Akash Deep Email & Phone Number
Who is Akash Deep? Overview
A concise factual answer block for searchers comparing this professional profile.
Akash Deep is listed as Researcher | Quantitative Finance Research Group, Texas Tech University at Texas Tech University, based in Lubbock, Texas, United States. AeroLeads shows a matched LinkedIn profile for Akash Deep.
Akash Deep previously worked as Co-Founder at Deepai Finance and Community Advisor at Texas Tech University. Akash Deep holds Master Of Science - Ms, Multi/Interdisciplinary Studies, 3.60/4.00 from Texas Tech University.
Email format at Texas Tech University
This section adds company-level context without repeating Akash Deep's masked contact details.
Review company-level records connected to Akash Deep before choosing the right outreach path.
About Akash Deep
Hello there! I'm Akash Deep, a data scientist, AI enthusiast, and co-founder of DeepAI Finance, where we use our wizardry in machine learning to supercharge stock analysis. With an arsenal of skills in applied physics and mathematics, I love transforming complex problems into simple, innovative solutions.Currently, I'm expanding my tech toolkit while pursuing a Master's in Computational Mathematics at Texas Tech University. In my past life, I've worn the hats of a community advisor and undergraduate research assistant, dabbling in everything from data analysis to quantum materials.My toolbox? Python, MATLAB, JavaScript, C/C++, and more. TensorFlow, Keras, and Scikit are the frameworks I juggle. Always up for learning new tricks, tackling challenges, and making a difference. Feel free to reach out if you're interested in talking about tech, collaboration, or the future of AI!
Akash Deep's current company
Company context helps verify the profile and gives searchers a useful next step.
Akash Deep work experience
A career timeline built from the work history available for this profile.
Co-Founder
CurrentCo-Founded Deep AI Finance-At DeepAI Finance, we are committed to providing cutting-edge, research-based solutions to our clients. Our team actively engages in research and contributes to the growing body of knowledge in the field of AI and finance. Our published research papers serve as a testament to our commitment to advancing the state of the art in.
Community Advisor
Worked with a team of 18 other CA’s for community building, administration, on-call/crisis response and departmental and campus support on on-campus residents.Lead role in establishing a community environment focused on student learning and student success.Collaborated with internal and external stakeholders to meet the needs of complex residents via.
Undergraduate Student Researcher
Student Assistant
Akash Deep education
Master Of Science - Ms, Multi/Interdisciplinary Studies, 3.60/4.00
Bachelors, Applied Physics
Physics Chemistry And Mathematics
Frequently asked questions about Akash Deep
Quick answers generated from the profile data available on this page.
What company does Akash Deep work for?
Akash Deep works for Texas Tech University.
What is Akash Deep's role at Texas Tech University?
Akash Deep is listed as Researcher | Quantitative Finance Research Group, Texas Tech University at Texas Tech University.
Where is Akash Deep based?
Akash Deep is based in Lubbock, Texas, United States while working with Texas Tech University.
What companies has Akash Deep worked for?
Akash Deep has worked for Texas Tech University, Deepai Finance, Hodovanets Quantum Materials Lab, and Ttu Hospitality Services.
How can I contact Akash Deep?
You can use AeroLeads to view verified contact signals for Akash Deep at Texas Tech University, including work email, phone, and LinkedIn data when available.
What schools did Akash Deep attend?
Akash Deep holds Master Of Science - Ms, Multi/Interdisciplinary Studies, 3.60/4.00 from Texas Tech University.
Search by job title, company, industry, location, and seniority. Export verified B2B contact data when you need it.
Start free trialCheck these profiles if this is not the Akash Deep you were looking for.
View similar profiles