Tech. [link]
• FEB'21 Paper on Learning Human Search Behavior accepted at EUROGRAPHICS'2021! [pdf] [arXiv]
• DEC'20 Paper on Few-shot visual sensor meta-adaptation accepted at ICRA'2021! [pdf] [arXiv]

Research Intern @ The AI Institute 2024 - Present

PhD in Robotics @ Georgia Tech 2020 - Present

AI Residency @ Google X 2021 - 2022

Latest Work

We present a learning-oriented morphology optimization framework that accounts for the interplay between the robot's morphology, onboard perception abilities, and their interaction in different tasks. We find that morphologies optimized holistically improve the robot performance by 15-20% on various manipulation tasks, and require 25x less data to match human-expert made morphology performance.

Publications

We propose a novel motion control system that allows a human user to operate various motor tasks seamlessly on a quadrupedal robot. Using our system, a user can execute a variety of motor tasks, including standing, sitting, tilting, manipulating, walking, and turning, on simulated and real quadrupeds.

We introduce Bootstrap Across Multiple Scales (BAMS), a multi-scale self-supervised representation learning model for behavior analysis. We combine a pooling module that aggregates features extracted over encoders with different temporal receptive fields, and design latent objectives to bootstrap the representations in each respective space to encourage disentanglement across different timescales.

We design a system which enables zero-shot vision-based policy transfer to the real-world outdoor environments for sidewalk navigation task. Our approach is evaluated on a quadrupedal robot navigating sidewalks in the real world walking 3.2 kilometers with a limited number of human interventions.

We train vision-based agent to perform object searching in photorealistic 3D scene. And propose a motion synthesis mechanism for head motion re-targeting. Using which we enable object searching behaviour with animated human character (PFNN/NSM).

We show how vision-based navigation agents can be trained to adapt to new sensor configurations with only three shots of experience. Rapid adaptation is achieved by introducing a bottleneck between perception and control networks, and through the perception component's meta-adaptation.

Image domain adaptation through the conversion of images with randomized textures (or real images) to a canonical image representation. Replication of a RCAN paper with different loss modeling ( Perceptual/Feature Loss instead of GAN loss).

Computer Animation class project, which utilizes off-the-shelf Soft-Actor-Critic Reinforcement Learning method that learns to build up the momentum and swing the animated character on a pull up bar.

Mobile Manipulation project that utilises MoveIt! & GQ-CNN to grasp an object from the table using a Fetch Robot in the Gazebo Simulator.

End-to-end (image-to-steering wheel) control policy learning from data collected over multiple laps with off-the-track recoveries generated by human.

Mentoring Experience

• PRESENT : Master's Student - Jiaxi Xu
• FALL 2021 : Master's Student - Arjun Krishna -> PhD student at UPenn’s GRASP lab
• FALL 2020 : Master's Student - Qian Luo -> NLP Algorithm Engineer at Alibaba Group

Teaching Experience

• FALL 2019 & SPRING 2020 : Head Teaching Assistant
• FALL 2018 & SPRING 2019 : Teaching Assistant

Scholarly Activities

• IROS 2023 - Session co-chair Mechanism Design
• RA-L 2023 - Reviewer at IEEE Robotics and Automation Letters
• RSS 2023 - Reviewer at Proceedings of Robotics: Science and Systems
• RA-L 2022 - Reviewer at IEEE Robotics and Automation Letters
• ICRA 2021 - Reviewer at IEEE International Conference on Robotics and Automation

2023© Maks Sorokin built using Skeleton , icon credits flaticon , hosted by GitHub Pages ❤️ feel free to copy: this page

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PhD student honored as 2024-2026 Jonas Scholar

Jessica Gonzalez, a PhD student at USC College of Nursing, has been named a Jonas Scholar for the 2024-2026 cohort. The Jonas Nursing and American Association of Colleges of Nursing (AACN) initiative aims to expand the pool of PhD and DNP-prepared nurses to educate future nurse leaders. Gonzalez’s research focuses on pain outcomes among minority breast cancer patients.

Why It Matters:

• Gonzalez’s selection underscores her commitment to nursing education and research.
• The Jonas Scholar program provides financial support, mentorship, and a tailored curriculum for aspiring faculty.

What's Next: Gonzalez’s research will delve deeper into pain outcomes among breast cancer patients, with a special focus on minority groups.

What They're Saying: “I am grateful for the support AACN and Jonas are providing to our PhD students,” says Dr. Robin Dail, PhD program director. “Jessica is entering her second year as a PhD student with a promising future, combining her clinical expertise with a desire to contribute as a nurse scientist.”

Personal Journey: Gonzalez began her research journey in 2020, two years after her best friend was diagnosed with breast cancer. Her stepsister was also diagnosed with breast cancer during Gonzalez's master’s program, inspiring her to focus on quality improvement for mammography compliance. Gonzalez herself was diagnosed with breast cancer two days before her USC Nursing DNP program interview, where she discussed breast health promotion projects.

Gonzalez Says: “This scholarship means so much to my personal growth not only as an educator but also as a nurse researcher. It will provide many resources and opportunities to reach my goals and I am grateful for the support of the university, my committee, chair, faculty advisor, pipeline program, and the dean of the College of Nursing for the opportunity to work with the Jonas Scholarship program.”

Challenge the conventional. Create the exceptional. No Limits.

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The sub is currently going dark based on a vote by users. The sub will be back up tomorrow night. Welcome to the Residency subreddit, a community of interns and residents who are just trying to make it through training! This is a subreddit specifically for interns and residents to get together and discuss issues concerning their training and medicine/surgery.

How many of you all plan to go for a PhD once you are finished with residency?

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