We are Clear

About Me:
Hi Everyone! I’m Jay, currently based out of Los Angeles but originally from Princeton, New Jersey. I graduated from UCLA three years ago and have since been working at FTI Consulting, focused on Media & Entertainment M&A Advisory. My specific interest in venture capital and entrepreneurship arose during my data analytics-related projects at work. At FTI, I built several data processing products and data warehousing mechanisms to enhance internal efficiency. Eventually, I had the experience of successfully pitching and selling these products to clients, which was thoroughly fulfilling. My particular interests for future projects center around the intersection of web3 and media platforms. My non-professional interests include sci-fi/fantasy, playing guitar, investing, and camping.

Mbogo has aspirations to be a company builder. University of Michigan BE, CS. 3x Varsity Letter Winner in Lacrosse. SWE at Sofi and Sleek. Interesting intersection of CS and Sales Experience + Finance.

JPM Chase. First Generation College Student, finished AA degree before graduating HS. MS in Biomedical Engineering from Carnegie Mellon. BS in Chemical Engineering from Carnegie Mellon University.

Infrastructure Engineer at Stripe. Investor at Contrary Capital, Kleiner Perkins Engineering Fellow.

About Me:
Hi, my name is Charles, I’m currently a first-year MBA student at Chicago Booth and originally from the Bay Area. I attended the University of Michigan where I studied Computer Science and Mathematics. Prior to Booth, I was a Forward Deployed Software Engineer at Palantir Technologies based in Palo Alto, CA. I worked as Technical Lead under our Business Development umbrella on Palantir’s deployment projects for US and international commercial clients. I worked with client businesses in energy, cyber & physical security, transportation, consulting, manufacturing, and telecommunication.

I’ve been interning with Clear Ventures since the start of 2022. I am focused on our open source and AI+X investment portfolio, and perform research and portfolio services work.

In my free time, I enjoy playing soccer, running, and learning about new products and technologies.

Hi, my name is Srishti and I’m a first year MBA student at the University of Chicago Booth School of Business. Prior to Booth, I was working as a data scientist at Spotify. I’m very excited about applications of AI in the future of work and Web 3.0. Looking forward to meeting you all!

About Me:
I’m a first-year MBA student at Chicago Booth who calls Singapore and New York home. I currently work as a product manager at a seed-funded networking platform bringing professional communities together. Prior to Booth, I worked in portfolio management at BlackRock in New York and a biotech VC in Palo Alto. In my free time, I enjoy painting, darkroom photo developing, and running.

I’m currently leading the largest annual technology conference at Booth (TechCon), with a focus on web3 and responsible AI for this year’s TechCon. Having been a classically trained painter, I am also very interested in AI’s applications in art and how NFT could be used to empower artists and democratize the art industry. Looking forward to meeting everyone!

Alberto is a from Puebla MX, grew up in North Carolina. Fluent in Spanish + Portuguese. Interested in Venture, particularly the intersection of ML and Life Sciences (Therapeutics). He is working with CLEAR this fall as an Post-MBA Intern.

Dileka is a Statistics PhD student at Stanford University who is passionate about machine learning and causal inference. As an undergraduate at Rice University, Dileka won first place in the International Conference on Establishment Statistics (ICES) Student Contest.

Austin is a Materials Science PhD student at Carnegie Mellon University. He researches hydrogel and organogel soft materials and is dedicated to developing the world’s first waterproof BTE cochlear implant. Austin is also the Founder and CEO of SilkyAI, a mobile application designed to eliminate global food waste using at-home ingredients.

Carlo is a Robotics PhD student at UC Berkeley and Researcher at the Berkeley AI Research Lab. Carlo’s interest lies at the intersection of robotics, multi-agent systems and machine learning.

Carlo obtained a Masters in Science with Honors in Robotics from Sant’Anna School of Advanced Studies and the University of Pisa, Italy. He has also conducted research at EPFL (Switzerland), Stanford University (USA), and TBSI (China).

Originally from Chicago, Nina is an undergraduate at Stanford University studying computer science on the AI track. She is the Founder of Stanford Women In Tech Entrepreneurship, which has over 150 active members.

As a Research Assistant at the Stanford Intelligent Systems Laboratory, Nina has published a paper on autonomous validation simulations. Passionate about climate, automation, and healthcare, she has worked for three startups and is currently a software engineer at Nuro, an autonomous delivery unicorn.

Anchit is the co-founder of Metcalfe.capital, a micro venture capital firm focused on Web3. He has previously worked with multiple web3/ fintech startups including Koii Network and Jiraaf. He began his career in financial markets at Goldman Sachs and later did investment banking at Jefferies.

Anchit recently graduated from the MBA Program at UC Berkeley Haas School of Business, where he used to lead the Haas Blockchain Club. He also has a Bachelors and Masters degree in Electronics Engineering from IIT Roorkee.

Johnny Chang is a Masters student at Stanford University studying Computer Science on the AI track. As a Graduate NLP Researcher, he is rethinking data science with LLM.

Specialized in robotics and AI, Johnny is focused on applying AI to education and climate tech and has founded several organizations for educators and entrepreneurs across the US and Taiwan.

Originally from Dubai, Manan Gupta is an undergraduate at Stanford University, studying Mathematical and Computational Science and Economics. He is very interested in the Future of Money and Payments, and is has been exploring Assured Payments as a Research Assistant at the Stanford University Graduate School of Business.

He is interning this summer as a Product Engineer at zSpace, an AR/VR edtech startup. Previously, he was an Data & Product Intern at Bayt.com, the Middle East’s leading job search site.

Shivam is a Machine Learning Software Engineer at Google. He has a dozen machine learning and computer vision based projects to his credit and has been actively pursuing work in machine learning both in implementation and research domains.

Shivam was a Visiting Researcher at MIT, Caltech, and the University of Cambridge and holds a Master of Science in Computer Science from Carnegie Mellon University.

Olivia Wang is a student at Stanford University pursuing an undergraduate degree in Symbolic Systems (with a focus on Human-Computer Interaction Design) and a Master’s in Sustainability Science and Practice.

From technical computer science courses to futuristic design-thinking classes, she has spent the past few years building technology and designing elevated user experiences. With these skills, she is now on a mission is to decarbonize the world and default sustainability.

Bailee is interested in applying optimization, mechanism design, and network analysis to fields that lie at the intersection of economics, finance, and technology.

Bailee started her career at Goldman Sachs, followed by the Federal Reserve Bank of New York. She received her MS from the Industrial Engineering and Operations Research school at Columbia University in New York City.

Francesco Marchioni is a Mechanical Engineering PhD student at Stanford University, focused on plasma physics, space propulsion, and nuclear fusion. His research has appeared in the Journal of Applied Physics and at the Space Propulsion Conference.

Previously, Francesco was the Innovation Fellow at Thales Alenia Space, where he identified new venture opportunities in the space industry. He also co-founded two AI startups, Mantisworks and Neuracity.

Mallika is a Master’s student in Computer Science at Stanford University. She is interested in theoretical machine learning, human-AI interaction and AI governance.

Prior to Stanford, she studied Computer Science at UC Berkeley, where she worked with Professor Ken Goldberg in the Berkeley Artificial Intelligence Research Lab on problems at the intersection of robotics and machine learning. She has worked on building robotic systems to autonomously untangle cables and efficiently plan multi-object grasps, co-authoring work published in the Conference on Robot Learning (CORL) and the International Conference on Intelligent Robots and Systems (IROS). She has previously interned at Meta and Abacus.Ai, working on reels ranking systems and anomaly detection.

Nathan C. is a dedicated student at Stanford University, pursuing a Bachelor of Science degree and specializing in the fields of biomedical AI and NLP. He has a strong track record in academia, having worked as a Research Intern for the Stanford Chirpy Cardinal Team, a Research Assistant in the Open Virtual Assistant Lab, and a Research Assistant in the Wall Lab at Stanford University. Nathan’s passion for research extends beyond Stanford, as he has also contributed to projects at Yale University, Harvard Medical School, and Meta. Furthermore, he serves as the Co-President of the Stanford Association for Computing Machinery, reflecting his leadership and commitment to the field of computer science.

Keren D is a data science enthusiast with a solid educational foundation, holding a Bachelor of Science in Data Science from the University of California, Berkeley. With an impressive work history, Keren has worked in diverse roles, ranging from her role as an Undergraduate Research Assistant at UC Berkeley to her positions as a Technical Program Manager at Google. Her multifaceted experience also extends to her involvement as an Investor at Rough Draft Ventures, showcasing her deep understanding of technology, data, and program management.

An interdisciplinary engineer, entrepreneur, and researcher working at the intersection of learning science and artificial intelligence. Merve’s current research aims to develop computational models of human digital behaviors and their relationship to executive functioning, with the long-term plan to understand and improve human learning and wellbeing at the nexus of engineering, social sciences, humanities, and medicine.

Holding a Bachelor of Science in Mechanical Engineering from the University of Florida and currently pursuing a PhD in Mechanical Engineering at Carnegie Mellon University, TJ is committed to academic and technical excellence. His work experience spans diverse research and industry roles, including Research and Development Hardware Engineer at Amazon Global Robotics, Graduate Researcher in the Microrobotics Lab at Carnegie Mellon University, and an Audio Product Design Intern at Apple, showcasing his passion for technology.

Aahil is a highly skilled software engineer with a strong educational foundation, holding a Masters of Engineering degree from Imperial College London. With an impressive work history, Aahil has contributed to both academia and industry, having worked as a Software Engineer at Google and as a Personal Programming Tutor at Imperial College London. His passion for innovation also led him to internships as a Machine Learning Engineer at Synthesized and a Software Engineer at Augnito, where he honed his expertise in cutting-edge technologies.

Clinton is an accomplished computer scientist currently pursuing his Master’s degree in Computer Science at Stanford University, building on the strong foundation he laid with a Bachelor’s degree from the same institution. Clinton’s passion for education is evident through his role as Head Teaching Assistant at Stanford and as a CS 105 Teaching Fellow Coordinator at the National Education Equity Lab. In addition to his academic contributions, he has gained valuable industry experience as a Software Engineer Intern at Lyft and Twitter, while also bringing his technical skills to Figma as a Software Engineering Intern. Clinton embodies the spirit of both academia and industry, making significant strides in the world of computer science and technology.

Mainak G is a versatile professional with a strong educational background, holding a Bachelor of Science in Electrical Engineering from Yale University and an MBA from MIT Sloan School of Management. He has a multifaceted career, including roles as an independent strategy consultant, investor at Stellaris Venture Partners and Saison Capital, and experience in data science and strategy with Engineers Gate and Goldman Sachs. His diverse skill set and experience make him a well-rounded contributor to the worlds of business, technology, and finance.

Favour N is a dedicated and highly educated individual, currently pursuing a PhD in Electrical Engineering at Stanford University, following her Bachelor’s degree in Computer Engineering from the University of Maryland. Favour has a strong research background, with roles as a Graduate Research Assistant at Stanford, and prior experience as an Undergraduate Research Assistant at both the UMD Department of Computer Science, NASA Harvest, and NASA Jet Propulsion Laboratory, reflecting her passion for cutting-edge technology and scientific exploration.

Shiladitya is an up-and-coming talent, currently pursuing a Bachelor of Science in Electrical Engineering and Computer Science at UC Berkeley’s College of Engineering, set to graduate in 2024. He’s been an active participant in the world of research, with internships in esteemed institutions such as the Berkeley Artificial Intelligence Research Lab, the Alaa Lab at UC Berkeley, and the University of California. Additionally, Shiladitya has honed his skills as a Software Engineer Intern at Amazon, showcasing his commitment to technological innovation.

Currently pursuing his MS in Electrical Engineering at Stanford University, specializing in AI / Machine Learning. For the last 2 years, Emil worked at Microsoft as a Data & Applied Scientist in the Cybersecurity research team. Previously, he graduated with a Bachelor’s degree in Electrical Engineering and a minor in Deep Learning from IIT Madras. During this time, Emil pursued research at the intersection of NLP and deep learning that led to publications at top conferences such as ACL, COLING and ALENEX. His primary research interests are in Interpretable Machine Learning, NLP and Deep Learning/LLMs.

Sai is a driven professional with a strong educational background, holding a Bachelor of Technology in Electrical Engineering from the prestigious Indian Institute of Technology, Bombay. Her journey through academia and industry is marked by her roles as an Undergraduate Research Assistant and Teaching Assistant at IIT Bombay, showcasing her commitment to learning and education. Sai has also gained valuable industry experience, with internships as a Hardware Engineering Intern and a STEP Intern at Google, demonstrating her expertise in cutting-edge technology and engineering.

Anirudh graduated top of his class with B.Tech in Electrical Engineering from IIT Madras and is currently pursuing his Masters degree from Stanford University. Anirudh’s academic pursuits are centered around cutting-edge topics such as 2D & 3D Computer Vision, Natural Language Processing, Multimodal Machine Learning, as well as the practical applications of edge-computing and on-device ML. Additionally, he is also interested in understanding and mitigating failure modes that limit the robustness and reliability of Neural networks.

Gabriela A is a driven student on the Artificial Intelligence track within Stanford University Symbolic Systems program, set to graduate in 2024. Her academic journey is complemented by diverse experiences, including an Engineering Product Management internship at Chime, research contributions as a Research Assistant at the Stanford Vision and Perception Neuroscience lab, and internship roles at Bain & Company and Meta University, showcasing her commitment to technology, research, and business development.

Dr. Aakash, a postdoctoral researcher at Stanford University, specializes in deep learning and mathematical modeling for complex scientific and engineering challenges. His Ph.D. in Computational Mathematics from Mines ParisTech – PSL led to innovative deep learning methods for turbulence modeling and the creation of a high-performance CPU-GPU framework for deep learning-assisted simulations. He co-founded Green Panda in 2014, a dynamic web solutions provider in India, and exited in 2019 after 5 years of successful operations.

Chris is a 2nd-year PhD student in Computer Science at Stanford University advised by Jeannette Bohg and Marco Pavone. He is a member of the Stanford Artificial Intelligence Laboratory, the Center for Research on Foundation Models, and works jointly with the Interactive Perception and Robot Learning Lab and the Autonomous Systems Lab.

His research investigates how robots can feasibly and efficiently plan for any task through learning.

Neil is a Ph.D. Candidate at Stanford University in Computer Security, Privacy, and Public Policy advised by Dan Boneh.

Neil received a Bachelor’s Degree with a triple major in Computer Science, Economics, and Applied Mathematics (Cryptography) from the University of Wisconsin-Madison along with honors in Liberal Arts. He has held internships for Netflix and the Wisconsin State Assembly. Neil is a SETR Fellow at the Hoover Institution.

Sanket is a Computer Science Ph.D. student at Stanford University. He works at the Medical AI and Computer Vision Lab (MARVL) led by Prof. Serena Yeung. His current research is focused on using Computer Vision and Deep Learning for cellular imaging to study the impact of neurodegenerative and viral diseases on the molecular machinery of the cell. His previous research spanned multiple domains including Computational Genomics, Proteomics, and Parallel Computing.

His primary focus is the development of label-efficient Computer Vision methods for high-resolution 3D data. He leverages approaches from self-supervised and semi-supervised learning, active learning, and domain adaptation to build robust models which generalize well, even across noisy datasets and domain shifts.

Nick began his career at TE Connectivity, developing
advanced sensing technology for consumer devices to
autonomous vehicles. As a product manager, he saw
firsthand how digital and physical technologies collided
to evolve industrial operations and business models.

Nick went on o join an early-stage industrial AI startup,
Aitomatic, to help lead enterprise sales and business
development. Before TE, Nick received his B.S. in MechE
from the University of Maryland.

Kabir entered college at age 13 through the Early Entrance Program at
Cal State LA. Since then, he has been working on research in the field of
machine learning both in industry and academia. Some highlights
include his work with Apple, CSULA’s Data Science Research Lab, the
ADALab at UCSD, and SVCL at UCSD.

Kabir has been the recipient of numerous awards including UCSD
Excellence in Research Award, CRA Outstanding Undergraduate
Researcher Honorable Mention, Jacobs School of Engineering
Fellowship, and the Halicioglu Data Science Institute Fellowship. Kabir
was a contributor to Siri’s invocation systems. Most recently Kabir
worked on the Machine Learning platform team at Netflix.

Tathagat is Masters student in CS at Stanford University specializing
in Artificial Intelligence. Prior to that he completed his Bachelors in
CSE at IIT Bombay.

Tathagat is deeply passionate about startups and making ubiquitous
products leveraging AI to solve real world problems. He has a
background in AI through publications and projects in domains like
deep generative models, medical image processing and NLP.
Tathagat has held internships at Microsoft, and Coupa.

Ashwin specializes in applications of AI in the construction
industry and has also worked on a number of special projects
alongside McKinsey & Co. and the World Economic Forum. Ashwin
is a researcher at SAIL under the tutelage of Andrew Ng. He
attended IIT Bombay and received a B Tech in Civil Engineering.

Jian holds a Bachelors of Technology in Electrical Engineering
from the Indian Institute of Technology, Bombay. He is currently
completing his master’s degree in Computer Science with a
specialization in Artificial Intelligence from Stanford University. Jian
works in the Stanford Artificial Intelligence Laboratory researching
tractable inference in multi-agent reinforcement learning,
imitation learning, and experimental design.

Nikhil holds a Bachelors of Science in Computer Science
from Stanford University and is currently finishing up his
Masters of Science in Computer Science at Stanford. Nikhil is
a researcher in Stanford Medical AI and Computer Vision Lab.
Where he worked alongside Leonidas Guibas and Prof.
Serena Yeung. He is currently a Computer Vision Intern at
Matroid, Inc. Nikhil is interested in machine learning
research, software development, and computer science
education.

Anthony is currently working towards his Bachelors of Science
and Masters of Science in Engineering at UPenn.Anthony plays
on their division one football team and does research on
optimization frameworks for quantum compilers and processors.
Anthony has held internships at Goldman Sachs, Microsoft, and
InstaHub.

Sundar is a 4th year PhD student in the Computer Science
department at Stanford University. He has been a Research Intern
and later on a part-time Student Researcher in the Network
Infrastructure team at Google Cloud. Prior to starting his PhD he
spent a couple of years as a Research Fellow at Microsoft Research
India working with Dr. Venkat Padmanabhan on the automated
debugging of wide-area network (WAN) degradations in the
context of Internet-scale “always online” services.

Samarth holds a Bachelors of Technology in Computer
Science from the Indian Institute of Technology, Delhi as well
as a Masters of Science in Computer Science from the
University of Illinois Urbana-Champaign. During his time at
the University of Illinois he worked as a graduate teaching
assistant. In addition, he worked as an applied research
scientist intern at Meta. Samarth is currently in a full time
software engineer position at Glean.

Qasim holds a bachelor’s degree in Computer Engineering
from Virginia Tech. Qasim has held internships at Infinitus
Systems, and Qualcomm where he worked on chip
optimization using graph based deep learning. At present
Qasim is now a Machine Learning engineer at Path AI. Qasim
is deeply interested in early stage startups.

Lee holds a Bachelors of Science in Computer Science and a
Masters of Science in Management Science and Engineering from
Stanford University. During her time at Stanford, she was a
teaching fellow and held internships at New York City Cyber
Command, Intuit, and The University of Hong Kong. Lee is
currently a growth manager at Rippling. Formerly she was a
project manager for Women in SpaceIL at the Parasol Foundation
Trust. In her role, she managed collaboration to create a $500k
project increasing female participation in Space and Aeronautics.

Hari is wrapping up his PhD in Computer Science at Cal
Berkeley. Hari has research expertise in generative AI, deep
learning, computer vision, transfer learning, time-series
modeling, IoT, and smart buildings. Hari holds a Bachelors of
Technology in Electrical Engineering from the Indian Institute of
Technology, Kharagpur. Hari has held internships at ByteDance,
Amazon, and Airbus. Hari was a MTS at Mentor Graphics.

Gautam received his bachelor’s degree from UC Berkeley in
Electrical Engineering and Computer Science. After the
completion of his bachelor’s, he went on to pursue a Masters of
Science in Computer Science at Stanford University. Gautam is
currently a researcher in Stanford’s Artificial Intelligence
Laboratory. During undergrad he was a researcher in the Berkley
RISE lab. Gautam has held internship positions at Tesla and
Google.

Building an end-to-end continuous security company for ML Models. Researched 3D Shape representation and generation under Olodapo Afulani and Shankar Sastry at BAIR. Worked with Nicholas Carlini on a research project involving evaluation of adversarial example detectors at Google. Published at ICLR 2022. Berkeley M.E.T.

Stanford PhD, advised by Chelsea Finn. Focused on NLP and ML. Member of BAIR lab during undergrad program at Cal Berkeley advised by Sergey Levin and Dan Klein.

Stanford Postdoc ML Researcher interested in Generative Models and Time Series, Advised by Percy Liang. University of Washington PhD & Ms in CS.

Soumya is working on his PhD at Stanford. He is a member of the Kundaje Lab, his research focuses on the genetic and molecular basis of neurodegenerative /psychiatric disorders.

Walmart Labs reporting group, working in Big Data. Stanford MSCS with AI Concentration. Explainable AI at Lenovo – using language models to classify customer support cases. Interested in AI, Big Data and Web3. Talented musician!

Working at Google AI as a Research Scientist. Stanford PhD focused on NLP and Health Care Applications. Advised by Chris Re on some projects related to Non-Euclidean Machine Learning. Worked on RoBerta while at FAIR, Xuedong Huang’s team at MSFT.

Former member of the Stanford Open Virtual Assistant Lab, worked under Monica Lam on Genie, OSS privacy preserving virtual assistant platform. SWE specializing in ML/NLP. Stanford PhD. ML Researcher at Bardeen.

Okan works in the research group led by Professor Amin Arbabian in the EECS department at Stanford University. His work covers circuit and system design for biomedical, sensing, and Internet of Things (IoT) applications.

Okan is working at the intersection of ML/Sensors/Robotics. Stanford PhD. From Turkish Capital Ankara.  

Currently a Stanford Post-doc researcher in the ILIAD lab. Research interest lies at the intersection of ML and Human-Robot Interaction. FAIR AI Resident.

Meet Asim. ?

Asim Hirji, one of our DeepTech Fellows, has been part of a successful exit as a Founding Engineer and may have his own start-up in the works. 

“There were always ups and downs when getting started on AccessBell. It was like raising a baby,” Asim says of his first start-up experience. Asim assisted in building their B2B integrated video software – a solution built to bolster telemedicine and remote healthcare services. Having a front row seat from beginning to exit at this successful start-up inspired entrepreneurship in Asim. “I’m more ingrained in entrepreneurship now. I used to be very corporate and software focused. For now, I am maintaining strong relationships in Silicon Valley and will see where it takes me.” 

Asim just finished his Masters in Computer Science at Georgia Tech and has an impressive engineering resume. 

CLEAR Fellowship Reflection

“I’ve been able to talk through strategy, get help reaching out to firms for fundraising, and gain access to a supportive group through this Fellowship. It’s been very eye-opening looking at DeepTech through the VC lens versus the engineer or founder perspective.” 

Advice from Asim 

“You’ll hear no a lot more than you’ll hear yes. Don’t get let down by that.”

Meet Jiaming. ?

Jiaming Song’s interest in DeepTech was sparked by a Machine Learning advisor at Duke who introduced him to ML research opportunities. Now Jiaming is an ML/AI research scientist at NVIDIA, has a PhD in Computer Science from Stanford, and is part of our CLEAR Ventures DeepTech Fellowship. 

Jiaming has over 45 publications under his belt and has experience in various ML/AI research projects – from positions at Microsoft Asia, Facebook, Duke, and postdoctoral at Stanford. 

The DeepTech topics that Fellows are presenting to the group, such as AI safety, have inspired new research ideas for Jiaming. “At NVIDIA, I have a lot more resources at my disposal to execute research, think of experiments, and actually implement those ideas.” 

CLEAR Fellowship Reflection

While Jiaming has clear expertise in ML/AI research, he wanted to learn more about what was happening in DeepTech outside of his research area. “This diverse network of Fellows has opened me up to VCs, and startups, and made me think about my career development long-term.”  

Advice from Jiaming 

“Get your hands dirty. Hands-on experience is invaluable.” 

Meet Sunwoo. ?

Sunwoo Lee has been busy in her Co-Founder role at Cromatic while participating in the CLEAR Ventures DeepTech Fellowship. Sunwoo has recently announced that Cromatic raised $1M in their pre-seed round (congratulations!). 

Prior to founding Cromatic, Sunwoo had internships at two early-stage B2B startups while pursuing her Bachelor’s and Master’s degree at Stanford. “I enjoy the early startup space because of how much impact you can have on the company, the product, the branding, etc. My voice matters when I’m on a small startup team and that matters to me.” During her senior year, she had her first co-founder experience, and while this startup didn’t stick it taught her the thrill and pace of the startup space and what it took to be a founder. 

Sunwoo and a Stanford PhD friend came together to start Cromatic three months ago and soon after convinced another classmate to serve as their CTO. “All of our backgrounds blended nicely to make this solution. The problem we are trying to solve deserved each of our expertise – in bio, AI, and SaaS.” Cromatic’s mission is to make meaningful research possible without physical labs. “With the virtualization of life-sciences research, outsourcing R&D has become more important than ever. But innovation in the space has been slow—scientists still face significant challenges finding and working with outsourcing partners that detract from the science.” 

CLEAR Fellowship Reflection 

“Chris Rust’s seminar to the Fellows about hiring and recruiting couldn’t have come at a more opportune time. It was exactly what I needed because we were hiring at Cromatic. He gave great advice and insights about hiring the right talent to help your startup grow.” 

Advice from Sunwoo

“The team is always going to be stronger than the individual so you need to find the right co-founder, the right team, and unlock everyone’s potential. They are going to be the reason you are excited and inspired to work hard.” 

Meet Aman. ?

Aman Kishore always asks himself “how much impact can I make?” and that question has guided his work on Autonomous Vehicles at NVIDIA to launching his start-up Mirage. We are glad to have Aman in our inaugural CLEAR Ventures DeepTech Fellowship. 

Aman saw his work on Autonomous Vehicle Perception at NVIDIA as a chance to save hundreds of thousands of human lives each year. Aman helped grow the synthetic data NVIDIA team from 3 to 8 people to help improve AV. But he couldn’t ignore the severe limitations he was witnessing with the computer vision data pipeline. 

He saw the bottleneck that perception engineers were constantly facing because of the time it takes to make real progress on computer vision applications. “If the quality of the data isn’t high, the model will not improve. It’s a huge challenge to fill in failures and edge cases to improve models.” Aman wanted to solve this problem to move the industry forward faster. *Enter Mirage.* 

Aman’s main vision with Mirage is to accelerate the development of groundbreaking technologies by speeding up the data pipeline. The platform supplements weak points in synthetic data automatically so months of effort from an engineer is virtually removed. “The direct impact is that robotics, autonomous vehicles, AR, VR, drones, and other technologies can actually come to market. It feels like no end is in sight for these technologies because iterations are so slow. With Mirage, you can accelerate these applications.” 

From the CLEAR team, congratulations on launching Mirage! 

CLEAR Fellowship Reflection

“This Fellowship reinforces entrepreneurship. Being a first time founder is challenging because there’s so much you don’t know. You have to jump off the cliff. This didn’t feel so daunting because CLEAR is DeepTech focused so they can provide hands-on help with what I’m building and working on. And the introductions to other founders and VCs have been extremely valuable.”  

 Advice from Aman 

“Be shameless in your networking. Meet as many people as possible and help others because you never know what help you’ll need in the future.” 

Meet Daniel. ?

Daniel Bashir is an integral part of our inaugural CLEAR Ventures DeepTech Fellowship. He brings a unique perspective to our program from his research at Harvey Mudd in applied Deep Learning, internship as an Applied Scientist at Amazon & current role as an ML Engineer at a Stealth Startup. 

While research and technical work are part of Daniel’s typical day-to-day life, the social impact and ethics of AI interest him too. Daniel has the opportunity to explore these subjects through his role as an Editor at The Gradient where he interviews AI researchers and practitioners on topics such as common sense, moral reasoning, and consciousness in AI. 

In addition to exploring ethical and responsible AI, Daniel is enjoying his first experience as an operator at a leading Startup in the Valley. “There are really no boundaries when you are at a startup. Your days always look different and you’re encouraged to jump around teams and projects to keep things moving forward. This environment might not be for everyone, but I’ve loved getting to learn by working on projects that I would not have been able to otherwise.”

CLEAR Fellowship Reflection

Daniel has always been interested in startups and entrepreneurship as a way to make an impact in DeepTech. “This Fellowship has been a great way to expose myself to startups, see what it looks like to be a founder, and learn more about the VC industry.”

Advice from Daniel

“Be flexible, adaptable, and willing to go out into the world, try things, and figure out what works for you.”

Meet Nkechi. ?

Nkechi Iregbulem is an early stage investor at 24VC with an impressive portfolio of companies such as Resourcely, Kasheesh, and 15+ others. We’ve enjoyed bringing Nkechi into the DeepTech space from her Fintech background in the CLEAR Ventures Fellowship. 

While Nkechi has always been deeply immersed in Fintech, the explosion of Web3 sparked her interest in the DeepTech space. From an investor perspective, she’s learned through the Fellowship that it takes a long time to get ML into production so companies that accelerate the productivity of ML models are very compelling to her. “This has opened the doors for me to invest more into DeepTech.” 

CLEAR Fellowship Reflection

“I’ve used this opportunity to learn about topics such as AI and ML that I didn’t have much familiarity with. If I wanted to invest in DeepTech, I now know what questions to ask founders. It’s so important to be knowledgeable, ask the right questions, and not take everything that founders say at face value in order to make smart investments.” 

Advice from Nkechi 

“Be open to learning and be a student of life.” 

Meet Kevin. ?

Kevin Lu has had a fascination with AI since high school so it’s no surprise that he now is an AI resident at Meta and is beginning his PhD studies in Robotics and Decision-Making at Stanford this fall. It has been a pleasure having Kevin in our inaugural class of DeepTech Fellows. 

Kevin combines his AI knowledge with his engineering sense in his role at Meta. “There is so much creation in this field. It excites me how much we can accomplish with DeepLearning.” 

Come fall, Kevin commences his PhD studies and is excited to explore DeepLearning topics and ideas (with freedom and depth!). “This is going to be a great opportunity to learn new things and work more long-term on projects.”   

CLEAR Fellowship Reflection

“The CLEAR Fellowship is teaching me to be prepared for opportunities and capitalize on them. It’s been a pleasure meeting like-minded people and getting an inside look at Venture Capital.” 

Advice from Kevin

“There are so many resources out there now. If you’re interested in the AI space, this is a great time to self-study online to get a foot in the door. I self-studied code and the basics of AI in high school and was able to improve on these skills with formal education and research mentors.”