Welcome new MLCommons public members, please introduce yourself!

[David Kanter]

Hi Everyone,

Happy new year - I hope everyone is looking forward to a great 2021. I'm really excited for a vaccine and resuming our community meetings :)

I want to welcome all the new members! Since this is a fully open and public mailing list, this is a thread for introductions. This is an opportunity to tell the community about your background, areas of interest, and any interesting ideas you might have.

I'll start - I'm a founder and the executive director of MLCommons, and you can find me on LinkedIn (https://www.linkedin.com/in/kanterd) and many of my writings are online at Real World Tech (www.realworldtech.com).

In the past, I helped to lead the Inference, Mobile, and Power working groups, and I attend many of the meetings currently, including Datasets and Best Practices.

I'll look forwarding to working with many of you in the future. Here's to a great 2021 and beyond!


Thanks,


David Kanter

Executive Director

MLCommons

[Dan McLeran]

Hello. My name is Dan McLeran. I am a Principal Engineer at Intel working in their non-volatile memory group (i.e. SSDs). I've worked in storage since 1998, then at Seagate. I've spent the past 2-3 years developing a C++ template library to run neural networks and machine learning algorithms within embedded systems. See https://intel.github.io/cppnnml/

Also see my article on LinkedIn(https://www.linkedin.com/in/danmcleran/):

https://www.linkedin.com/pulse/table-based-q-learning-under-1kb-dan-mcleran/

https://www.linkedin.com/pulse/neural-network-under-4kb-dan-mcleran/

https://www.linkedin.com/pulse/qformat-dan-mcleran/

I am continuing to develop this framework to add DQN, LSTM, other functionality. Any collaborators are welcome.

Regards,

Dan McLeran

[Nelson Ijih]

Hi Everyone,

I'm Nelson Ijih and co-founder of Blockmint technologies. We designed a dual-purpose ASIC for mining Monero and also perform AI inference. I worked at Intel prior to that on FPGAs. My Linkedin is here: https://www.linkedin.com/in/nelsonijih and Twitter: https://twitter.com/NelsonIjih

Looking forward to participation in the MLCommons community and thanks to David for putting this together.

Best Regards and Happy 2021!

Nelson Ijih

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[Zhiyang Ong]

G'Day All,
I am a Ph.D. student at Texas A&M University trying to design
hardware accelerators for machine learning applications.

Regards

[Nikola Nikolov]

Hi Everybody,

 

My name is Nikola Nikolov. I am software and AI developer at Supermicro. Prior that I was principal engineer at KLA (former KLA-Tencor) working on detection and classification of wafer defects with CNN.

I am looking forward to join MLCommons and Tensorflow communities. I am interested into automation of the benchmarking and inferencing.

Happy New Year!

 

Best Regards,

Nikola

 

From: David Kanter <da...@mlcommons.org>
Sent: Tuesday, January 5, 2021 2:45 PM
To: public <pub...@mlcommons.org>
Subject: Welcome new MLCommons public members, please introduce yourself!

 

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[Cheolkyoo Kim]

Hello, my name is Cheolkyoo, Kim, I am with Samsung Electronics and work on neural networks 

Best Regards,

Cheolkyoo, Kim

2021년 1월 6일 수요일 오전 10시 45분 28초 UTC+9에 Zhiyang Ong님이 작성:

[Zihong Zhou]

Hi Everyone.

Glad to join you! My name is Zihong Zhou, a Ph.D. student in computer science at Zhejiang University, China. I’m trying to design some low-cost but high-intelligence robots recently, so tinyML and NAS are my main focus.

Best Regards!

Zihong Zhou

[Nikolay Borissov]

Dear All

Thank you for having me. My name is Nikolay and I am a Data Scientist working on information retrieval and classification models for clinical trials analyses and relevant publications search. 

I studied computer science at Karlsruhe, after my PhD I worked as a software engineer in consulting and industry and since a year in startup https://www.risklick.ch

Here is my linkedin profile: https://www.linkedin.com/in/nikolayborissov/

I am happy for discussions with you.

Best Regards

Nikolay

[Dustin Zubke]

Hello all, 

I'm Dustin Zubke. For the past year, I have been working with Speak Labs, an English-language instruction app, to develop a phoneme recognition system for their Korean users. Previously, I worked in on-grid and off-grid solar and energy storage. 

My LinkedIn is: https://www.linkedin.com/in/dustin-zubke-074b8628/

Happy to be part of ML Commons and interested in attending a few meetings. 

All the best,

Dustin

To view this discussion on the web visit https://groups.google.com/a/mlcommons.org/d/msgid/public/CAHCHES3erRCMoWK8mgxZANmuDj%3D-rEj8RGFsudGq2QCU4qBjRQ%40mail.gmail.com.

[Rahul Shirale]

Hello, My name is Rahul, I just completed Harvard Business Analytics Program with distinction! Looking forward to using analytics in MLcommons!

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[Mark Johnson]

Hello, my name is Mark Johnson and I am a technologist at Western Digital with a 30yr background in relational databases and 10-15yr with flash storage technologies.  No background in AI/ML.  I am just now coming up to speed on MLPerf Inference for data center and edge, so I will probably be asking a lot of elementary questions.

[Jean-Louis QUEGUINER]

Hi everyone,

My name is Jean-Louis Queguiner, I'm the head of Data&AI at OVHcloud

I'm just coming up to speed to test our new infrastructure range on T4 mainly and check especially the impact of PCIe Lanes over T4 in the case of inference but maybe also on training (I'll see if I have time).

I'll share results in few months regarding that.

Also I have 40+ cards types/accelerators (FPGA/ASIC) that I'm looking to bench in a standard Apple to Apple way. Which is not that simple to be honest.

Feel free to connect here is my Linkedin : https://www.linkedin.com/in/jlqueguiner/

[Roselyn Isimeto]

Hi everyone,

My name is Roselyn Isimeto. I am an academic/Researcher at the University of Lagos, Nigeria.

I have been involved in building intelligent systems. 

tinyML is the future and I am super-excited about this as there are a lot of stuffs to be done in my part of the world using tinyML.

I would share some of my thoughts soon so anyone interested could collaborate with me on this beautiful journey!. 

I see so many beautiful opportunities begging to be tapped here! I need a team. 

Please feel free to connect here: https://www.linkedin.com/in/roselyn-isimeto-0454b744/

Thank you!!

Roselyn

[Brian Chami]

Hello all,

I'm Ibrahim (Brian) elchami, I'm a postdoc at the University of British Columbia. 

I'm building IoT and AI apps (edge AI, custom vision, and deep learning) on the 5G network, as a part of the UBC-Rogers smart campus project.

Some of the projects include:

- natural- asset management: Putting up sensors on trees to manage tree health. The same setup can be utilized later on for community/student engagement. 

- crowd analytics on green spaces on campus: leveraging 5G network to create a cheap, efficient network to use custom vision to detect cars, people, bikes on campus, which include road intersections. The approach in this is an ethical, data- responsible practice, that can be deployed later on in participating cities.     

- a few projects related to mobility and infrastructures. 

Feel free to connect with me on linkedin: https://www.linkedin.com/in/brian-chami-14459344/

Side projects on my portfolio: brianchami.com 

Happy to discuss any of the 5G/edge-AI projects or side projects. 

[Paweł Cyrta]

Hi All,

My name is Pawel. I'm  graduate student at interdisciplinary supercomputing center on Warsaw University.

I've been living for some time in Warsaw, Poland and cooperate remotely with companies as applied research contractor. 

Recently, i am researching multilingual semi-supervised affective speech embeddings (emotion) in noisy environment, in the wild.  

I do have years of experience in speech and audio processing. e.g.  In the past I was responsible for speech recognition and speech synthesis models in european languages for Samsung S-Voice. 

I hope to help in speech dataset group and I am planning to benchmark training of asr on my university computing cluster.

Happy to be now part of MLCommons community

Paweł Cyrta

[Jinle Zeng]

Hi Everyone,

I am Jinle Zeng from Baidu Company. I am an engineer working for PaddlePaddle deep learning framework. My interests include: large-scale distributed training, graph compiler for deep learning framework, AutoML, etc.

Happy to discuss with all of you.

Best Regards,

Jinle Zeng

[Philip Chow]

Howdy - I lead a Palo Alto-based startup seeking to tackle AI fairness. Kudos to this community! Best, Phil

[Jaideep Ray]

Howdy all ! I lead a team in ML Evaluation at Meta. 
Best, Jaideep.

[Ali Vahdat]

Hi all,

My name is Ali Vahdat, and I lead a research team at Thomson Reuters researching and developing NLP techniques for applications on legal documents.

Happy to be part of the MLCommons community.

Cheers,

-Ali

[Robin Fettelaar]

Hi everyone, I am Robin a second year AI student at Radboud University. I really enjoy to spend my free time testing out new AI (Deep Learning) methods and would love to join a working group at MLCommons. Currently, I do not yet have a large amount of practical experience in AI, but I am particularly interested in applying and exploring DL algorithms. However, due to the fact that I do not have a wide range of practical skills, I would be more than happy to explore any of the other workgroups.

Robin Fettelaar

[Huihuo Zheng]

Hi all, 

This is Huihuo. I am a staff scientist at Argonne Leadership Computing Facility. I am working on data management and I/O for AI workloads, data parallel deep learning for scientific AI. My current (and previous) works include developing I/O benchmarks and profiling tools for DL applications (DLIO), developing parallel data loader for scientific datasets, developing HDF5 library for exascale computing (ExaIO/ExaHDF5), etc. I just joined the storage working group a few days ago. I look forward to having more interaction with all of you. 

Best, 

Huihuo Zheng

[Hasan Amca]

Hi ML Friends,

 

I am Prof. Dr. Hasan Amca, I am teaching Artificial Neural Networks and supervising MSc and PhD research on Machine Learning blended research projects in EMU.

 

Prof. Dr. Hasan Amca

 

Electrical and Electronic Engineering Department

Eastern Mediterranean University

Famagusta,

Mersin 10 Turkey

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[Benson Muite]

Hi,

My name is Benson, I am a software developer based in Nairobi Kenya with
interests in performance and reproducible workflows. Look forward to
interacting with you and contributing to some of the efforts.

Regards,
Benson Muite

[Abhishek Kumar]

Hi,

I am a PostDoc in the Interactive Edge research group at the University of Oulu, Finland.  

Since 2021, I have been working on on-device machine learning, more specifically how to do efficient continual learning (i.e. robust to catastrophic forgetting) on embedded devices in multimodal sensing settings. 

This is the first work on this theme: Y. D. Kwon, J. Chauhan, A. Kumar, P. Hui. and C. Mascolo, "Exploring System Performance of Continual Learning for Mobile and Embedded Sensing Applications," 2021 IEEE/ACM Symposium on Edge Computing (SEC), 2021, pp. 319-332, doi: 10.1145/3453142.3491285.

Currently, I am interested in reformable TinyML, and hardware/software co-integration for building more energy-efficient edge AI computing infrastructures.

Looking forward to interacting with you all!

Kind Regards,

Abhishek

[Kate Hodesdon]

Hello everyone,

I'm a machine learning engineer at Graphcore. We're a chip company and one of the founding members of ML Commons. I work on porting and implementing neural networks on our novel hardware, so have an interest in application performance and the implications of new deep learning architectures on memory consumption.

My side projects include work on ML interpretability.

Looking forward to being part of the ML Commons community,

Kate

[Amay Iyer]

Pleased to be acquainted with all of you!

I am a Product Developer at IMMCO, we're an engineering services company that tailors SaaS and Infrastructure Solutions for Vertical Telecom Operators and Service Providers. I was looking into possible ways to utilize NVIDIA's ML modules especially Aerial SDK to implement better automative solutions but didn't know how broad the field of AI Acceleration is. I am still learning and I stumbled upon ML Commons via this article that outlines and rank certain AI Systems based on the MLPerf specifications. 

I am still a noob when it comes to these things but I hope I can learn more as I will be beginning my Masters in IT (with a concentration in AI) at the Royal Melbourne Institute of Technology the coming February. So far, my knowledge only composes of a few individual companies and the direction they're going with to meet the markets demand in the face of Moore's Law coming to a close like Mythic AI's analog microchips and whatnot but honestly I just understand such segments just as an anecdote and not in-depth as I would like to. 

I hope to learn more by engaging with the ML Commons community and am glad to be a part of this forum! Thanks for having me.

Best Regards,

Amay

[Julian Kunkel]

Hi all,
my name is Julian, I'm a professor at the University of Göttingen and
a deputy head of GWDG. We operate various HPC systems.
My key research interest is storage including analysis and
benchmarking. I'm involved in the IO500 benchmarking effort.
I heard that a benchmark for IO (with ML-inspired workloads) is
developed by you guys, this is of course very interesting to me and I
want to get involved.

Best,
Julian

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[jaynarayan thakurdas tudu]

Hello All,

 Myself Jaynarayan from India, IIT Tirupati. I work in Accelerator design and focus is to make the smaller device reliable for ML. 

I hope to contribute to the mlcommon society and get to learn from it.  

Regards,

Jay

शनि, 6 अग॰ 2022 को 6:02 am बजे को 'Julian Kunkel' via public <pub...@mlcommons.org> ने लिखा:

To view this discussion on the web visit https://groups.google.com/a/mlcommons.org/d/msgid/public/CAMcTfv7iNEbOOA7%2BrzsvDrCG-vQa_2e%3D_W3DMLiQeF0Vam6uhw%40mail.gmail.com.

[Nikhil Ghanathe]

Hello everyone,

My name is Nikhil, a PhD student at University of British Columbia. My current research interests lie with tinyML+FPGAs.  My most recent work was on early-exit networks for tiny-CNNs (https://arxiv.org/pdf/2207.06613.pdf)

I am looking forward to be involved in this community and interact with some of you! 

Cheers,

Nikhil

[Shantanu Sharma]

Hi everyone!

I'm Shantanu ― co-founder of Stem Lending, a consumer-direct mortgage shopping portal serving in the US markets.

In the past, I've worked on imaging genomics ML at GE Research and discrete event simulations based protein/RNA folding models at UNC Chapel Hill.

I'm interested in ML models' cost-effectiveness, scale, interpretability, fairness and expansion of ML applications.

Please feel free to connect: https://linkedin.com/in/shantanu   /   https://twitter.com/shantanu

Regards,
Shantanu

[Prerana Maslekar]

Hey All,

I am Prerana, Performance Verification engineer at Microsoft. I have worked with AI accelerator IPs so far, and would like to learn more about performance benchmarks and evolving architectures for ML. I graduated with Master's from UT Austin in 2019 where I worked on projects related to Parallelism and locality, and Tiny DarkNet on SoC.

I'm highly interested in exploring opportunities related to HPC and Benchmarks in Training. Excited to see the talent pool and looking forward to interact with everyone here! Feel free to connect: https://www.linkedin.com/in/psmaslekar/

Thanks,

Prerana 

[Dylan Muir]

Hi everyone

I‘m the VP for Global Research Operations at SynSense, and co-lead of the ML / Algorithms group at SynSense. We are a TinyML low-power inference ASIC startup, based in Zürich Switzerland, and with offices also in China.

I‘m interested in the Tiny Inference benchmarks, and arranging for us to contribute benchmark results and guide the benchmarks to be suitable for spiking NN inference.

Best regards

Dylan.

[SARADINDU SENGUPTA]

Hi,

I am Saradindu, currently working at  Nunam, an energy startup, where I am working on building li-ion battery analytics platform. Recently, we started working on ML accelerator SoCs to deploy our model closer to the assets and run inferences faster.

I also speak on MLOps and running ML production.

Recently, I became heavily interested in federated learning and running ML on resource constrained platforms. Feel free to contact me on LinkedIn: https://www.linkedin.com/in/saradindusengupta/

[David Aponte]

Hello everyone!

My name is David Aponte and I am software engineer at Microsoft focusing mostly on MLOps and performance. I am also doing distributed training research at NJIT as a part of the center for big data, so I am interested in participating in the training group :).

Really excited to be here!

I would love to connect on linkedIn:  David Aponte | LinkedIn

Best,

David

[arash.a...@mail.utoronto.ca]

Hi everyone! 

I'm Arash and I am a 3rd year Computer Engineering undergrad at the University of Toronto. I am currently a software engineering intern at Cerebras where I work on optimizing the training efficiency of large models. I've previously worked on a novel learning rate scheduler and NAS for CNNs. I'm mainly interested in theoretical optimization and training dynamics within deep learning so I'm heavily interested in participating in the algorithms research team :) 

However, I'm also open to contributing other fields as I am still exploring as an undergrad :) 

Here are my LinkedIn and Twitter, I'm always down to chat about stuff so feel free to reach out! 

Best,
Arash

[haejin kim]

Hi,

 

I'm  HaeJin from Testworks

Testworks provides one-stop service to collect, annotate, and manage training datasets, located at Seoul, Korea.

So, We are especially interested in the work of DataPerf WG.

 

Testworks also offer software testing service, as a KOLAS accredited testing institution.

As we collaborate with Semi-conductor companies, we are also interested in MLPerf benchmarks, for testing AI specialized processors.

 

Best,

HaeJin Kim. Researcher at Testworks

2021년 1월 6일 수요일 오전 7시 45분 1초 UTC+9에 da...@mlcommons.org님이 작성:

[Alperen Gormez]

Hello everyone,

My name is Alperen. I am a fourth year PhD student at University of Illinois Chicago. My research focus is reducing the inference & training costs of deep learning models. I have experience in early exit networks, pruning, knowledge distillation, quantization and sparsity.

My LinkedIn, Website, GitHub

Happy to join here!

[Adugna Necho Mulatu]

Hello everyone. This is Adugna Necho from Ethiopia, working at Bahir Dar University as a lecturer in computer engineering and now a PhD student there. In addition, I am Internet Society Ethiopia Chapter President.

I'm interested in embedded machine learning or tiny machine learning for IoT devices. 

Thanks!

[fabian schuetze]

Hello everybody,

My name is Fabian and I am a software engineer at roboception, a robotics startup in Munich. I am working on efficient ml training and inference.

I am looking forward to working with you.

Best wishes,

Fabian 

[Leon Wu]

Hi everyone,

I previously worked at Google on a compiler for their Edge TPU (ML accelerator), mainly the compiler frontend, debugging tools, and numerically debugging selected ML models. Got laid off about a week ago so I'm now checking out other ML-related roles, mainly at a higher level of abstraction (e.g. working with the models themselves), but keeping things open for now as I explore.

Feel free to reach out! Easiest ways to reach me are Twitter and email  lwgi...@gmail.com, thanks to David for showing me here :)

[Eric Han]

Welcome Leon! 

I co-chair Training, which focuses on benchmarking ML training performance. We're landing a benchmark for DLRM (recommendations) and GPT3. Please reach out if you have any questions about what might be best to explore at MLC. Glad to have you here!!

Eric

---

From: pub...@mlcommons.org <pub...@mlcommons.org> on behalf of Leon Wu <lwgi...@gmail.com>
Sent: Tuesday, January 31, 2023 10:59 AM
To: public <pub...@mlcommons.org>
Cc: fabian....@roboception.de <fabian....@roboception.de>; adugna...@gmail.com <adugna...@gmail.com>; da...@mlcommons.org <da...@mlcommons.org>

Subject: Re: Welcome new MLCommons public members, please introduce yourself!

Hi everyone, I previously worked at Google on a compiler for their Edge TPU (ML accelerator), mainly the compiler frontend, debugging tools, and numerically debugging selected ML models. Got laid off about a week ago so I'm now checking out

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[Eric Hunsberger]

Hi everyone,

I'm Eric, a Senior Research Scientist at Applied Brain Research (ABR). We do lots of work in the area of low-power AI, and are currently developing our own hardware AI accelerator for time-series processing. We also have a product called NengoEdge to allow users to train and test ML solutions across a variety of commercially available hardware, to see what solution might be right for them.

So I'm interested both in benchmarks that could be applied to our upcoming hardware, as well as benchmarks of other hardware that could help inform what we want to support with NengoEdge (in both cases, I'm most interested in inference benchmarks, not training so much).

Also, we have a novel type of neural network we're working with called the Legendre Memory Unit (LMU), and I heard that there were some people here discussing it (though I have yet to find that discussion, so if anybody knows where that is please point me there).

Looking forward to learning more about the great work going on in the MLCommons community, and seeing how we at ABR can contribute.

Best,

Eric Hunsberger

[Lexing Xie]

Dear all - Hello from Australia, pleased to meet you all. 

A brief self-intro: 

I teach a large Statistical Machine Learning class (200-300 students) in Australian National University https://sml-anu.github.io/
I lead the ANU Computational Media lab https://cm.cecs.anu.edu.au/, our recent interests are ML for sequences, graphs, and in social and economic systems 

I direct a large university initiative on ML-in-society with involving social sciences, law https://hmi.anu.edu.au/

I found this group from the deep learning tuning playbook github ... 

Loving ML commons as a source of fun + fresh things to say to my class (some of whom would become your colleagues in industry)

Look forward to making some connections that make  our academic research help each other. 

Cheers,

Lexing Xie 

[Yuankun Shi]

Hi All,

I am Yuankun, Shi, an AI Framework Engineer from Intel, working for MLPerf training/inference submission.

Will work with community more closely to optimize model on Intel platform.

Looking forward to learning more from the community.

Thanks,

Yuankun

[Chad Martin]

Hi everyone,

I'm Chad Martin and am helping to coordinate Graphcore's MLPerf activities.  We're particularly interested in the GNN work at the moment, but also staying on top of all of the great AI benchmarking efforts.  While my direct involvement in MLPerf is new, I was involved in most benchmarking activity between Intel and Dell over the prior two decades when I was an Intel FAE.

It's great to meet all of you and reconnect with a few of you that I've worked with before.

Regards,

Chad

[Yoni Sher]

Hi Everyone, 

I'm Yoni Sher, I work at Mobileye. We recently took an interest in benchmarking our proprietary chips (the EyeQ series) using standardized, "apples to apples" metrics, and we're learning to use the MLCommons methodology to do so. 

Best, 

Yoni Sher

[Sebastian Boblest]

Hi Everybody,

I'm Sebastian Boblest, I work at Bosch in the area of neural network deployment on micro controllers.

Best,

Sebastian

[Steve Mussmann]

Hi everyone!

I'm Steve Mussmann and I'm currently a postdoc at University of Washington working with Kevin Jamieson and Ludwig Schmidt where I research active learning/labeling and data pruning. I'm excited about benchmarking data-centric AI/ML and I'm looking forward to getting involved with DataPerf.

It's great to be here and meet everyone!

All the best,

Steve

[Anil Thomas]

Hello all,

Great to be part of this exciting community! At Akridata, we have built a platform that tackles Computer Vision development from a data-centric perspective. We look forward to seeing how the recently launched DataPerf challenges play out.

Cheers,

Anil

--

Senior Director of Applied Data Science

Akridata, Inc.

https://akridata.ai

[Romain Egele]

Hello everyone!

    I am Romain Egele, a 2nd year Ph.D. candidate at Université Paris-Saclay and Argonne National Laboratory. I worked for a few years on "Automated Deep Learning", especially on Hyperparameter optimization and Neural Architecture Search (what we could call "model-centric") and I am now interested in the data-centric aspect of AutoML in particular: bias and noise in data, domain adaptation, data augmentation.

Happy to join the community!

All the best,

Romain.

[Paolo Climaco]

Hello everyone,

My name is Paolo Climaco, and I am a PhD student in Mathematics at the University of Bonn. My research focuses on data-efficient machine learning regression in quantum chemistry.

Specifically, my research aims to interpret and develop model-agnostic strategies for training subset selection from a pool of unlabeled data points to improve the quality of predictions on the new data not used for training for various learning algorithms.

I'm excited to be a part of this community and look forward to discussing with fellow researchers in the field of data-efficient machine learning. Please get in touch with me with any questions or to chat about my research.

Best regards,
Paolo Cimaco

[Sankranti Joshi]

Hi All,

I am Sunny and I gonna be starting a PhD in Computer Vision focused on Environment/Remote Sensing focussing on Bayesian Meta Learning. I currently work as an AI/ML RDP Engineer at GSK. In the past I have worked in NLP Research, and as an ML engineer with time series models. 

Cheers!

[deepa lakshmi]

Hello all!

I am Deepa(https://www.linkedin.com/in/deepalakshmi-g-9276348/), ML practitioner with more than a decade of experience building end user facing large scale recommendation engines at eBay, Target, Expedia etc. for varying context/domain i.e. search ranking, product recommendations, keyword recommendation etc. 

My primary interest is in building ML models to solve for product use cases & all related areas of work involved from data, prototyping, shipping & monitoring production models.

Currently, in personal sabbatical & excited to be part of the community!

Thanks,

Deepa

[Seulkee Lee]

Hello Everyone,

My name is Seulkee. Currently I'm in career transition: I used to be a construction / engineering project management professional and now am building AI/ML solutions based on LLMs.  I'm interested in finding use cases for LLMs and generating and augmenting quality data. Hopefully I can bring the technology back to construction some day where adoption of new technology always seems to be behind other industries. 

Happy to be part of the community!

Best,

Seulkee

[Victor Olmedo]

Hello MLCommons community,

 

My name is Victor Alberto Olmedo, Global Analytics and AI Staff FSA @ Pure Storage.  I am looking forward, on a personal level, to help drive forward the goals of this community.  My domain experience is applied to finance and life sciences.

Victor Alberto Olmedo // Global Analytics and AI/ML Staff FSA//| Pure Storage, Inc.
  |  vol...@purestorage.com  |  

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[Niraj Kumar Singh]

Hi Everyone, 

My name is Niraj Kumar Singh. I am currently working as a Machine Learning Engineer at a healthcare startup called Inbound Health. Previously I have worked with healthcare startups like Curai Health and BenevolentAI. I have worked with LLMs and helped deploy them in production for clinical applications and in the customer support industry. I also enjoy working with biomedical knowledge graphs and currently working on linking LLMs with biomedical knowledge graphs for enforcing factual correctness. 

I would like to work on evaluating LLMs and their application in the biomedical domain. I am very happy to join this community and looking forward to contributing and learning from everyone. 

LinkedIn: https://www.linkedin.com/in/niraj17singh/

Thanks,

Niraj